Conditional Survival Probability of Non-Small Cell Lung Cancers, Based on The SEER Database

Conditional Survival Probability of Non-Small Cell Lung Cancers, Based on The SEER Database | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Conditional Survival Probability of Non-Small Cell Lung Cancers, Based on The SEER Database Shixu Fang, Kui Zhai, Xixian Ke, Hao Han, Hongling Lu, Gang Xu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-138915/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: This study aims to explore the dynamic survival probability of lung cancers after resection based on those had survived several years, provide more precise monitoring and treatment information for non-metastatic non-small cell lung cancer (NSCLC) patients. Materials and Methods: In the Surveillance, Epidemiology, and End Results (SEER) database (2000–2016), 95531 eligible non-metastatic NSCLC patients after surgery were enrolled, TNM stage were reclassified, the methods of condition survival probability (CS) and actuarial overall survival (OS) were used to explore the relationship between clinicopathological characteristics and cancer prognosis. Results: The 1-, 3-, 5- and 10-year OS of included patients were 83.6% (95%CI: 83%-84%), 62.9% (95%CI: 62.6%-63.1%), 50.8% (95%CI: 50.6%-51.0%) and 33.1% (95%CI: 32.7%-33.6%) respectively. For those already survived 1, 2, 3, 4 and 5 years after diagnosis, the probability for surviving an additional 3 years were 67%, 71%, 73%, 75% and 77% respectively. Enrolled population were reclassified into 9 cohorts including T1aN0, T1bN0, T1cN0, T2aN0, T2bN0, T3N0, T4N0, T1-4N1, T1-4N2 according to 8th TNM staging. According to the conditional survival probability, patients with unfavorable tumor stage diagnosed initially at surgery had the significant improvement in CS over time. Analysis based on other clinical features demonstrated similar conclusion that the poorer the initial diagnosis, the more significant the benefit of conditional survival over time. Conclusion: The worse the patient's prognosis, the more significant the benefit of time-dependent conditional survival probability, long-lived cancer patients may have a better cancer prognosis. Cancer Biology Non-small cell lung cancer Non-metastasis postoperative conditional survival probability SEER database Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Survival estimates for cancer patients was traditionally based on TNM stage at the time of diagnosis or after diagnosis or treatment [ 1 ], which answered prognostic questions that many cancer patients care about. This result makes the 5-year survival rate of cancer patients a fixed value, and could be understood as "static survival estimate" [ 2 ]. However, for those who have survived for several years after diagnosis, the survival probability established at the time of diagnosis may not be applicable, because the overall survival rate of patients includes those who died within the first few years, as well as those who have passed through the first few years and "stand out" from them. For those patients pass through the first few years, the doubt troubling them may be "If I have already lived x years after diagnosis, what is the probability that I survive for another y years". In the past few years, the occurrence of conditional survival (CS) probability has given this question an exact answer [ 3 ], the CS refers to the probability of surviving for another n years if the patient with chronic disease has been alive for m years after diagnosis or treatment, the concept was derived from the conditional probability in biostatistics [ 4 – 6 ]. It can provide a dynamic and more precise survival rate for cancer patients [ 7 ]. It is well known that the prognosis of cancer patients who survived in the first few years will be better, because the impact of death risk factors on the prognosis of patients will gradually weaken over time [ 8 – 10 ], and as we all known, for those patients who have pass through the first few years after radiotherapy or chemotherapy, the adverse effects of radiotherapy and chemotherapy on the body gradually weaken. Conditional survival means that, on average, the prognosis of long-term cancer survivors are better than these newly diagnosed patients [ 11 – 13 ]. This study aims to explore the postoperative conditional survival of patients with non-distant metastatic non-small cell lung cancer, providing more powerful information for doctors to formulate treatment plans and monitoring plans, giving patients and doctors a new understanding of cancer prognosis. 2. Patients And Methods 2.1. Data Source The patients of this study was selected from the National Cancer Institute database (The Surveillance, Epidemiology, and End Results, SEER) [14]. The raw data in this investigation was downloaded from the SEER web site (https://seer.cancer.gov/data/) via SEER*Stat in client-server mode after we submitted a request for access and signed the SEER research data agreement. 2.2. Study Population In this study, non-metastatic NSCLC from 18 registration centers in the SEER database were obtained. Since the SEER database is a public database, analysis of lung cancer patients does not require informed consent and institutional review. The clinical pathological characteristics of the patients were screened, the inclusion criteria are: 1) 15 years old or older patients diagnosed with lung cancer between 2000 and 2016 years; 2) with definite pathological diagnosis of NSCLC; 3) Single primary tumor; 4) Complete follow-up data (patients who died within 1 month after diagnosis were excluded, lack of specific follow-up time was also excluded); 5) Complete clinical pathological characteristics (such as age, tumor size, whether surgery, TNM stage). Exclusion criteria include: 1) metastatic lung cancer; 2) lack of T and N stages; 3) Tumor size is not available, histological and grade information is unclear; 4) diagnosis based on autopsy or death certificate only; 5) Died within one month of diagnosis or lack of follow-up data. The patient’s TNM staging was reclassified based on the eighth edition of the American Joint Committee on Cancer (AJCC) staging standard according to the tumor size. Detail in Figure 1 . 2.3. Statistical Analyses The analysis of this study is based on two steps. First, TNM stage was reclassified based on tumor diameter according to the 8 th version of the American Joint Committee on Cancer (AJCC) staging (T1aN0, T1bN0, T1cN0, T2aN0, T2bN0, T3N0, T4N0, T1-4N1, and T1-4N2). Clinicopathological characteristics were also stratified, such as surgical situations, positive lymph nodes, tumor grade, tumor size and patient age. (Details in Table 1 ). Subsequently, Kaplan-Meier method was used to analyze actuarial survival rate of cancers, such as 5-year survival rate or 10-year survival rate. Most of the missing values in this article were eliminated. Another statistical method involved in this study is the conditional survival probability. To illustrate how we obtain conditional survival estimates from the cumulative survival estimates, suppose we are interested in the population’s 5-year lung cancer survival probability conditioned on already having survived 5 years. The estimate is obtained by dividing the cumulative survival at 10 years by the cumulative survival at 5 years. The 1-year lung-cancer survival estimates conditioned on already having survived 5 years after diagnosis are derived by dividing the cumulative survival estimates at 6 years by the cumulative survival estimates at 5 years. Subtracting this survival probability from 1 gives the probability of dying in the year conditioned on having already survived 5 years. CS was adopted to estimate the survival probability, the mathematical definition of CS could be expressed as: CS ( n | m ) = S ( n ) / S ( m ), ( m < n ), where CS ( n | m ) is the probability of survival n years assuming that patient have already survived for m years after diagnosis. In this study, we estimated the additional 5-year conditional survival probability of patients given that they have already survived x years using the mathematical formula：CS( x +5ǀ x ) = OS( x +5)/OS( x ). Finally, the differences between the actuarial OS and the CS of the population were compared and analyzed. All statistical methods were implemented by Graphpad prism version 8.0.2 and R language 3.6.3 version, all statistical tests are two-sided, P value <0.05 is considered statistically significant. 3. Results Overall Population From 2000 to 2016 years, 95,531 postoperative patients with non-metastatic NSCLC were included (For ease of comparison, 4346 non-surgical patients were also included in this study). The average age of the patients was 62 years old. Almost half of the patients were male (46863, 49%). Stages distribution (re-staged according to the tumor size) were as follows: 4499 cases (9.42%) with pT1aN0, 21138 cases (22.13%) with pT1bN0, 17254 cases (18.06%) pT1cN0, 9587 cases (10%) with pT2aN0, 5100 cases (5.33%) with pT2bN0, 4790 cases (5.01%) with pT3N0, 4409 cases (4.61%) with pT4N0, 12021 cases (12.58%) with pT1-4N1, 11517 cases (12.05%) with pT1-4N2. The average of tumor size is 3.32cm, Grade I-IV and unknown were accounts for 13.5%, 36%, 33%, 2.5% and 15% respectively, the primary tumor site was divided into the upper lobe, middle lobe, lower lobe and other locations, positive regional lymph nodes accounted for 36058 (37.8%). The surgical intervention situations were divided into non-operation, local ablation or cauterization, sublobar resection, lobectomy, pneumonectomy and other surgical methods. 22,530 patients (23.5%) received chemotherapy and 12,631 patients (13.1%) received radiotherapy ( Table 1 ). At the last follow-up, the median follow-up time was 62 months, the number of deaths or events was 51,175. 1-year, 3-year and 5-year OS were 83.6% (95%CI: 83%-84%), 62.9% (95%CI: 62.6%-63.1%) and 50.8% (95%CI: 50.6%-51.0%) respectively. Figure 2(A) shows the rapid decline of overall survival rate in the first three years. Although the overall survival of lung cancers shows unsatisfactory, for those living several years after diagnosis, the mortality rate is gradually decreasing Figure 2(B) and the probability rates for surviving an additional 5 years were steadily increased ( Figure 2(C-D) and Table 2 ). Figure 3 shows the decrease of the actuarial survival rates over time and the increases of estimated CS(8) for 1-5 years in total patients, which demonstrated that as the survival time of cancers increases, the gap between overall survival rate and conditional survival rate becomes more significant. 8 th T and N stage Enrolled population were reclassified into 9 groups including T1aN0, T1bN0, T1cN0, T2aN0, T2bN0, T3N0, T4N0, T1-4N1, T1-4N2 according to 8 th TNM staging. The actuarial survival probability and conditional survival probability of these 9 groups were also explored. According to the results exhibited in Table 3 , the worse the TNM stage, the lower the overall survival rate of cancers, for example, 5-year OS in T1aN0 cohort is 73% (95%CI: 72%-74%), T2aN0 cohort is 54% (95%CI: 53%-55%), T3N0 cohort is 46% (95%CI: 44%-47%), T4N0 cohort is 39% (95%CI: 37%-40.5%). Analysis based on conditional survival probability indicating that the worse the prognosis of those who survived the first few years of diagnosis, the more significant the improvement of the survival probability, and for patients with a relatively well initial prognosis, the corresponding increase in conditional survival probability is not obvious. For example, in the T4N0 cohort, the 8-year OS rate is 30% (95%CI: 27%-32%), corresponding, for these who have survived for 5 years, the probability surviving another 3 years (according to the mathematical formula, it could be described as CS (8ǀ5)) is 78%. The actuarial 8-year OS of T3N0 cohort is 34% (95%CI: 31%-36%), corresponding, the CS (8ǀ5) was 74% (95%CI: 72%-75%). The actuarial 8-year OS of T1aN0 patients is 62% (95%CI: 60%-64%), corresponding, the CS (8ǀ5) was 85 % (95%CI: 83%-86%) (Difference is 23%; P <0.001) ( Figure 4A ). Pathological types Other tumor prognostic factors were also explored in this study. Analysis based on pathological types showed that the prognosis of patients with adenocarcinoma is better than other types including squamous cell carcinoma, adenosquamous cell carcinoma and large cell carcinoma ( Figure 4(A) ). For those surviving in the first few years after diagnosis, the worse the prognosis of pathological types (such as squamous cell carcinoma (SCC), adenosquamous cell carcinoma (ACC), and large cell carcinoma (LCC)), the more significance the conditional survival probability benefit, for example, in the adenocarcinoma cohort (n 55,592), the 8-year OS is 46.3% (95%CI: 45%-47%), but the 8-year survival rate for those who had survived 5 years after diagnosis is 79% (95%CI: 78%-80%), the difference is 22.7%. Simultaneously, in the SCC cohort (n 24,062), the probabilities of CS(8) increased from 30.2% (95%CI: 29%-33%) at baseline to 70% (95%CI: 67%-74%) at 5 years of follow-up, the probabilities of CS(8) in the ACC cohort (n 2,188) increased from 29.3% (95%CI: 27%-31%) at baseline to 72% (95%CI: 67%-76%) at 5 years of follow-up, and in the LCC cohort (n 3,712) increased from 29.4% at baseline to 74% at 5 years of follow-up ( Figure 4(B) and Table 4 ). It indicated that the longer cancer patient survives, the more improvement of survival prognosis they would get, and the less significant the influence of pathology type on cancer prognosis. Tumor size Compared with the patients with tumor size less than 3cm (5-year OS is 60.7% (95%CI: 59%-62%)), the bigger tumor size shows a unsatisfactory 5-year OS (the 5-year OS of 3.1-5.0cm cohort, 5.1-7.0cm cohort and more than 7.0cm cohort were 45.7% (95%CI: 45%-46%), 39.3% (95%CI: 38%-40%) and 31.2% (95%CI: 30%-32%) respectively) ( Figure 4(C) ), the 8-year survival probability given that the patient has lived for the first 5 years after diagnosis in the less than 3cm cohort, 3.1-5.0cm cohort, 5.1-7.0cm cohort and more than 7.0cm cohort were 78% (95%CI: 77%-79%), 74% (95%CI: 73%-74%), 74% (95%CI: 72%-76%) and 76% (95%CI: 73%-78%) respectively, which did not show a significant difference, indicating that, after a period of survival, patients with poor initial prognosis could obtain greater survival benefits when compared with those better initial prognoses ( Figure 4(D) ). Surgical intervention In this study, the approaches of surgical interventions included no surgery perform, local ablation or electrocautery, sublobar resection, lobectomy and others, the corresponding 5-year OS were 5.4% (95%CI: 5%-6%), 19.9% (95%CI: 17%-23%), 48.2% (95%CI: 47%-49%), 56.4% (95%CI: 54%-58%) and 40.6% (95%CI: 37%-44%) respectively ( Figure 4(E) ), we also analyzed the 5-year survival probability of those who already lived for the first 2 years after diagnosis (CS (5ǀ2)), the CS (5ǀ2) of the above 5 interventions were 34% (95%CI: 30%-38%), 41% (95%CI: 35%-47%), 66% (95%CI: 65%-68%), 73% (95%CI: 72%-73%) and 66% (95%CI: 65%-68%) respectively (( Figure 4(F) ) and Table 4 ), which demonstrated that the cancer prognosis increased rapidly for those who survived the first few years, this result greatly encourages cancer survivor. Patient age As shown in Figure 4(G) , the 5-year OS of patients in different age groups are significantly different, specifically, the 5-year OS of those ages range from 15-45, 45-70 and over 70 years old were 77.1%, 56.1 % and 41.8% respectively. For these had survived 5 years after surgery, The probability for living another 3 years (CS (8ǀ5)) were 93%(+15.9%) in patients aged 15-45 years, 81% (+24.9%) in patients aged 45-70 years and 65% (+23.2%) in patients aged ≥71 years Figure 4(H) , suggesting that the significant survival benefit would be got for those survived the first few years. Other pathological features Actuarial survival probability and condition survival probability of other pathological features were also analyzed including gender Figure 5(A-B) , chemotherapy Figure 5(C-D) , radiotherapy Figure 5(E-F) , positive lymph nodes Figure 5(G-H) , SEER stage Figure 6(A-B) , primary tumor site Figure 6(C-D) . The results showed that the chemotherapy cohort and the radiotherapy cohort, lymph node positives (more than 16), the SEER stage was regional, Caucasian, primary tumor site lie in whole lung or bronchus were associated with lower 5-year actuarial survival ( Table 4 ). At the same time, time-dependent conditional survival probability was also explored, for example, patients in the female group had an actuarial 5-year OS of 57.4%, while the 5-year survival probability of these who had survived for 2 years (CS (5ǀ2)) is 74%. The 5-year OS in the male cohort is 44%, and the CS (5ǀ2) is 67% ( Figure 5(B) ). Simultaneously, the 5-year OS in the chemotherapy cohort is 42.1%, and the CS (5ǀ2) is 62%, corresponding difference in the non-chemotherapy cohort is 19.6% ( Figure 5(D) ), patients in the radiotherapy cohort had an actuarial 5-year OS of 30.2% and a CS (5ǀ2) of 54%, The detailed overall survival rates and conditional survival probability of other tumor prognostic factors were showed in Table 4 . 4. Discussion The view that the risk of tumor-specific death decreases with the length of postoperative survival is called conditional survival. Conditional survival (CS) means that, on average, long-term cancer survivors have a better prognosis than newly diagnosed individuals [15-17], because most of the patients who survived after the first few years were those respond well to treatment, and the condition was alleviated, the complications were controlled, adverse reactions caused by surgery, radiotherapy and chemotherapy gradually weakened and the threat of death-related risks is gradually reduced [4]. The 5-year overall survival rate of the enrolled patients is 51%, For these who have survived 1-, 2-, 3-, 4- or 5 years after the diagnosis of cancer, the probability to survive another 3 years is 67%, 71%, 73%, 75% and 77% respectively, demonstrated that the survival probability increasing gradually as patients survive longer. The results showed that the 5-year OS of patients with T1aN0 to T1-4N2 gradually decreases, range from 55% of T1aN0 to 17% of T1-4N2, which brought frustrating results to those patients initially diagnosed with advanced disease. However, it is gratifying to observe the significant improvement in CS as patients survive longer, especially for those with advanced disease. For example, the difference between 5-year actuarial OS and CS (5ǀ3) in T1aN0 cohort is 15%, T2aN0 is 27%, T3N0 is 35%, and T4N0 is 39% ( Figure. 