Evaluating the Role of Age in Post-Nephrectomy Outcomes for Patients with Early-Stage Renal Cell Carcinoma: A Retrospective Multi-Centre Cohort Study

Evaluating the Role of Age in Post-Nephrectomy Outcomes for Patients with Early-Stage Renal Cell Carcinoma: A Retrospective Multi-Centre Cohort Study | 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 Evaluating the Role of Age in Post-Nephrectomy Outcomes for Patients with Early-Stage Renal Cell Carcinoma: A Retrospective Multi-Centre Cohort Study Zhi-Wei Sun, Dong-Liang Yang, Wei-Wei Lu, Jia-Wei Lu, Li Xu, Zhi-Xiang Gao, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8299759/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 & Objectives: Renal cell carcinoma (RCC) incidence is rising among both elderly and younger populations. This study aimed to investigate the impact of age on long-term oncological outcomes following curative nephrectomy for early-stage RCC. Methods A retrospective analysis was conducted using data from 5 Chinese medical centers, including patients who underwent curative nephrectomy for T1-T2 RCC between 2008 and 2023. Patients aged < 40 years and ≥ 75 years were compared for overall survival (OS), cancer-specific survival (CSS), and recurrence rates. Propensity score matching (PSM) was employed to balance baseline characteristics. Results Of 357 patients, 234 (65.5%) were young and 123 (34.5%) were elderly. PSM yielded 96 pairs. In the matched cohort, young patients demonstrated significantly lower 5-year OS (76.0% vs 86.5%, P = 0.038) and CSS rates (86.5% vs 93.8%, P = 0.019) compared to elderly patients. The 5-year cumulative recurrence rate was higher in young patients (28.1% vs 13.5%, P = 0.003). Multivariable analysis confirmed young age as an independent risk factor for decreased OS (HR 2.407, 95% CI 1.387–4.177; P = 0.002) and increased recurrence (HR 2.824, 95% CI 1.393–5.722; P = 0.004). Conclusion Diverging from traditional expectations, our study reveals that younger patients experienced poorer long-term outcomes after curative nephrectomy for early-stage RCC. These findings suggest the need for more intensive surveillance and possibly more aggressive treatment strategies for young RCC patients. Renal cell carcinoma nephrectomy Recurrence Survival young elderly Figures Figure 1 Figure 2 INTRODUCTION Renal cell carcinoma (RCC) represents a significant global health burden, ranking as the 16th most common cancer worldwide 1 . According to GLOBOCAN 2020, there were approximately 431,288 new cases and 179,368 deaths attributed to kidney cancer globally in 2020 2 . The incidence of RCC increases with age, with about 50% of cases occurring in individuals aged 65 years and older 3 , 4 . Curative nephrectomy remains the gold standard curative treatment for RCC, especially for early-stage and unifocal tumors 5 , 6 . The overall prognosis for patients undergoing this procedure is generally favorable, with some studies reporting 5-year recurrence-free survival rates exceeding 80% 7 . However, a concerning trend has emerged: the rising incidence of RCC among younger populations, with rates in individuals aged 20–39 years increasing from 0.9 per 100,000 in 1975 to 1.6 per 100,000 in 2015 8,9 . Influenced by evolving lifestyle factors and environmental exposures, there is a discernible demographic shift towards younger populations affected by sporadic renal neoplasms. This trend underscores the necessity for a more nuanced approach to long-term prognostication and therapeutic management in young adults, where biopsy and active surveillance are less frequently implemented compared with their older counterparts 10 , 11 . Numerous studies have revealed that age difference at cancer diagnosis was significantly correlated with long-term postoperative outcomes in a spectrum of malignancies, encompassing gastric adenocarcinoma, breast neoplasms, and colorectal carcinomas 12 , 13 . While increased age has traditionally been associated with higher surgical risks and postoperative complications, emerging evidence across various malignancies suggests that younger patients