4D ). We can also note that, for these long-term cancer survivors, the difference in conditional survival probability of people with different T and N stages gradually narrowed, tending to be consistent. In other words, for these had survived 5 years after diagnosed, the probability of patients still alive in the tenth year in T1aN0, T2aN0, T3N0, T4N0, T1-4N1 are 76%, 63%, 64%, 67% and 60% respectively, which revealed that the survival prognosis of patients is not only related to clinical pathological factors, but also to the survival time of patients after surgery, and as the survival time is prolonged, the prognosis of patients increasingly shows time dependence. The results of the age-based grouping show that the survival prognosis of patients in different age groups varies greatly, the 5-year OS of the elderly patients is the unsatisfactory (32.4%), and the young patients is the best (46.5%). In the 15-45 cohorts, the 3-year conditional survival probabilities increased from 83% at baseline to 93% at 60 months, in these aged more than 70 years old, the CS3 increased from 56% at baseline to 65% at 60 month. Compared with young patients and middle-aged patients, the improvement of conditional probability in elderly patients is not significant, which may be due to the long smoking time of elderly patients, the high incidence of cardiovascular diseases and respiratory diseases or the poor physical performance of elderly patients caused by. Other tumor characteristics, including poor histological grade, larger tumor size, adenosquamous carcinoma, lymph node involvement, male, Caucasians, tumor located in the middle lobe and seed stage were associated with poor survival prognosis ( Figure 6 ). However, from the perspective of long-term survival of patients, it may be more meaningful to explore the conditional survival probability and compare the actuarial OS and CS. Although unfavorable clinicopathological features show poor 5-year OS, the benefit of conditional survival becomes very significance with the survival time of patient increases. For example, in the cohort of more than 16 lymph node metastasis, compared with the 5-year OS of all patients, those survived the first three years after diagnosis (CS (5ǀ3)) shows a better 5-year survival rate, increased by 16% (55%-71%), while patients without lymph node metastasis increased by only 4% (75%-79%). Similarly, Patients with larger tumor diameters increased CS (8ǀ5) by 26% and patients with smaller tumor diameters increased by only 5% ( Figure 3 ). Those patients with adverse clinical factors did not pass the most critical period and died within the first few years, as the years of survival of specific patients increase, these adverse prognostic factors that affect the prognosis become increasingly unrelated. Therefore, our data suggests that CS may be a more valuable tool late in the postoperative period to estimate the prognosis of patients who are predicted to die based on initial actuarial estimates. Some limitations of this study should not be overlooked. First, this study is a retrospective study. Inevitable deviations would be appear in the collection of clinical pathological characteristics, diagnosis and treatment of patients; second, the diagnosis of patients in this study the time span is large (2000-2016). The impact between lung cancer patients diagnosed in different periods and the prognosis has not been explored. Third, multiple primary tumors were excluded in order to eliminate interference, but the errors were unavoidable in reclassified the T stage and N stage. Nonetheless, this study also proposes a dynamic assessment of the conditional survival probability of lung cancer patients, thereby allowing adjustment of the predicted survival time after lung resection. The tool may prove useful to patients, doctors and researchers, and will guide dynamic and personalized clinical management decisions. Conclusion The worse the initial diagnosis of cancer patient, the more significant the benefit of time-dependent conditional survival probability, long-lived cancer patients may have a better cancer prognosis. Abbreviations NSCLC: non-small cell lung cancer SEER: Surveillance, Epidemiology, and End Results CS: condition survival probability OS: overall survival AJCC: American Joint Committee on Cancer SCC:squamous cell carcinoma ACC: adenosquamous cell carcinoma LCC:and large cell carcinoma Declarations Ethics approval and consent to participate This manuscript does not involve animal and the SEER database is a public database, analysis of lung cancer patients does not require informed consent and institutional review. So it has not yet applied the Ethics approval and consent to participate. Consent for publication Not applicable. Availability of data and materials The datasets supporting the conclusions of this article were included within the article Conflict of interest The authors declare no conflict of interest. Founding This research was supported by the National Natural Science Foundation of China (grant number 81960532). Author contributions Project design: Gang Xu and Hongling Lu; Searched databases and performed literature screen: Shixu Fang and Xixian Ke; Data extraction and analysis: Kui Zhai and Hao Han; Evaluated the quality of included literature: Shixu Fang; Manuscript writing: Gang Xu, Shixu Fang, XixianKe and Hongling Lu. Final draft was approved by all the authors. Acknowledgments Not applicable. Authors' information s 1 Department of Thoracic Surgery, The Affiliated Hospital of Zunyi medical university, 149 Dalian road, Zunyi, Guizhou, 563000, China 2 Department of biochemistry, Zunyi medical university, No.6 xuefu west road, xinpu new area, Zunyi, Guizhou, 563099, China References Feinstein AR, Sosin DM, Wells CK: The Will Rogers phenomenon. Stage migration and new diagnostic techniques as a source of misleading statistics for survival in cancer . The New England journal of medicine 1985, 312 (25):1604-1608. FL G: TNM: our language of cancer . CA: a cancer journal for clinicians 2004, 54 (3):129-130. Skuladottir H, Olsen JH: Conditional survival of patients with the four major histologic subgroups of lung cancer in Denmark . Journal of clinical oncology : official journal of the American Society of Clinical Oncology 2003, 21 (16):3035-3040. Zabor EC, Gonen M, Chapman PB, Panageas KS: Dynamic prognostication using conditional survival estimates . Cancer 2013, 119 (20):3589-3592. Hieke S, Kleber M, König C, Engelhardt M, Schumacher M: Conditional Survival: A Useful Concept to Provide Information on How Prognosis Evolves over Time . Clinical cancer research : an official journal of the American Association for Cancer Research 2015, 21 (7):1530-1536. Wang P, Sun Z, Wang W, Deng J, Wang Z: Conditional survival of patients with gastric cancer who undergo curative resection: A multi-institutional analysis in China . 2018, 124 (5):916-924. van Erning FN, van Steenbergen LN, Lemmens V, Rutten HJT, Martijn H, van Spronsen DJ, Janssen-Heijnen MLG: Conditional survival for long-term colorectal cancer survivors in the Netherlands: who do best? European journal of cancer (Oxford, England : 1990) 2014, 50 (10):1731-1739. Zhong Q, Chen QY, Li P, Xie JW, Wang JB, Lin JX, Lu J, Cao LL, Lin M, Tu RH et al : Prediction of Conditional Probability of Survival After Surgery for Gastric Cancer: A Study Based on Eastern and Western Large Data Sets . Surgery 2018, 163 (6):1307-1316. Ito Y, Miyashiro I, Ito H, Hosono S, Chihara D, Nakata-Yamada K, Nakayama M, Matsuzaka M, Hattori M, Sugiyama H et al : Long-term survival and conditional survival of cancer patients in Japan using population-based cancer registry data . Cancer science 2014, 105 (11):1480-1486. Thuret R, Sun M, Abdollah F, Schmitges J, Shariat SF, Iborra F, Guiter J, Patard JJ, Perrotte P, Karakiewicz PI: Conditional survival predictions after surgery for patients with penile carcinoma . Cancer 2011, 117 (16):3723-3730. Kurta ML, Edwards RP, Moysich KB, McDonough K, Bertolet M, Weissfeld JL, Catov JM, Modugno F, Bunker CH, Ness RB et al : Prognosis and conditional disease-free survival among patients with ovarian cancer . Journal of clinical oncology : official journal of the American Society of Clinical Oncology 2014, 32 (36):4102-4112. Palumbo C, Mistretta FA, Knipper S, Pecoraro A, Tian Z, Shariat SF, Saad F, Simeone C, Briganti A, Antonelli A et al : Conditional Survival of Patients With Nonmetastatic Renal Cell Carcinoma: How Cancer-Specific Mortality Changes After Nephrectomy . Journal of the National Comprehensive Cancer Network : JNCCN 2020, 18 (1):44-51. Huang JF, Chen D, Zheng XQ, Lin JL, Wang XY, Wu AM: Conditional survival and changing risk profile in patients with chordoma: a population-based longitudinal cohort study . 2019, 14 (1):181. Cronin KA, Ries LA, Edwards BK: The Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute . Cancer 2014, 120 Suppl 23 :3755-3757. Latenstein AEJ, van Roessel S, van der Geest LGM, Bonsing BA, Dejong CHC, Groot Koerkamp B, de Hingh I, Homs MYV, Klaase JM, Lemmens V et al : Conditional Survival After Resection for Pancreatic Cancer: A Population-Based Study and Prediction Model . Annals of surgical oncology 2020. Chen QY, Zhong Q, Zhou JF, Qiu XT, Dang XY, Cai LS, Su GQ, Xu DB, Lin GT, Guo KQ et al : Conditional survival and recurrence of remnant gastric cancer after surgical resection: A multi-institutional study . Cancer science 2020, 111 (2):502-512. Yan L, Chen F, Chen L, Lin J, Chen Q, Bao X, Qiu Y, Lin L, Zheng X, Pan L et al : Dynamic evaluation of conditional survival in patients with oral squamous cell carcinoma after surgical resection: A large-scale prospective study . Oral oncology 2020, 104 :104639. Tables Table 1: Baseline characteristics of enrolled patients with NSCLC in the SEER database. Variables Total cohort , n (%) No. patients (%) 95531 Mean (median) age, years 62(62) Age 15-45 years 3046 (3.2) 46-70 years 51191 (53.6) ≥70 years 40494 (43.2) Gender, n (%) Female 48668 (50.9) Male 46863 (49.1) Race, n (%) White 81013 (84.8) Black 8127 (8.5) other 6391 (6.7) 8 th AJCC* pathological stage, n (%) Stage Ⅰ 52478 (54.9) Stage Ⅱ 18726 (19.6) Stage Ⅲ 19136 (20) Unknown 5191 (5.5) Pathological T stage, n (%) pT1 53086 (55.5) pT2 22645 (23.7) pT3 8330 (8.7) pT4 11470 (12.1) Pathological N stage, n (%) pN0/pNx 71968 (75.3) pN1 12021 (12.6) pN2 11517 (12.1) pN3 25 (0.026) Tumour grade, n (%) grade Ⅰ 12681 (13.5) grade Ⅱ 34063 (35.7) grade Ⅲ 31540 (33) grade Ⅳ 2390 (2.5) Unknown 14857 (15.3) Tumour size, n (%) ≤30 mm 53086 (55.5) 31-50 mm 22645 (23.7) 51-70mm 8330 (8.7) ≥ 71 mm 4982 (5.2) Unknown 6268 (6.5) Histological subtype, n (%) Adenocarcinoma 55592 (49.1) Squamous cell carcinoma 24062 (25.2) Adenosquamous carcinoma 2188 (2.3) Large cell carcinoma 3712 (3.9) Other 18676 (19.5) Primary tumor site Upper lobe 53757 (56.3) Middle lobe 5213 (5.5) Lower lobe 29529 (30.1) Other 7032 (7.1) Type of surgery local distribution or excision 722 (0.75) Sublobar resection 14615 (15.3) Lobectomy 65951 (59) Resection of whole lung 9897 (10.4) No surgery 4346 (4.5) Number of positive lymph node 0 59473 (62.3) 1-15 19657 (20.6) ≥ 16 16401 (17.1) Radiation Yes 13133 (13.7) No 82398 (86.3) Chemotherapy Yes 22530 (23.6) No 73001 (76.4) Seer stage local 47912 (50.2) regional 43359 (45.4) Unknown 4260 (4.4) Table 2: Probability of patients with NSCLC resection can reach a certain survival time after a period of survival. Years already survived Survival probability to reach X years 0 Year 1 Year 2 Year 3 Year 4 Year 5 Year 6 Year 7 Year 8 Year 1 Year 0.84 (0.83-0.84) 1 2 Year 0.72 (0.72-0.72) 0.86 (0.86-0.86) a 1 3 Year 0.63 (0.63-0.63) 0.75 (0.75-0.76) 0.88 (0.87-0.88) 1 4 Year 0.56 (0.56-0.57) 0.67 (0.67-0.68) 0.78 (0.78-0.79) 0.89 (0.89-0.90) 1 5 Year 0.51 (0.51-0.51) 0.61 (0.60-0.61) 0.71 (0.70-0.71) 0.81 (0.80-0.81) 0.90 (0.90-0.91) 1 6 Year 0.46 (0.46-0.47) 0.55 (0.55-0.56) 0.64 (0.64-0.65) 0.73 (0.73-0.74) 0.82 (0.82-0.83) 0.91 (0.91-0.91) 1 7 Year 0.42 (0.42-0.43) 0.51 (0.50-0.51) 0.59 (0.59-0.59) 0.67 (0.67-0.68) 0.75 (0.75-0.76) 0.83 (0.83-0.84) 0.92 (0.91-0.92) 1 8 Year 0.39 (0.38-0.39) 0.47 (0.46-0.47) 0.54 (0.54-0.55) 0.62 (0.61-0.62) 0.69 (0.69-0.70) 0.77 (0.76-0.77) 0.84 (0.84-0.85) 0.92 (0.91-0.92) 1 9 Year 0.36 (0.35-0.36) 0.43 (0.42-0.43) 0.50 (0.49-0.50) 0.57 (0.56-0.58) 0.64 (0.63-0.64) 0.71 (0.70-0.71) 0.78 (0.77-0.78) 0.85 (0.84-0.85) 0.92 (0.92-0.93) 10 Year 0.33 (0.33-0.34) a 0.40 (0.39-0.40) 0.46 (0.46-0.47) 0.53 (0.52-0.53) 0.59 (0.58-0.60) 0.65 (0.65-0.66) a 0.72 (0.71-0.72) 0.78 (0.78-0.79) 0.85 (0.85-0.86) number at risk 95531 74924 59279 47592 38626 31546 25838 21029 17207 a For example, if patients had survived for 1 year, the probability to survived another 1 year is 86%. If patients had survived for 5 year after diagnosis, the survival probability of 10-year is 65%, and the 10-year survival probability for these initial diagnosis of cancer is 33%. Table 3: Actual survival rates of 5-15 years, Conditional 5-Year probability based on surviving years and Survival Gains After Surgery according to AJCC 8th. Actual survival, Conditional 5-Year and Survival Gains After Surgery according to AJCC 8th Years already survived Cohort 0 1 2 3 4 5 6 8 10 T1aN0 Conditional 5-y survival probability, % a 73 74 74 a 75 76 76 76 75 76 number at risk, n b 4499 3800 3205 2723 2271 1896 1615 1115 687 survival gain, % c - +1 0 +1 +1 0 0 -1 +1 Actual survival rate, % d 73 d 69 65 62 59 55 d 52 47 42 T1bN0 Conditional 5-y survival probability, % a 69 68 68 69 69 69 70 69 68 number at risk, n b 21138 18108 15364 12873 10756 8906 7358 4911 2975 survival gain, % c - -1 0 +1 0 0 +1 -1 -1 Actual survival rate, % d 69 64 59 55 51 48 44 38 33 T1cN0 Conditional 5-y survival probability, % a 61 61 62 63 65 65 66 66 64 number at risk, n b 17254 14548 12077 9974 8221 6771 5550 3555 2268 survival gain, % c - 0 +1 +1 +2 0 +1 0 -2 Actual survival rate, % d 61 55 51 46 43 40 36 31 25 T2aN0 Conditional 5-y survival probability, % a 54 57 59 61 62 63 62 63 62 number at risk, n b 9587 7820 6384 5137 4187 3436 2823 1844 1144 survival gain, % c - +3 +2 +2 +1 +1 -1 +1 -1 Actual survival rate, % d 54 49 45 41 37 34 31 26 21 T2bN0 Conditional 5-y survival probability, % a 50 55 59 61 63 62 61 63 66 number at risk, n b 5100 4034 3198 2606 2104 1746 1447 944 583 survival gain, % c - +5 +4 +2 +2 -1 -1 +2 +3 Actual survival rate, % d 50 45 42 38 35 31 28 24 21 T3N0 Conditional 5-y survival probability, % a 46 52 58 60 63 64 65 64 60 number at risk, n b 4790 3628 2784 2197 1802 1489 1223 810 525 survival gain, % c - +6 +6 +2 +3 +1 +1 -1 -4 Actual survival rate, % d 46 42 38 34 32 30 27 22 18 T4N0 Conditional 5-y survival probability, % a 39 47 56 61 65 67 68 68 67 number at risk, n b 4409 3135 2310 1795 1455 1186 989 691 470 survival gain, % c - +8 +9 +5 +4 +2 +1 0 -1 Actual survival rate, % d 39 35 33 30 28 26 24 21 16 T1-4N1 Conditional 5-y survival probability, % a 38 42 48 53 57 60 63 66 64 number at risk, n b 12021 9183 6728 5083 3893 3058 2405 1542 949 survival gain, % c - +4 +6 +5 +4 +3 +3 +3 +1 Actual survival rate, % d 38 33 30 27 25 23 21 18 15 T1-4N2 Conditional 5-y survival probability, % a 30 35 42 48 53 57 59 62 64 number at risk, n b 11517 8316 5690 4072 3051 2361 1853 1133 669 survival gain, % c - +5 +7 +6 +5 +4 +2 +3 +2 Actual survival rate, % d 30 27 23 21 19 17 16 13 11 Abbreviation: a The conditional 5-year survival probability for these already survived 2 years in T1aN0 cohort, which means that if patients had survived 2 years after diagnosis, the probability of still alive in the seventh year after diagnosis is 74% (Purple background). b At the beginning of the interval c Relative to the previous year; d For example, the 5-year overall survival rate in T1aN0 cohort is 73%, 10-year overall survival rate in T1aN0 cohort is 55% (Red background). Table 4: Conditional probability of survival for a few years after having survived for a certain years since diagnosed according to tumor prognostic factors. 1-, 3-, 5-, 8-year OS rates, (%) 3-year conditional survival probability, (%) a Variables 1-year OS 3-year OS 5-year OS 8-year OS 1 y after surgery 2 y after surgery 3 y after surgery 4 y after surgery 5 y after surgery All patients 83.5 63.6 50.8 38.8 67 71 73 75 77 Age 15-45 years 94.1 83.9 77.1 71.8 85 88 89 91 93 46-70 years 87.2 68.1 56.2 45.7 70 74 77 80 81 ≥70 years 78.1 56.3 41.8 27.4 61 64 66 67 65 Gender (%) Female 87.5 69.2 57.4 45.3 72 74 76 78 79 Male 79.5 56.5 44 32.3 62 67 70 72 73 Race (%) White 83.1 62.4 50.4 38.4 67 71 73 75 76 Black 83.7 62.3 49.7 38.1 66 70 73 75 77 other 88.6 69.7 56.7 44.5 71 72 73 76 79 8 th AJCC* pathological stage(%) Stage Ⅰ 91.4 75.9 63.8 50.1 76 76 77 78 78 Stage Ⅱ 81.8 55.9 42.2 30.7 59 64 67 71 73 Stage Ⅲ 75 44.9 32.6 23.6 50 58 64 70 72 Unknown 42.8 22.3 14.8 10 43 50 57 61 68 Pathological T stage (%) pT1 90.6 73.5 60.7 47.3 73 74 76 77 78 pT2 82.8 58.5 45.7 33.9 62 66 70 73 74 pT3 76.3 50.4 39.3 28.9 57 65 70 73 74 pT4 57.9 33.4 24.6 18.2 49 59 65 71 74 Tumour grade (%) grade Ⅰ 94.1 83.5 74 61.4 84 83 84 84 83 grade Ⅱ 88.3 67.1 52.9 39.1 67 69 71 73 74 grade Ⅲ 80.5 55.6 43.1 31.6 60 66 69 72 74 grade Ⅳ 74.7 49.9 39.6 29.5 59 68 73 74 74 Unknown Tumour size (%) ≤30 mm 90.6 73.5 60.7 47.3 73 74 76 77 78 31-50 mm 82.8 58.5 45.7 33.9 62 66 70 73 74 51-70mm 76.3 50.4 39.3 28.9 57 65 70 73 72 ≥ 71 mm 69.8 40.9 31.2 23.6 50 61 68 74 76 Unknown 47.7 26.6 18.7 13.7 Histological subtype (%) Adenocarcinoma 89.7 71.3 58.6 46.3 72 73 76 78 79 Squamous cell carcinoma 79.9 55.8 43.3 30.2 61 66 69 69 70 Adenosquamous carcinoma 80.3 52.8 40.5 29.3 45 52 68 72 72 Large cell carcinoma 75.8 50.7 39.7 29.4 59 67 72 74 74 Other Primary tumor site Upper lobe 85.9 65.1 52.6 40.1 68 71 73 75 76 Middle lobe 89.8 72 59.5 48.3 73 75 77 80 81 Lower lobe 85.3 64.3 51.8 39.2 67 71 73 75 76 Overlapping 53.7 34.6 26.8 21 56 64 71 76 78 Type of surgery local distribution or excision 66.4 36.5 19.9 11.5 41 41 47 53 58 Sublobar resection 85.1 62.6 48.2 34.3 64 66 68 70 71 Lobectomy 88.2 68.7 56.4 43.8 70 73 75 77 78 Resection of whole lung 76.4 51.5 40.6 31.1 59 66 71 75 77 No surgery 29.2 10.1 5.4 3.7 26 34 44 53 68 Number of positive lymph node 0 89.7 73.3 61.8 48.7 75 76 78 78 79 1-15 79.4 49.1 34.8 24.5 51 57 62 67 70 ≥ 16 66.5 43.2 31.5 22.2 55 60 64 68 71 Radiation Yes 76.9 43.6 30.2 20.7 46 54 60 65 69 No 84.6 66.2 54.2 41.9 71 73 75 76 77 Chemotherapy Yes 84.6 55.8 42.1 31.6 56 62 68 72 74 No 83.2 65.1 53.4 41.4 71 73 75 76 77 Seer stage local 90.5 75.2 63.5 50.1 76 77 78 79 79 regional 80.6 54.2 40.9 29.9 58 63 68 71 73 Unknown 37 18.8 12.2 8.2 42 49 56 62 67 Abbreviation: a For example, in the cohort of aged 15-45 years old, the 4-year survival rate for those who had survived 1 years (CS(4ǀ1)) after diagnosis is 85%, the 8-year survival rate for those who had survived 5 years (CS(8ǀ5)) after diagnosis is 93%. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-138915","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":10084527,"identity":"31acc7d1-3c05-45c4-8514-9ad06372d68d","order_by":0,"name":"Shixu Fang","email":"","orcid":"","institution":"The Affiliated Hospital of Zunyi Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Shixu","middleName":"","lastName":"Fang","suffix":""},{"id":10084529,"identity":"433c916c-cb30-4292-8693-995cad8d0554","order_by":1,"name":"Kui Zhai","email":"","orcid":"","institution":"The Affiliated Hospital of Zunyi Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Kui","middleName":"","lastName":"Zhai","suffix":""},{"id":10084531,"identity":"af7124d0-3a5b-4b08-b6e4-99ae036afba8","order_by":2,"name":"Xixian Ke","email":"","orcid":"","institution":"The Affiliated Hospital of Zunyi Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xixian","middleName":"","lastName":"Ke","suffix":""},{"id":10084533,"identity":"a816be76-6d74-4d48-b0f2-28bff3ee46fa","order_by":3,"name":"Hao Han","email":"","orcid":"","institution":"The Affiliated Hospital of Zunyi Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Hao","middleName":"","lastName":"Han","suffix":""},{"id":10084534,"identity":"46ece537-67c4-420e-ad3f-00131b8c58ee","order_by":4,"name":"Hongling Lu","email":"","orcid":"","institution":"Zunyi medical university","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Hongling","middleName":"","lastName":"Lu","suffix":""},{"id":10084538,"identity":"85150990-ce59-47e6-9146-fdbff11f6d5b","order_by":5,"name":"Gang Xu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxElEQVRIiWNgGAWjYFAC5jaGBz9q7PiZmQ8/IFILYxtDYs+xZMl2tjQD4rUksDEzbjjPoyBBlAaD8wvbHiTwsDEbH+ZhMGCosYkmqEVyxsN2gwQLGT6zw7wHHjAcS8ttIKSFX+JgmwTIFrPDfAkGjA2HCWthA2sB+mVzM4+BBFFa+PkbIVo2MBOrRXIGY5sEKJAlDgMDOYEYvxicP3xM4gMoKvsPH37wocaGsBYGiQQkTgIORaiA/wBRykbBKBgFo2AkAwD5FT0Hn0+sYgAAAABJRU5ErkJggg==","orcid":"","institution":"The Affiliated Hospital of Zunyi Medical University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Gang","middleName":"","lastName":"Xu","suffix":""}],"badges":[],"createdAt":"2020-12-31 14:47:01","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-138915/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-138915/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":5622814,"identity":"787391a8-f177-457d-bf04-bddfad1c693e","added_by":"auto","created_at":"2021-02-04 15:14:46","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":88744,"visible":true,"origin":"","legend":"Flow chart of data inclusion and exclusion.","description":"","filename":"OnlineFigure1.png","url":"https://assets-eu.researchsquare.com/files/rs-138915/v1/06abce2dccc351e18d012345.png"},{"id":5622602,"identity":"1fdd72c8-7e54-4918-a551-138f4b131560","added_by":"auto","created_at":"2021-02-04 15:11:46","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":102618,"visible":true,"origin":"","legend":"The overall survival and conditional survival of 99531 patients.\nNote: The overall survival rate (A), Time-dependent mortality of lung cancer (B), Kaplan-Meier graphs for overall survival according to duration of survivorship (C), 3- , 5-year actuarial survival and conditional survival probability based on 0-5 years survival after surgical perform (D). ","description":"","filename":"OnlineFigure2.png","url":"https://assets-eu.researchsquare.com/files/rs-138915/v1/02bc600d0c5eff4e7e36c081.png"},{"id":5622815,"identity":"c9cc1260-085c-4ebd-847d-5641f53bec59","added_by":"auto","created_at":"2021-02-04 15:14:46","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":807118,"visible":true,"origin":"","legend":"Kaplan-Meier method was used to estimate the survival rate in different cohort.\nNote: (T1aN0, T1bN0, T1cN0, T2aN0, T2bN0, T3N0, T4N0, T1-4N1, T1-4N2) given the survival of 0-10 years after resection of NSCLC.","description":"","filename":"OnlineFigure3.png","url":"https://assets-eu.researchsquare.com/files/rs-138915/v1/32344cc5d085b39c62abda6f.png"},{"id":5622816,"identity":"97a0f5dd-b2f3-4fee-ae30-fbf7e73c13c1","added_by":"auto","created_at":"2021-02-04 15:14:46","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":151174,"visible":true,"origin":"","legend":"The overall survival and conditional survival based on different variables.\nNote: The overall survival of histological types (A), tumor size (C), surgical intervention (E) and age (G). 3-year conditional probability of histological types (B), tumor size (D), surgical intervention (F) and age (H).","description":"","filename":"OnlineFigure4.png","url":"https://assets-eu.researchsquare.com/files/rs-138915/v1/969f46be1cf6c5438ed3fba7.png"},{"id":5622605,"identity":"b81e315f-3b95-4e56-9ee8-5cdf7aa92494","added_by":"auto","created_at":"2021-02-04 15:11:46","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":124358,"visible":true,"origin":"","legend":"The overall survival and conditional survival based on different histological types.\nNote: gender (A), chemotherapy (C), radiotherapy (E) and lymph node involvement (G). And 3-year conditional probability in accordance with different survival years after resection based on different stratification by gender (B), chemotherapy (D), radiotherapy (F) and lymph node involvement (H).","description":"","filename":"OnlineFigure5.png","url":"https://assets-eu.researchsquare.com/files/rs-138915/v1/2263d1ecb9d4a0244c7f8a96.png"},{"id":5622606,"identity":"d7273769-dc56-40cf-ac28-032cb361255b","added_by":"auto","created_at":"2021-02-04 15:11:46","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":72551,"visible":true,"origin":"","legend":"The overall survival and 3-year conditional probability in accordance with different histological types.\nNote: SEER stage (A-B), Lobectomy site (C-D) ","description":"","filename":"OnlineFigure6.png","url":"https://assets-eu.researchsquare.com/files/rs-138915/v1/5cd225716c86a07cd0263829.png"},{"id":13655432,"identity":"47272b8a-3604-4d13-aef6-b782983e9b1f","added_by":"auto","created_at":"2021-09-17 10:02:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2787796,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-138915/v1/d5efc22d-8ddb-4484-9107-015741d63d8b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eConditional Survival Probability of Non-Small Cell Lung Cancers, Based on The SEER Database\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":" \u003cp\u003eSurvival estimates for cancer patients was traditionally based on TNM stage at the time of diagnosis or after diagnosis or treatment [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], which answered prognostic questions that many cancer patients care about. This result makes the 5-year survival rate of cancer patients a fixed value, and could be understood as \"static survival estimate\" [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. However, for those who have survived for several years after diagnosis, the survival probability established at the time of diagnosis may not be applicable, because the overall survival rate of patients includes those who died within the first few years, as well as those who have passed through the first few years and \"stand out\" from them. For those patients pass through the first few years, the doubt troubling them may be \"If I have already lived \u003cem\u003ex\u003c/em\u003e years after diagnosis, what is the probability that I survive for another \u003cem\u003ey\u003c/em\u003e years\".\u003c/p\u003e \u003cp\u003eIn the past few years, the occurrence of conditional survival (CS) probability has given this question an exact answer [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], the CS refers to the probability of surviving for another \u003cem\u003en\u003c/em\u003e years if the patient with chronic disease has been alive for \u003cem\u003em\u003c/em\u003e years after diagnosis or treatment, the concept was derived from the conditional probability in biostatistics [\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. It can provide a dynamic and more precise survival rate for cancer patients [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. It is well known that the prognosis of cancer patients who survived in the first few years will be better, because the impact of death risk factors on the prognosis of patients will gradually weaken over time [\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], and as we all known, for those patients who have pass through the first few years after radiotherapy or chemotherapy, the adverse effects of radiotherapy and chemotherapy on the body gradually weaken. Conditional survival means that, on average, the prognosis of long-term cancer survivors are better than these newly diagnosed patients [\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. This study aims to explore the postoperative conditional survival of patients with non-distant metastatic non-small cell lung cancer, providing more powerful information for doctors to formulate treatment plans and monitoring plans, giving patients and doctors a new understanding of cancer prognosis.\u003c/p\u003e "},{"header":"2. Patients And Methods","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003e2.1. Data Source\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe patients of this study was selected from the National Cancer Institute database (The Surveillance, Epidemiology, and End Results, SEER) [14]. The raw data in this investigation was downloaded from the SEER web site (https://seer.cancer.gov/data/) via SEER*Stat in client-server mode after we submitted a request for access and signed the SEER research data agreement.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e2.2. Study Population\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this study, non-metastatic NSCLC from 18 registration centers in the SEER database were obtained. Since the SEER database is a public database, analysis of lung cancer patients does not require informed consent and institutional review. The clinical pathological characteristics of the patients were screened, the inclusion criteria are: 1) 15 years old or older patients diagnosed with lung cancer between 2000 and 2016 years; 2) with definite pathological diagnosis of NSCLC; 3) Single primary tumor; 4) Complete follow-up data (patients who died within 1 month after diagnosis were excluded, lack of specific follow-up time was also excluded); 5) Complete clinical pathological characteristics (such as age, tumor size, whether surgery, TNM stage). Exclusion criteria include: 1) metastatic lung cancer; 2) lack of T and N stages; 3) Tumor size is not available, histological and grade information is unclear; 4) diagnosis based on autopsy or death certificate only; 5) Died within one month of diagnosis or lack of follow-up data. The patient\u0026rsquo;s TNM staging was reclassified based on the eighth edition of the American Joint Committee on Cancer (AJCC) staging standard according to the tumor size. Detail in \u003cstrong\u003eFigure 1\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e2.3. Statistical Analyses\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe analysis of this study is based on two steps. First, TNM stage was reclassified based on tumor diameter according to the 8\u003csup\u003eth \u003c/sup\u003eversion of the American Joint Committee on Cancer (AJCC) staging (T1aN0, T1bN0, T1cN0, T2aN0, T2bN0, T3N0, T4N0, T1-4N1, and T1-4N2). Clinicopathological characteristics were also stratified, such as surgical situations, positive lymph nodes, tumor grade, tumor size and patient age. (Details in \u003cstrong\u003eTable 1\u003c/strong\u003e). Subsequently, Kaplan-Meier method was used to analyze actuarial survival rate of cancers, such as 5-year survival rate or 10-year survival rate. Most of the missing values in this article were eliminated.\u003c/p\u003e\n\u003cp\u003eAnother statistical method involved in this study is the conditional survival probability. To illustrate how we obtain conditional survival estimates from the cumulative survival estimates, suppose we are interested in the population\u0026rsquo;s 5-year lung cancer survival probability conditioned on already having survived 5 years. The estimate is obtained by dividing the cumulative survival at 10 years by the cumulative survival at 5 years. The 1-year lung-cancer survival estimates conditioned on already having survived 5 years after diagnosis are derived by dividing the\u003c/p\u003e\n\u003cp\u003ecumulative survival estimates at 6 years by the cumulative survival estimates at 5 years. Subtracting this survival probability from 1 gives the probability of dying in the year conditioned on having already survived 5 years. CS was adopted to estimate the survival probability, the mathematical definition of CS could be expressed as: CS (\u003cem\u003en\u003c/em\u003e | \u003cem\u003em\u003c/em\u003e) = S (\u003cem\u003en\u003c/em\u003e) / S (\u003cem\u003em\u003c/em\u003e), (\u003cem\u003em\u003c/em\u003e \u0026lt;\u003cem\u003en\u003c/em\u003e), where CS (\u003cem\u003en\u003c/em\u003e | \u003cem\u003em\u003c/em\u003e) is the probability of survival \u003cem\u003en\u003c/em\u003e years assuming that patient have already survived for \u003cem\u003em\u003c/em\u003e years after diagnosis. In this study, we estimated the additional 5-year conditional survival probability of patients given that they have already survived \u003cem\u003ex\u003c/em\u003e years using the mathematical formula：CS(\u003cem\u003ex\u003c/em\u003e+5ǀ\u003cem\u003ex\u003c/em\u003e) = OS(\u003cem\u003ex\u003c/em\u003e+5)/OS(\u003cem\u003ex\u003c/em\u003e). Finally, the differences between the actuarial OS and the CS of the population were compared and analyzed. All statistical methods were implemented by Graphpad prism version 8.0.2 and R language 3.6.3 version, all statistical tests are two-sided, P value \u0026lt;0.05 is considered statistically significant.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003e\u003cstrong\u003eOverall Population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFrom 2000 to 2016 years, 95,531 postoperative patients with non-metastatic NSCLC were included (For ease of comparison, 4346 non-surgical patients were also included in this study). The average age of the patients was 62 years old. Almost half of the patients were male (46863, 49%). Stages distribution (re-staged according to the tumor size) were as follows: 4499 cases (9.42%) with pT1aN0, 21138 cases (22.13%) with pT1bN0, 17254 cases (18.06%) pT1cN0, 9587 cases (10%) with pT2aN0, 5100 cases (5.33%) with pT2bN0, 4790 cases (5.01%) with pT3N0, 4409 cases (4.61%) with pT4N0, 12021 cases (12.58%) with pT1-4N1, 11517 cases (12.05%) with pT1-4N2. The average of tumor size is 3.32cm, Grade I-IV and unknown were accounts for 13.5%, 36%, 33%, 2.5% and 15% respectively, the primary tumor site was divided into the upper lobe, middle lobe, lower lobe and other locations, positive regional lymph nodes accounted for 36058 (37.8%). The surgical intervention situations were divided into non-operation, local ablation or cauterization, sublobar resection, lobectomy, pneumonectomy and other surgical methods. 22,530 patients (23.5%) received chemotherapy and 12,631 patients (13.1%) received radiotherapy (\u003cstrong\u003eTable 1\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eAt the last follow-up, the median follow-up time was 62 months, the number of deaths or events was 51,175. 