may present with more aggressive tumor characteristics and worse overall survival following curative resection 14 , 15 . Age at diagnosis has long been recognized as a critical factor influencing cancer outcomes, but its impact on RCC prognosis remains a subject of debate 16 , 17 . In the context of RCC, the impact of age on outcomes remains controversial. Some studies have reported better outcomes for younger patients, with one analysis showing a 5-year relative survival rate of 85.7% for patients aged 20–39 years compared to 74.1% for those over 60 18,19 . Conversely, other research indicates that younger patients may present with higher-grade and more advanced-stage tumors, as well as a higher proportion of rare non-clear cell subtypes associated with poorer prognoses 20 , 21 . The discrepancies in these findings can be attributed to several factors. Firstly, the definition of "young" and "elderly" varies across studies, with different age cut-offs used for categorization. Secondly, the higher proportion of non-cancer-specific deaths among elderly patients may skew overall survival analyses, suggesting that cancer-specific survival might be a more appropriate measure of oncological outcomes 19 . Additionally, many existing studies are single-center with relatively small sample sizes, potentially limiting the generalizability of their findings. To address these limitations and provide a more comprehensive understanding of age-related prognostic differences in RCC, we conducted a single-center study comparing long-term overall survival, cancer-specific survival, and recurrence rates between young (< 40 years) and elderly (≥ 75 years) patients undergoing curative-intent nephrectomy for RCC. Propensity score matching (PSM) was employed to balance baseline characteristics between the two groups, aiming to offer insights that could inform personalized treatment strategies and follow-up protocols for RCC patients across different age groups. METHODS Study Design and Patient Population Data from a multicenter database were obtained after obtaining approval from 5 institutions’ review boards, as well as informed consent for the use of data for research purposes from all patients on admission or before their Operation. We identified 1644 patients who underwent curative nephrectomy for early-stage (T1-T2) solitary RCC between January 2008.06 and December 2023.06. To account for therapeutic advances, patients were stratified into pre-immunotherapy (pre-IO: year 2008–2015) and post-immunotherapy (post-IO: year 2016–2023) eras based on the landmark approval of immune checkpoint inhibitors for RCC in 2015. All patients were pathologically confirmed to have RCC postoperatively. The diagnosis of RCC was confirmed on postoperative histopathological examination. Histologic subtype was categorized according to WHO 2022 classification, including clear cell RCC (ccRCC), papillary, chromophobe, and unclassified RCC. Exclusion criteria were as follows: age < 18 years old; history of chronic hepatic or renal insufficiency; Palliative surgery; concomitant malignancy or prior anti-tumor therapy; perioperative 90-day mortality; severe postoperative complications prolonging hospital stay; missing important clinical data; and loss to follow-up within 1 year after surgery. After applying these criteria, 357 patients were included in the final analysis cohort. The study was conducted in accordance with the Declaration of Helsinki. Informed consent was waived due to the retrospective nature of the study by the Institutional Review Board of Zhangjiagang Hospital affiliated to Soochow University (ZJGYYLL-2023-11-lw002). Clinical Characteristics Patient clinical characteristics included age, sex, body mass index (BMI), co-morbidities, American Society of Anesthesiologists (ASA) score, long-term smoking, chronic alcohol exposure, abnormal blood parameters, surgical approach, maximum tumor diameter, microvascular invasion, satellite nodules, International Society of Urological Pathology (ISUP) grade, and regular surveillance. Curative nephrectomy includes radical nephrectomy