1-year, 3-year and 5-year OS were 83.6% (95%CI: 83%-84%), 62.9% (95%CI: 62.6%-63.1%) and 50.8% (95%CI: 50.6%-51.0%) respectively. \u003cstrong\u003eFigure 2(A)\u003c/strong\u003e shows the rapid decline of overall survival rate in the first three years. Although the overall survival of lung cancers shows unsatisfactory, for those living several years after diagnosis, the mortality rate is gradually decreasing \u003cstrong\u003eFigure 2(B)\u003c/strong\u003e and the probability rates for surviving an additional 5 years were steadily increased (\u003cstrong\u003eFigure 2(C-D) and Table 2\u003c/strong\u003e). \u003cstrong\u003eFigure 3\u003c/strong\u003e shows the decrease of the actuarial survival rates over time and the increases of estimated CS(8) for 1-5 years in total patients, which demonstrated that as the survival time of cancers increases, the gap between overall survival rate and conditional survival rate becomes more significant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e8\u003csup\u003eth \u003c/sup\u003eT and N stage\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEnrolled population were reclassified into 9 groups including T1aN0, T1bN0, T1cN0, T2aN0, T2bN0, T3N0, T4N0, T1-4N1, T1-4N2 according to 8\u003csup\u003eth\u003c/sup\u003eTNM staging. The actuarial survival probability and conditional survival probability of these 9 groups were also explored. According to the results exhibited in \u003cstrong\u003eTable 3\u003c/strong\u003e, the worse the TNM stage, the lower the overall survival rate of cancers, for example, 5-year OS in T1aN0 cohort is 73% (95%CI: 72%-74%), T2aN0 cohort is 54% (95%CI: 53%-55%), T3N0 cohort is 46% (95%CI: 44%-47%), T4N0 cohort is 39% (95%CI: 37%-40.5%). Analysis based on conditional survival probability indicating that the worse the prognosis of those who survived the first few years of diagnosis, the more significant the improvement of the survival probability, and for patients with a relatively well initial prognosis, the corresponding increase in conditional survival probability is not obvious. For example, in the T4N0 cohort, the 8-year OS rate is 30% (95%CI: 27%-32%), corresponding, for these who have survived for 5 years, the probability surviving another 3 years (according to the mathematical formula, it could be described as CS (8ǀ5)) is 78%. The actuarial 8-year OS of T3N0 cohort is 34% (95%CI: 31%-36%), corresponding, the CS (8ǀ5) was 74% (95%CI: 72%-75%). The actuarial 8-year OS of T1aN0 patients is 62% (95%CI: 60%-64%), corresponding, the CS (8ǀ5) was 85 % (95%CI: 83%-86%) (Difference is 23%; P \u0026lt;0.001) (\u003cstrong\u003eFigure 4A\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePathological types\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOther tumor prognostic factors were also explored in this study. Analysis based on pathological types showed that the prognosis of patients with adenocarcinoma is better than other types including squamous cell carcinoma, adenosquamous cell carcinoma and large cell carcinoma (\u003cstrong\u003eFigure 4(A)\u003c/strong\u003e). For those surviving in the first few years after diagnosis, the worse the prognosis of pathological types (such as squamous cell carcinoma (SCC), adenosquamous cell carcinoma (ACC), and large cell carcinoma (LCC)), the more significance the conditional survival probability benefit, for example, in the adenocarcinoma cohort (n 55,592), the 8-year OS is 46.3% (95%CI: 45%-47%), but the 8-year survival rate for those who had survived 5 years after diagnosis is 79% (95%CI: 78%-80%), the difference is 22.7%. Simultaneously, in the SCC cohort (n 24,062), the probabilities of CS(8) increased from 30.2% (95%CI: 29%-33%) at baseline to 70% (95%CI: 67%-74%) at 5 years of follow-up, the probabilities of CS(8) in the ACC cohort (n 2,188) increased from 29.3% (95%CI: 27%-31%) at baseline to 72% (95%CI: 67%-76%) at 5 years of follow-up, and in the LCC cohort (n 3,712) increased from 29.4% at baseline to 74% at 5 years of follow-up (\u003cstrong\u003eFigure 4(B) and Table 4\u003c/strong\u003e). It indicated that the longer cancer patient survives, the more improvement of survival prognosis they would get, and the less significant the influence of pathology type on cancer prognosis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTumor size\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCompared with the patients with tumor size less than 3cm (5-year OS is 60.7% (95%CI: 59%-62%)), the bigger tumor size shows a unsatisfactory 5-year OS (the 5-year OS of 3.1-5.0cm cohort, 5.1-7.0cm cohort and more than 7.0cm cohort were 45.7% (95%CI: 45%-46%), 39.3% (95%CI: 38%-40%) and 31.2% (95%CI: 30%-32%) respectively) (\u003cstrong\u003eFigure 4(C)\u003c/strong\u003e), the 8-year survival probability given that the patient has lived for the first 5 years after diagnosis in the less than 3cm cohort, 3.1-5.0cm cohort, 5.1-7.0cm cohort and more than 7.0cm cohort were 78% (95%CI: 77%-79%), 74% (95%CI: 73%-74%), 74% (95%CI: 72%-76%) and 76% (95%CI: 73%-78%) respectively, which did not show a significant difference, indicating that, after a period of survival, patients with poor initial prognosis could obtain greater survival benefits when compared with those better initial prognoses (\u003cstrong\u003eFigure 4(D)\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSurgical intervention\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this study, the approaches of surgical interventions included no surgery perform, local ablation or electrocautery, sublobar resection, lobectomy and others, the corresponding 5-year OS were 5.4% (95%CI: 5%-6%), 19.9% (95%CI: 17%-23%), 48.2% (95%CI: 47%-49%), 56.4% (95%CI: 54%-58%) and 40.6% (95%CI: 37%-44%) respectively (\u003cstrong\u003eFigure 4(E)\u003c/strong\u003e), we also analyzed the 5-year survival probability of those who already lived for the first 2 years after diagnosis (CS (5ǀ2)), the CS (5ǀ2) of the above 5 interventions were 34% (95%CI: 30%-38%), 41% (95%CI: 35%-47%), 66% (95%CI: 65%-68%), 73% (95%CI: 72%-73%) and 66% (95%CI: 65%-68%) respectively ((\u003cstrong\u003eFigure 4(F)\u003c/strong\u003e) \u003cstrong\u003eand Table 4\u003c/strong\u003e), which demonstrated that the cancer prognosis increased rapidly for those who survived the first few years, this result greatly encourages cancer survivor.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatient age\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs shown in\u003cstrong\u003e Figure 4(G)\u003c/strong\u003e, the 5-year OS of patients in different age groups are significantly different, specifically, the 5-year OS of those ages range from 15-45, 45-70 and over 70 years old were 77.1%, 56.1 % and 41.8% respectively. For these had survived 5 years after surgery, The probability for living another 3 years (CS (8ǀ5)) were 93%(+15.9%) in patients aged 15-45 years, 81% (+24.9%) in patients aged 45-70 years and 65% (+23.2%) in patients aged \u0026ge;71 years \u003cstrong\u003eFigure 4(H)\u003c/strong\u003e, suggesting that the significant survival benefit would be got for those survived the first few years.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOther pathological features\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eActuarial survival probability and condition survival probability of other pathological features were also analyzed including gender \u003cstrong\u003eFigure 5(A-B)\u003c/strong\u003e, chemotherapy\u003cstrong\u003e Figure 5(C-D)\u003c/strong\u003e, radiotherapy \u003cstrong\u003eFigure 5(E-F)\u003c/strong\u003e, positive lymph nodes \u003cstrong\u003eFigure 5(G-H)\u003c/strong\u003e, SEER stage \u003cstrong\u003eFigure 6(A-B)\u003c/strong\u003e, primary tumor site \u003cstrong\u003eFigure 6(C-D)\u003c/strong\u003e. The results showed that the chemotherapy cohort and the radiotherapy cohort, lymph node positives (more than 16), the SEER stage was regional, Caucasian, primary tumor site lie in whole lung or bronchus were associated with lower 5-year actuarial survival (\u003cstrong\u003eTable 4\u003c/strong\u003e). At the same time, time-dependent conditional survival probability was also explored, for example, patients in the female group had an actuarial 5-year OS of 57.4%, while the 5-year survival probability of these who had survived for 2 years (CS (5ǀ2)) is 74%. The 5-year OS in the male cohort is 44%, and the CS (5ǀ2) is 67% (\u003cstrong\u003eFigure 5(B)\u003c/strong\u003e). Simultaneously, the 5-year OS in the chemotherapy cohort is 42.1%, and the CS (5ǀ2) is 62%, corresponding difference in the non-chemotherapy cohort is 19.6% (\u003cstrong\u003eFigure 5(D)\u003c/strong\u003e), patients in the radiotherapy cohort had an actuarial 5-year OS of 30.2% and a CS (5ǀ2) of 54%, The detailed overall survival rates and conditional survival probability of other tumor prognostic factors were showed in \u003cstrong\u003eTable 4\u003c/strong\u003e.\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe view that the risk of tumor-specific death decreases with the length of postoperative survival is called conditional survival. Conditional survival (CS) means that, on average, long-term cancer survivors have a better prognosis than newly diagnosed individuals [15-17], because most of the patients who survived after the first few years were those respond well to treatment, and the condition was alleviated, the complications were controlled, adverse reactions caused by surgery, radiotherapy and chemotherapy gradually weakened and the threat of death-related risks is gradually reduced [4].\u003c/p\u003e\n\u003cp\u003eThe 5-year overall survival rate of the enrolled patients is 51%, For these who have survived 1-, 2-, 3-, 4- or 5 years after the diagnosis of cancer, the probability to survive another 3 years is 67%, 71%, 73%, 75% and 77% respectively, demonstrated that the survival probability increasing gradually as patients survive longer.\u003c/p\u003e\n\u003cp\u003eThe results showed that the 5-year OS of patients with T1aN0 to T1-4N2 gradually decreases, range from 55% of T1aN0 to 17% of T1-4N2, which brought frustrating results to those patients initially diagnosed with advanced disease. However, it is gratifying to observe the significant improvement in CS as patients survive longer, especially for those with advanced disease. For example, the difference between 5-year actuarial OS and CS (5ǀ3) in T1aN0 cohort is 15%, T2aN0 is 27%, T3N0 is 35%, and T4N0 is 39% (\u003cstrong\u003eFigure. 4D\u003c/strong\u003e). We can also note that, for these long-term cancer survivors, the difference in conditional survival probability of people with different T and N stages gradually narrowed, tending to be consistent. In other words, for these had survived 5 years after diagnosed, the probability of patients still alive in the tenth year in T1aN0, T2aN0, T3N0, T4N0, T1-4N1 are 76%, 63%, 64%, 67% and 60% respectively, which revealed that the survival prognosis of patients is not only related to clinical pathological factors, but also to the survival time of patients after surgery, and as the survival time is prolonged, the prognosis of patients increasingly shows time dependence.\u003c/p\u003e\n\u003cp\u003eThe results of the age-based grouping show that the survival prognosis of patients in different age groups varies greatly, the 5-year OS of the elderly patients is the unsatisfactory (32.4%), and the young patients is the best (46.5%). In the 15-45 cohorts, the 3-year conditional survival probabilities increased from 83% at baseline to 93% at 60 months, in these aged more than 70 years old, the CS3 increased from 56% at baseline to 65% at 60 month. Compared with young patients and middle-aged patients, the improvement of conditional probability in elderly patients is not significant, which may be due to the long smoking time of elderly patients, the high incidence of cardiovascular diseases and respiratory diseases or the poor physical performance of elderly patients caused by.\u003c/p\u003e\n\u003cp\u003eOther tumor characteristics, including poor histological grade, larger tumor size, adenosquamous carcinoma, lymph node involvement, male, Caucasians, tumor located in the middle lobe and seed stage were associated with poor survival prognosis (\u003cstrong\u003eFigure 6\u003c/strong\u003e). However, from the perspective of long-term survival of patients, it may be more meaningful to explore the conditional survival probability and compare the actuarial OS and CS. Although unfavorable clinicopathological features show poor 5-year OS, the benefit of conditional survival becomes very significance with the survival time of patient increases. For example, in the cohort of more than 16 lymph node metastasis, compared with the 5-year OS of all patients, those survived the first three years after diagnosis (CS (5ǀ3)) shows a better 5-year survival rate, increased by 16% (55%-71%), while patients without lymph node metastasis increased by only 4% (75%-79%). Similarly, Patients with larger tumor diameters increased CS (8ǀ5) by 26% and patients with smaller tumor diameters increased by only 5% (\u003cstrong\u003eFigure 3\u003c/strong\u003e). Those patients with adverse clinical factors did not pass the most critical period and died within the first few years, as the years of survival of specific patients increase, these adverse prognostic factors that affect the prognosis become increasingly unrelated. Therefore, our data suggests that CS may be a more valuable tool late in the postoperative period to estimate the prognosis of patients who are predicted to die based on initial actuarial estimates.\u003c/p\u003e\n\u003cp\u003eSome limitations of this study should not be overlooked. First, this study is a retrospective study. Inevitable deviations would be appear in the collection of clinical pathological characteristics, diagnosis and treatment of patients; second, the diagnosis of patients in this study the time span is large (2000-2016). The impact between lung cancer patients diagnosed in different periods and the prognosis has not been explored. Third, multiple primary tumors were excluded in order to eliminate interference, but the errors were unavoidable in reclassified the T stage and N stage. Nonetheless, this study also proposes a dynamic assessment of the conditional survival probability of lung cancer patients, thereby allowing adjustment of the predicted survival time after lung resection. The tool may prove useful to patients, doctors and researchers, and will guide dynamic and personalized clinical management decisions.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe worse the initial diagnosis of cancer patient, the more significant the benefit of time-dependent conditional survival probability, long-lived cancer patients may have a better cancer prognosis.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eNSCLC: non-small cell lung cancer\u003c/p\u003e\n\u003cp\u003eSEER: \u0026nbsp;Surveillance,\u0026nbsp;Epidemiology,\u0026nbsp;and\u0026nbsp;End\u0026nbsp;Results\u003c/p\u003e\n\u003cp\u003eCS: condition survival probability\u003c/p\u003e\n\u003cp\u003eOS: overall survival\u003c/p\u003e\n\u003cp\u003eAJCC: American Joint Committee on Cancer\u003c/p\u003e\n\u003cp\u003eSCC:squamous cell carcinoma\u003c/p\u003e\n\u003cp\u003eACC: adenosquamous cell carcinoma\u003c/p\u003e\n\u003cp\u003eLCC:and large cell carcinoma\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis manuscript does not involve animal and the SEER database is a public database, analysis of lung cancer patients does not require informed consent and institutional review. So it has not yet applied\u0026nbsp;the Ethics approval and consent to participate.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets supporting the conclusions of this article were included within the article\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFounding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by the National\u0026nbsp;Natural\u0026nbsp;Science\u0026nbsp;Foundation\u0026nbsp;of\u0026nbsp;China (grant number 81960532).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eProject design: Gang Xu and Hongling Lu;\u003c/p\u003e\n\u003cp\u003eSearched databases and performed literature screen: Shixu Fang and Xixian Ke;\u003c/p\u003e\n\u003cp\u003eData extraction and analysis: Kui Zhai and Hao Han;\u003c/p\u003e\n\u003cp\u003eEvaluated the quality of included literature: Shixu Fang;\u003c/p\u003e\n\u003cp\u003eManuscript writing: Gang Xu, Shixu Fang, XixianKe and Hongling Lu.\u003c/p\u003e\n\u003cp\u003eFinal draft was approved by all the authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' information\u003c/strong\u003e\u003cstrong\u003es\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003eDepartment of Thoracic Surgery, The Affiliated Hospital of Zunyi medical university, 149 Dalian road, Zunyi, Guizhou, 563000, China\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u003c/sup\u003eDepartment of biochemistry, Zunyi medical university, No.6 xuefu west road, xinpu new area, Zunyi, Guizhou, 563099, China\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eFeinstein AR, Sosin DM, Wells CK: \u003cstrong\u003eThe Will Rogers phenomenon. Stage migration and new diagnostic techniques as a source of misleading statistics for survival in cancer\u003c/strong\u003e. \u003cem\u003eThe New England journal of medicine \u003c/em\u003e1985, \u003cstrong\u003e312\u003c/strong\u003e(25):1604-1608.\u003c/li\u003e\n\u003cli\u003eFL G: \u003cstrong\u003eTNM: our language of cancer\u003c/strong\u003e. \u003cem\u003eCA: a cancer journal for clinicians \u003c/em\u003e2004, \u003cstrong\u003e54\u003c/strong\u003e(3):129-130.\u003c/li\u003e\n\u003cli\u003eSkuladottir H, Olsen JH: \u003cstrong\u003eConditional survival of patients with the four major histologic subgroups of lung cancer in Denmark\u003c/strong\u003e. \u003cem\u003eJournal of clinical oncology : official journal of the American Society of Clinical Oncology \u003c/em\u003e2003, \u003cstrong\u003e21\u003c/strong\u003e(16):3035-3040.\u003c/li\u003e\n\u003cli\u003eZabor EC, Gonen M, Chapman PB, Panageas KS: \u003cstrong\u003eDynamic prognostication using conditional survival estimates\u003c/strong\u003e. \u003cem\u003eCancer \u003c/em\u003e2013, \u003cstrong\u003e119\u003c/strong\u003e(20):3589-3592.\u003c/li\u003e\n\u003cli\u003eHieke S, Kleber M, K\u0026ouml;nig C, Engelhardt M, Schumacher M: \u003cstrong\u003eConditional Survival: A Useful Concept to Provide Information on How Prognosis Evolves over Time\u003c/strong\u003e. \u003cem\u003eClinical cancer research : an official journal of the American Association for Cancer Research \u003c/em\u003e2015, \u003cstrong\u003e21\u003c/strong\u003e(7):1530-1536.\u003c/li\u003e\n\u003cli\u003eWang P, Sun Z, Wang W, Deng J, Wang Z: \u003cstrong\u003eConditional survival of patients with gastric cancer who undergo curative resection: A multi-institutional analysis in China\u003c/strong\u003e. 2018, \u003cstrong\u003e124\u003c/strong\u003e(5):916-924.\u003c/li\u003e\n\u003cli\u003evan Erning FN, van Steenbergen LN, Lemmens V, Rutten HJT, Martijn H, van Spronsen DJ, Janssen-Heijnen MLG: \u003cstrong\u003eConditional survival for long-term colorectal cancer survivors in the Netherlands: who do best?\u003c/strong\u003e \u003cem\u003eEuropean journal of cancer (Oxford, England : 1990) \u003c/em\u003e2014, \u003cstrong\u003e50\u003c/strong\u003e(10):1731-1739.\u003c/li\u003e\n\u003cli\u003eZhong Q, Chen QY, Li P, Xie JW, Wang JB, Lin JX, Lu J, Cao LL, Lin M, Tu RH\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003ePrediction of Conditional Probability of Survival After Surgery for Gastric Cancer: A Study Based on Eastern and Western Large Data Sets\u003c/strong\u003e. \u003cem\u003eSurgery \u003c/em\u003e2018, \u003cstrong\u003e163\u003c/strong\u003e(6):1307-1316.\u003c/li\u003e\n\u003cli\u003eIto Y, Miyashiro I, Ito H, Hosono S, Chihara D, Nakata-Yamada K, Nakayama M, Matsuzaka M, Hattori M, Sugiyama H\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eLong-term survival and conditional survival of cancer patients in Japan using population-based cancer registry data\u003c/strong\u003e. \u003cem\u003eCancer science \u003c/em\u003e2014, \u003cstrong\u003e105\u003c/strong\u003e(11):1480-1486.\u003c/li\u003e\n\u003cli\u003eThuret R, Sun M, Abdollah F, Schmitges J, Shariat SF, Iborra F, Guiter J, Patard JJ, Perrotte P, Karakiewicz PI: \u003cstrong\u003eConditional survival predictions after surgery for patients with penile carcinoma\u003c/strong\u003e. \u003cem\u003eCancer \u003c/em\u003e2011, \u003cstrong\u003e117\u003c/strong\u003e(16):3723-3730.\u003c/li\u003e\n\u003cli\u003eKurta ML, Edwards RP, Moysich KB, McDonough K, Bertolet M, Weissfeld JL, Catov JM, Modugno F, Bunker CH, Ness RB\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003ePrognosis and conditional disease-free survival among patients with ovarian cancer\u003c/strong\u003e. \u003cem\u003eJournal of clinical oncology : official journal of the American Society of Clinical Oncology \u003c/em\u003e2014, \u003cstrong\u003e32\u003c/strong\u003e(36):4102-4112.\u003c/li\u003e\n\u003cli\u003ePalumbo C, Mistretta FA, Knipper S, Pecoraro A, Tian Z, Shariat SF, Saad F, Simeone C, Briganti A, Antonelli A\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eConditional Survival of Patients With Nonmetastatic Renal Cell Carcinoma: How Cancer-Specific Mortality Changes After Nephrectomy\u003c/strong\u003e. \u003cem\u003eJournal of the National Comprehensive Cancer Network : JNCCN \u003c/em\u003e2020, \u003cstrong\u003e18\u003c/strong\u003e(1):44-51.\u003c/li\u003e\n\u003cli\u003eHuang JF, Chen D, Zheng XQ, Lin JL, Wang XY, Wu AM: \u003cstrong\u003eConditional survival and changing risk profile in patients with chordoma: a population-based longitudinal cohort study\u003c/strong\u003e. 2019, \u003cstrong\u003e14\u003c/strong\u003e(1):181.\u003c/li\u003e\n\u003cli\u003eCronin KA, Ries LA, Edwards BK: \u003cstrong\u003eThe Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute\u003c/strong\u003e. \u003cem\u003eCancer \u003c/em\u003e2014, \u003cstrong\u003e120 Suppl 23\u003c/strong\u003e:3755-3757.\u003c/li\u003e\n\u003cli\u003eLatenstein AEJ, van Roessel S, van der Geest LGM, Bonsing BA, Dejong CHC, Groot Koerkamp B, de Hingh I, Homs MYV, Klaase JM, Lemmens V\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eConditional Survival After Resection for Pancreatic Cancer: A Population-Based Study and Prediction Model\u003c/strong\u003e. \u003cem\u003eAnnals of surgical oncology \u003c/em\u003e2020.\u003c/li\u003e\n\u003cli\u003eChen QY, Zhong Q, Zhou JF, Qiu XT, Dang XY, Cai LS, Su GQ, Xu DB, Lin GT, Guo KQ\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eConditional survival and recurrence of remnant gastric cancer after surgical resection: A multi-institutional study\u003c/strong\u003e. \u003cem\u003eCancer science \u003c/em\u003e2020, \u003cstrong\u003e111\u003c/strong\u003e(2):502-512.\u003c/li\u003e\n\u003cli\u003eYan L, Chen F, Chen L, Lin J, Chen Q, Bao X, Qiu Y, Lin L, Zheng X, Pan L\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eDynamic evaluation of conditional survival in patients with oral squamous cell carcinoma after surgical resection: A large-scale prospective study\u003c/strong\u003e. \u003cem\u003eOral oncology \u003c/em\u003e2020, \u003cstrong\u003e104\u003c/strong\u003e:104639.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1:\u003c/strong\u003e Baseline characteristics of enrolled patients with NSCLC in the SEER database.\u003c/p\u003e\n\u003ctable border=\"1\" width=\"0\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003eVariables\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eTotal cohort , n (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003eNo. patients (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e95531\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003eMean (median) age, years\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e62(62)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003eAge\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; 15-45 years\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e3046 (3.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; 46-70 years\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e51191 (53.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; \u0026ge;70 years\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e40494 (43.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003eGender, n (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; Female\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e48668 (50.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; Male\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e46863 (49.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003eRace, n (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; White\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e81013 (84.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; Black\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e8127 (8.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; other\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e6391 (6.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e8\u003csup\u003eth\u003c/sup\u003e AJCC* pathological stage, n (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; Stage Ⅰ\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e52478 (54.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; Stage Ⅱ\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e18726 (19.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; Stage Ⅲ\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e19136 (20)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; Unknown\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e5191 (5.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003ePathological T stage, n (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; pT1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e53086 (55.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; pT2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e22645 (23.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; pT3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e8330 (8.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; pT4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e11470 (12.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003ePathological N stage, n (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp;pN0/pNx\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e71968 (75.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp;pN1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e12021 (12.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp;pN2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e11517 (12.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp;pN3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e25 (0.026)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003eTumour grade, n (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; grade Ⅰ\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e12681 (13.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; grade Ⅱ\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e34063 (35.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; grade Ⅲ\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e31540 (33)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; grade Ⅳ\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e2390 (2.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; Unknown\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e14857 (15.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003eTumour size, n (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp; \u0026le;30 mm\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e53086 (55.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; 31-50 mm\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e22645 (23.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; 51-70mm\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e8330 (8.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp; \u0026ge; 71 mm\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e4982 (5.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; Unknown\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e6268 (6.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003eHistological subtype, n (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; Adenocarcinoma\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e55592 (49.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; Squamous cell carcinoma\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e24062 (25.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; Adenosquamous carcinoma\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e2188 (2.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; Large cell carcinoma\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e3712 (3.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; Other\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e18676 (19.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003ePrimary tumor site\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; Upper lobe\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e53757 (56.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; Middle lobe\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e5213 (5.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; Lower lobe\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e29529 (30.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; Other\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e7032 (7.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003eType of surgery\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; local distribution or excision\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e722 (0.75)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; Sublobar resection\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e14615 (15.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; Lobectomy\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e65951 (59)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; Resection of whole lung\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e9897 (10.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; No surgery\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e4346 (4.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003eNumber of positive lymph node\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e59473 (62.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; 1-15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e19657 (20.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; \u0026ge; 16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e16401 (17.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003eRadiation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; Yes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e13133 (13.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; No\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e82398 (86.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003eChemotherapy\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; Yes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e22530 (23.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; No\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e73001 (76.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003eSeer stage\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; local\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e47912 (50.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; regional\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e43359 (45.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp; Unknown\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e4260 (4.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr /\u003e\u003cstrong\u003eTable 2:\u003c/strong\u003e Probability of patients with NSCLC resection can reach a certain survival time after a period of survival.\u003c/p\u003e\n\u003ctable border=\"1\" width=\"0\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"91\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"103\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"505\"\u003e\n\u003cp\u003eYears already survived\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"103\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"91\"\u003e\n\u003cp\u003eSurvival probability to reach X years\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"103\"\u003e\n\u003cp\u003e0 Year\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e1 Year\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e2 Year\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e3 Year\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e4 Year\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e5 Year\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e6 Year\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"103\"\u003e\n\u003cp\u003e7 Year\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e8 Year\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"91\"\u003e\n\u003cp\u003e1 Year\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"103\"\u003e\n\u003cp\u003e0.84 (0.83-0.84)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"103\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"91\"\u003e\n\u003cp\u003e2 Year\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"103\"\u003e\n\u003cp\u003e0.72 (0.72-0.72)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e0.86 (0.86-0.86)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"103\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"91\"\u003e\n\u003cp\u003e3 Year\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"103\"\u003e\n\u003cp\u003e0.63 (0.63-0.63)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e0.75 (0.75-0.76)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e0.88 (0.87-0.88)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"103\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"91\"\u003e\n\u003cp\u003e4 Year\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"103\"\u003e\n\u003cp\u003e0.56 (0.56-0.57)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e0.67 (0.67-0.68)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e0.78 (0.78-0.79)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e0.89 (0.89-0.90)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"103\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"91\"\u003e\n\u003cp\u003e5 Year\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"103\"\u003e\n\u003cp\u003e0.51 (0.51-0.51)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e0.61 (0.60-0.61)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e0.71 (0.70-0.71)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e0.81 (0.80-0.81)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e0.90 (0.90-0.91)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"103\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"91\"\u003e\n\u003cp\u003e6 Year\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"103\"\u003e\n\u003cp\u003e0.46 (0.46-0.47)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e0.55 (0.55-0.56)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e0.64 (0.64-0.65)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e0.73 (0.73-0.74)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e0.82 (0.82-0.83)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e0.91 (0.91-0.91)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"103\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"91\"\u003e\n\u003cp\u003e7 Year\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"103\"\u003e\n\u003cp\u003e0.42 (0.42-0.43)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e0.51 (0.50-0.51)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e0.59 (0.59-0.59)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e0.67 (0.67-0.68)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e0.75 (0.75-0.76)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e0.83 (0.83-0.84)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e0.92 (0.91-0.92)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"103\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"91\"\u003e\n\u003cp\u003e8 Year\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"103\"\u003e\n\u003cp\u003e0.39 (0.38-0.39)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e0.47 (0.46-0.47)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e0.54 (0.54-0.55)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e0.62 (0.61-0.62)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e0.69 (0.69-0.70)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e0.77 (0.76-0.77)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e0.84 (0.84-0.85)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"103\"\u003e\n\u003cp\u003e0.92 (0.91-0.92)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"91\"\u003e\n\u003cp\u003e9 Year\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"103\"\u003e\n\u003cp\u003e0.36 (0.35-0.36)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e0.43 (0.42-0.43)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e0.50 (0.49-0.50)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e0.57 (0.56-0.58)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e0.64 (0.63-0.64)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e0.71 (0.70-0.71)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e0.78 (0.77-0.78)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"103\"\u003e\n\u003cp\u003e0.85 (0.84-0.85)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e0.92 (0.92-0.93)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"91\"\u003e\n\u003cp\u003e10 Year\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"103\"\u003e\n\u003cp\u003e0.33 (0.33-0.34)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e0.40 (0.39-0.40)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e0.46 (0.46-0.47)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e0.53 (0.52-0.53)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e0.59 (0.58-0.60)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e0.65 (0.65-0.66)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e0.72 (0.71-0.72)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"103\"\u003e\n\u003cp\u003e0.78 (0.78-0.79)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e0.85 (0.85-0.86)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"91\"\u003e\n\u003cp\u003enumber at risk\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"103\"\u003e\n\u003cp\u003e\u003cem\u003e95531\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e\u003cem\u003e74924\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e\u003cem\u003e59279\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e\u003cem\u003e47592\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e\u003cem\u003e38626\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e\u003cem\u003e31546\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e\u003cem\u003e25838\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"103\"\u003e\n\u003cp\u003e\u003cem\u003e21029\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e\u003cem\u003e17207\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003eFor example, if patients had survived for 1 year, the probability to survived another 1 year is 86%. If patients had survived for 5 year after diagnosis, the survival probability of 10-year is 65%, and the 10-year survival probability for these initial diagnosis of cancer is 33%.