and nephron-sparing surgery. Co-morbidities comprised hypertension, diabetes mellitus, chronic obstructive pulmonary disease and cardiovascular diseases. Abnormal blood parameters were defined as the presence of three or more of the following: leukocytosis (> 10×10^9/L), anemia (hemoglobin < 90 g/L), thrombocytosis or thrombocytopenia (platelet count 450×10^9/L), elevated C-reactive protein (> 10 mg/L), abnormal serum calcium levels ( 2.75 mmol/L), and prolonged coagulation time (> 16 seconds). Study Endpoints and Propensity Score Matching This study focused on three primary outcomes: overall survival (OS), cancer-specific survival (CSS), and time-to-recurrence (TTR). OS was defined as the interval between the date of nephrectomy and either death from any cause or the last documented follow-up for those still alive. CSS was measured from the time of surgery until death attributed to RCC, with patients who died from other causes or remained alive at last contact considered as censored observations. TTR was the time from surgical intervention to the first detected recurrence, with those who died without documented recurrence or remained recurrence-free at last follow-up treated as censored cases. To balance differences in baseline characteristics between young (< 40 years) and elderly (≥ 75 years) patients, propensity score matching (PSM) was performed using a 1:1 nearest neighbor matching algorithm without replacement and a caliper width of 0.1 standard deviations of the logit of the propensity score. Variables included in the PSM model were sex, BMI, smoking status, alcohol consumption, abnormal blood parameters, surgical approach, maximum tumor diameter, microvascular invasion, satellite nodules, ISUP grade, and Irregular Surveillance. As ASA score and co-morbidities are intrinsic variables known to be related to age, these were not matched in the PSM model. Follow-up Protocol Following hospital discharge, a unified post-operative surveillance strategy was implemented across all participating medical centers to monitor potential cancer recurrence. This standardized approach ensured consistency in patient follow-up procedures throughout the multi-institutional study. Postoperative follow-up included the first evaluation at 1 month after surgery, followed by regular check-ups every 2–3 months for the first 2 years, then every 6 months thereafter. Each surveillance visit included physical examination, laboratory tests, and abdominal ultrasonography and/or enhanced computed tomography (CT) or magnetic resonance imaging (MRI). Irregular surveillance was defined as any deviation from the prescribed follow-up schedule, which included follow-up intervals exceeding the recommended timeframes, missed appointments, or cases where recurrences were detected through symptomatic presentation or incidental findings rather than scheduled screenings. Statistical Analysis Continuous variables were expressed as mean ± standard deviation or median (interquartile range) and compared using Student's t-test or Mann-Whitney U test as appropriate. Categorical variables were expressed as numbers (percentages) and compared using chi-square test or Fisher's exact test. Survival curves were generated using the Kaplan-Meier method and compared with the log-rank test. Univariable and multivariable Cox proportional hazards regression models were used to identify independent prognostic factors for OS, CSS, and recurrence. Variables with P < 0.1 in univariable analysis were included in the multivariable model. Hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated. Treatment era (post-IO vs pre-IO) was included as a covariate in Cox regression models. Survival outcomes between pre-IO and post-IO groups were compared using Kaplan-Meier analysis. All statistical analyses were performed using SPSS version 26.0 (IBM Corp., Armonk, NY, USA). Two-sided P < 0.05 was considered statistically significant. RESULTS Patient Characteristics and Baseline Comparisons Following the application of inclusion and exclusion criteria, our study encompassed 357 patients who underwent curative