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3:\u003c/strong\u003e Actual survival rates of 5-15 years, Conditional 5-Year probability based on surviving years and Survival Gains After Surgery according to AJCC 8th.\u003c/p\u003e\n\u003ctable border=\"1\" width=\"0\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"9\" width=\"585\"\u003e\n\u003cp\u003eActual survival, Conditional 5-Year and Survival Gains After Surgery according to AJCC 8th\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"9\" width=\"585\"\u003e\n\u003cp\u003eYears already survived\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003eCohort\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003eT1aN0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; Conditional 5-y survival probability, %\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e73\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e74\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e74\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e75\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e76\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e76\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e76\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e75\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e76\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; number at risk, n\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e4499\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e3800\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e3205\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e2723\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e2271\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e1896\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e1615\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e1115\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e687\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; survival gain, %\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e+1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e+1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e+1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e-1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e+1\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; Actual survival rate, %\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e73\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e69\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e65\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e62\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e59\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e55\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e52\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e47\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e42\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003eT1bN0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; Conditional 5-y survival probability, %\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e69\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e68\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e68\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e69\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e69\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e69\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e70\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e69\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e68\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; number at risk, n\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e21138\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e18108\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e15364\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e12873\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e10756\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e8906\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e7358\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e4911\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e2975\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; survival gain, %\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e-1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e+1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e+1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e-1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e-1\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; Actual survival rate, %\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e69\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e59\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e55\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e51\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e48\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e44\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e38\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e33\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003eT1cN0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; Conditional 5-y survival probability, %\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e61\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e61\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e62\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e63\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e65\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e65\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e66\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e66\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e64\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; number at risk, n\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e17254\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e14548\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e12077\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e9974\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e8221\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e6771\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e5550\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e3555\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e2268\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; survival gain, %\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e+1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e+1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e+2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e+1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e-2\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; Actual survival rate, %\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e61\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e55\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e51\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e46\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e43\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e40\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e36\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e31\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e25\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003eT2aN0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; Conditional 5-y survival probability, %\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e54\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e57\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e59\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e61\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e62\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e63\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e62\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e63\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e62\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; number at risk, n\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e9587\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e7820\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e6384\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e5137\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e4187\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e3436\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e2823\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e1844\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e1144\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; survival gain, %\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e+3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e+2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e+2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e+1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e+1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e-1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e+1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e-1\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; Actual survival rate, %\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e54\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e49\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e45\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e41\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e37\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e34\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e31\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e21\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003eT2bN0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; Conditional 5-y survival probability, %\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e55\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e59\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e61\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e63\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e62\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e61\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e63\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e66\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; number at risk, n\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e5100\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e4034\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e3198\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e2606\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e2104\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e1746\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e1447\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e944\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e583\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; survival gain, %\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e+5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e+4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e+2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e+2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e-1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e-1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e+2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e+3\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; Actual survival rate, %\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e45\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e42\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e38\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e35\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e31\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e28\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e21\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003eT3N0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; Conditional 5-y survival probability, %\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e46\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e52\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e58\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e60\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e63\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e65\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e60\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; number at risk, n\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e4790\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e3628\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e2784\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e2197\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e1802\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e1489\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e1223\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e810\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e525\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; survival gain, %\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e+6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e+6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e+2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e+3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e+1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e+1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e-1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e-4\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; Actual survival rate, %\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e46\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e42\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e38\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e34\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e32\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e18\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003eT4N0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; Conditional 5-y survival probability, %\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e39\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e47\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e56\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e61\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e65\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e67\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e68\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e68\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e67\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; number at risk, n\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e4409\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e3135\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e2310\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e1795\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e1455\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e1186\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e989\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e691\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e470\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; survival gain, %\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e+8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e+9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e+5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e+4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e+2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e+1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e-1\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; Actual survival rate, %\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e39\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e35\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e33\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e28\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e16\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003eT1-4N1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; Conditional 5-y survival probability, %\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e38\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e42\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e48\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e53\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e57\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e60\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e63\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e66\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e64\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; number at risk, n\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e12021\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e9183\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e6728\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e5083\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e3893\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e3058\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e2405\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e1542\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e949\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; survival gain, %\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e+4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e+6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e+5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e+4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e+3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e+3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e+3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e+1\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; Actual survival rate, %\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e38\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e33\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e18\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e15\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003eT1-4N2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; Conditional 5-y survival probability, %\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e35\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e42\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e48\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e53\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e57\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e59\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e62\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e64\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; number at risk, n\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e11517\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e8316\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e5690\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e4072\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e3051\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e2361\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e1853\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e1133\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e669\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; survival gain, %\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e+5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e+7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e+6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e+5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e+4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e+2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e+3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e+2\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"295\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; Actual survival rate, %\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e19\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"54\"\u003e\n\u003cp\u003e13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e11\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"10\" rowspan=\"6\" width=\"881\"\u003e\n\u003cp\u003eAbbreviation:\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003eThe conditional 5-year survival probability for these already survived 2 years in T1aN0 cohort, which means that if patients had survived 2 years after diagnosis, the probability of still alive in the seventh year after diagnosis is 74% (Purple background). \u003cbr /\u003e \u003csup\u003eb\u003c/sup\u003eAt the beginning of the interval\u003cbr /\u003e \u003csup\u003ec\u003c/sup\u003eRelative to the previous year;\u003cbr /\u003e \u003csup\u003ed\u003c/sup\u003eFor example, the 5-year overall survival rate in T1aN0 cohort is 73%, 10-year overall survival rate in T1aN0 cohort is 55% (Red background).\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cbr /\u003eTable 4:\u003c/strong\u003e Conditional probability of survival for a few years after having survived for a certain years since diagnosed according to tumor prognostic factors.\u003c/p\u003e\n\u003ctable border=\"1\" width=\"0\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"233\"\u003e\n\u003cp\u003e\u0026nbsp;1-, 3-, 5-, 8-year OS rates, (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"5\" width=\"444\"\u003e\n\u003cp\u003e3-year conditional survival probability, (%) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003eVariables\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e1-year OS\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e3-year OS\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e5-year OS\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e8-year OS\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e1 y after surgery\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e2 y after surgery\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e3 y after surgery\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e4 y after surgery\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e5 y after surgery\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003eAll patients\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e83.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e63.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e50.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e38.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e67\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e71\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e73\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e75\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e77\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003eAge\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; 15-45 years\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e94.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e83.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e77.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e71.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e85\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e88\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e89\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e91\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e93\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; 46-70 years\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e87.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e68.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e56.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e45.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e70\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e74\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e77\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e80\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e81\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; \u0026ge;70 years\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e78.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e56.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e41.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e27.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e61\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e66\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e67\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e65\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003eGender (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; Female\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e87.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e69.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e57.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e45.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e72\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e74\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e76\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e78\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e79\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; Male\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e79.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e56.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e44\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e32.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e62\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e67\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e70\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e72\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e73\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003eRace\u0026nbsp; (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; White\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e83.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e62.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e50.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e38.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e67\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e71\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e73\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e75\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e76\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; Black\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e83.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e62.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e49.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e38.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e66\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e70\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e73\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e75\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e77\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; other\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e88.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e69.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e56.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e44.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e71\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e72\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e73\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e76\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e79\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e8\u003csup\u003eth\u003c/sup\u003e AJCC* pathological stage(%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; Stage Ⅰ\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e91.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e75.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e63.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e50.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e76\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e76\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e77\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e78\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e78\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; Stage Ⅱ\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e81.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e55.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e42.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e30.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e59\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e67\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e71\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e73\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; Stage Ⅲ\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e75\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e44.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e32.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e23.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e58\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e70\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e72\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; Unknown\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e42.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e22.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e14.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e43\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e57\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e61\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e68\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003ePathological T stage (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; pT1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e90.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e73.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e60.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e47.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e73\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e74\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e76\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e77\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e78\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; pT2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e82.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e58.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e45.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e33.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e62\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e66\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e70\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e73\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e74\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; pT3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e76.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e50.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e39.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e28.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e57\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e65\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e70\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e73\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e74\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; pT4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e57.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e33.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e24.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e18.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e49\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e59\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e65\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e71\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e74\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003eTumour grade (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; grade Ⅰ\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e94.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e83.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e74\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e61.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e84\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e83\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e84\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e84\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e83\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; grade Ⅱ\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e88.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e67.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e52.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e39.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e67\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e69\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e71\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e73\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e74\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; grade Ⅲ\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e80.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e55.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e43.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e31.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e60\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e66\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e69\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e72\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e74\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; grade Ⅳ\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e74.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e49.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e39.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e29.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e59\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e68\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e73\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e74\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e74\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; Unknown\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003eTumour size (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp; \u0026le;30 mm\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e90.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e73.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e60.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e47.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e73\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e74\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e76\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e77\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e78\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; 31-50 mm\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e82.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e58.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e45.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e33.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e62\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e66\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e70\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e73\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e74\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; 51-70mm\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e76.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e50.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e39.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e28.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e57\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e65\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e70\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e73\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e72\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp; \u0026ge; 71 mm\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e69.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e40.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e31.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e23.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e61\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e68\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e74\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e76\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; Unknown\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e47.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e26.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e18.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e13.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003eHistological subtype (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; Adenocarcinoma\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e89.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e71.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e58.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e46.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e72\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e73\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e76\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e78\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e79\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; Squamous cell carcinoma\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e79.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e55.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e43.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e30.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e61\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e66\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e69\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e69\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e70\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; Adenosquamous carcinoma\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e80.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e52.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e40.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e29.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e45\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e52\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e68\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e72\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e72\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; Large cell carcinoma\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e75.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e50.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e39.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e29.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e59\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e67\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e72\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e74\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e74\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; Other\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003ePrimary tumor site\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; Upper lobe\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e85.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e65.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e52.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e40.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e68\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e71\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e73\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e75\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e76\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; Middle lobe\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e89.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e72\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e59.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e48.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e73\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e75\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e77\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e80\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e81\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; Lower lobe\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e85.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e64.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e51.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e39.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e67\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e71\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e73\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e75\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e76\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; Overlapping\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e53.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e34.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e26.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e56\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e71\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e76\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e78\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003eType of surgery\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; local distribution or excision\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e66.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e36.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e19.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e11.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e41\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e41\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e47\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e53\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e58\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; Sublobar resection\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e85.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e62.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e48.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e34.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e66\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e68\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e70\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e71\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; Lobectomy\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e88.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e68.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e56.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e43.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e70\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e73\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e75\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e77\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e78\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; Resection of whole lung\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e76.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e51.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e40.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e31.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e59\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e66\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e71\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e75\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e77\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; No surgery\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e29.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e10.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e5.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e3.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e34\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e44\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e53\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e68\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003eNumber of positive lymph node\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e89.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e73.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e61.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e48.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e75\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e76\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e78\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e78\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e79\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; 1-15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e79.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e49.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e34.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e24.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e51\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e57\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e62\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e67\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e70\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; \u0026ge; 16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e66.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e43.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e31.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e22.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e55\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e60\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e68\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e71\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003eRadiation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; Yes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e76.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e43.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e30.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e20.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e46\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e54\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e60\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e65\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e69\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; No\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e84.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e66.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e54.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e41.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e71\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e73\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e75\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e76\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e77\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003eChemotherapy\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; Yes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e84.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e55.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e42.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e31.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e56\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e62\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e68\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e72\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e74\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; No\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e83.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e65.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e53.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e41.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e71\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e73\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e75\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e76\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e77\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003eSeer stage\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; local\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e90.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e75.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e63.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e50.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e76\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e77\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e78\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e79\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e79\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; regional\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e80.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e54.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e40.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e29.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e58\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e63\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e68\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e71\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e73\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u0026nbsp; Unknown\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e37\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e18.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e12.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e8.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e42\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e49\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e56\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e62\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"93\"\u003e\n\u003cp\u003e67\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviation: \u003cbr /\u003e \u003csup\u003ea\u003c/sup\u003eFor example, in the cohort of aged 15-45 years old, the 4-year survival rate for those who had survived 1 years (CS(4ǀ1)) after diagnosis is 85%, the 8-year survival rate for those who had survived 5 years (CS(8ǀ5)) after diagnosis is 93%.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Non-small cell lung cancer, Non-metastasis, postoperative, conditional survival probability, SEER database","lastPublishedDoi":"10.21203/rs.3.rs-138915/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-138915/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e This study aims to explore the dynamic survival probability of lung cancers after resection based on those had survived several years, provide more precise monitoring and treatment information for non-metastatic non-small cell lung cancer (NSCLC) patients.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMaterials and Methods:\u003c/strong\u003e In the Surveillance,\u0026nbsp;Epidemiology,\u0026nbsp;and\u0026nbsp;End\u0026nbsp;Results (SEER) database (2000–2016), 95531 eligible non-metastatic NSCLC patients after surgery were enrolled, TNM stage were reclassified, the methods of condition survival probability (CS) and actuarial overall survival (OS) were used to explore the relationship between clinicopathological characteristics and cancer prognosis.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e The 1-, 3-, 5- and 10-year OS of included patients were 83.6% (95%CI: 83%-84%), 62.9% (95%CI: 62.6%-63.1%), 50.8% (95%CI: 50.6%-51.0%) and 33.1% (95%CI: 32.7%-33.6%) respectively. For those already survived 1, 2, 3, 4 and 5 years after diagnosis, the probability for surviving an additional 3 years were 67%, 71%, 73%, 75% and 77% respectively. Enrolled population were reclassified into 9 cohorts including T1aN0, T1bN0, T1cN0, T2aN0, T2bN0, T3N0, T4N0, T1-4N1, T1-4N2 according to 8th TNM staging. According to the conditional survival probability, patients with unfavorable tumor stage diagnosed initially at surgery had the significant improvement in CS over time. Analysis based on other clinical features demonstrated similar conclusion that the poorer the initial diagnosis, the more significant the benefit of conditional survival over time.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e The worse the patient's prognosis, the more significant the benefit of time-dependent conditional survival probability, long-lived cancer patients may have a better cancer prognosis.\u003c/p\u003e","manuscriptTitle":"Conditional Survival Probability of Non-Small Cell Lung Cancers, Based on The SEER Database","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-02-04 15:11:44","doi":"10.21203/rs.3.rs-138915/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1cc4316c-d9cf-4eae-9cbd-1074af86d961","owner":[],"postedDate":"February 4th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":2246095,"name":"Cancer Biology"}],"tags":[],"updatedAt":"2021-04-21T15:59:10+00:00","versionOfRecord":[],"versionCreatedAt":"2021-02-04 15:11:44","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-138915","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-138915","identity":"rs-138915","version":["v1"]},"buildId":"ehx78VzkSd0WSzXnipQa-","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}