nephrectomy for early-stage RCC ( Fig. 1 ) . The cohort comprised 234 young patients (65.5%) with a median age of 33.6 years (range: 18–39 years) and 123 elderly patients (34.5%) with a median age of 78.9 years (range: 75–93 years). PSM yielded 96 pairs of young and elderly patients. Table 1 summarizes the clinical and operative characteristics of both groups before and after PSM. In the matched cohort, young and elderly patients showed no significant differences in tumor features and surgical variables, except for the prevalence of comorbidities (6.3% vs 34.4%, P < 0.001) and ASA score ≥ 3 (4.2% vs 49.0%, P < 0.001), and larger tumor size (61.5% vs 45.8%, P = 0.030). Histologic subtype distribution did not differ between matched young and elderly groups (ccRCC 79.2% vs 84.4%, P = 0.350). Table 1 Comparisons of patients’ clinical characteristics and operative variables between the young and the elderly before and after propensity score matching. Variables The entire cohort The PSM cohort The Young (< 40 years old) (N = 234) The Elderly (≥ 75 years old) (N = 123) P The Young (< 40 years old) (N = 96) The Elderly (≥ 75 years old) (N = 96) P Age, years* 33.6 (4.6) 78.9 (3.9) < 0.001 34.2 (4.5) 79.1 (4.1) 0.673 Male sex 205 (87.6) 99 (80.5) 0.072 84 (87.5) 82 (85.4) 0.190 BMI ≥ 25 64 (27.4) 59 (48.0) < 0.001 45 (46.9) 40 (41.7) 0.468 Co-morbidities 8 (3.4) 43 (35.0) < 0.001 6 (6.3) 33 (34.4) < 0.001 ASA score ≥ 3 9 (3.8) 57 (46.3) < 0.001 4 (4.2) 47 (49.0) < 0.001 Long-term smoking 29 (12.4) 37 (30.1) < 0.001 24 (25.0) 26 (27.1) 0.742 Chronic alcohol exposure 44 (18.8) 51 (41.5) < 0.001 35 (36.5) 31 (32.3) 0.543 Abnormal blood parameters ≥ 3 11 (4.7) 19 (15.4) 0.001 9 (9.4) 11 (11.5) 0.637 Laparoscopic approach 119 (50.9) 46 (37.4) 0.015 37 (38.5) 39 (40.6) 0.768 Largest tumor size ≥ 4cm 118 (50.4) 54 (43.9) 0.241 59 (61.5) 44 (45.8) 0.030 Clear cell RCC 186 (79.5) 102 (82.9) 0.434 76 (79.2) 81 (84.4) 0.350 Microscopic Vascular Invasion 47 (20.1) 30 (24.4) 0.347 22 (22.9) 23 (24.0) 0.865 Satellite nodules 48 (20.5) 15 (12.2) 0.050 22 (22.9) 15 (15.6) 0.200 ISUP grade ≥ 3 69 (29.5) 31 (25.2) 0.392 26 (27.1) 23 (24.0) 0.619 Irregular Surveillance 72 (30.8) 25 (20.3) 0.035 23 (24.0) 23 (24.0) 0.999 * Values are mean ± standard deviation. RCC, Renal Cell Carcinoma. ASA, American Society of Anesthesiologists; BMI, body mass index; CI, confidence interval; ISUP, International Society of Urological Pathology; PSM, propensity score matching. Long-term Oncological Outcomes Table 2 presents a comparison of long-term oncological outcomes between young and elderly groups before and after PSM. The overall recurrence rate was significantly higher in the young group both before (32.9% vs 17.1%, P < 0.001) and after PSM (34.4% vs 16.7%, P = 0.005). During the follow-up period, overall mortality rates were comparable between groups before PSM (39.3% vs 29.3%, P = 0.060), but the young group exhibited higher mortality after PSM (46.9% vs 29.2%, P = 0.011). Cancer-specific mortality rates were consistently higher in the young group both before (17.5% vs 8.0%, P < 0.01) and after PSM (17.7% vs 7.3%, P < 0.01). In the entire cohort (N = 357), pre-IO (n = 156) and post-IO (n = 201) groups demonstrated comparable 5-year oncologic outcomes (OS: 80.1% vs 87.6%, P = 0.057; CSS: 89.7% vs 90.5%, P = 0.138; and recurrence rates: 26.3% vs 17.9%, P = 0.126) (Table S1 ). Table 2 Comparisons of long-term oncological outcomes between the young and the elderly before and after propensity score matching Entire cohort PSM cohort The Young (< 40 years old) (N = 234) The Elderly (≥ 75years old) (N = 123) P The Young (< 40 years old) (N = 96) The Elderly (≥ 75 years old) (N = 96) P Period of follow-up, months* 71.8 (3.0) 70.9 (2.0) 0.362 71.0 (5.1) 69.6 (2.3) 0.370 Recurrence during the follow-up 77 (32.9) 21 (17.1) 0.001 33 (34.4) 16 (16.7) 0.005 Death during the follow-up 92 (39.3) 36 (29.3) 0.060 45 (46.9) 28 (29.2) 0.011 Cancer-specific death 41 (17.5) 10 (8.0) 17 (17.7) 7 (7.3) Median overall survival, months, 95% CI 89.5 (76.5, 102.4) 93.6 (77.5, 109.7) 0.195 77.8 (71.8, 83.8) 93.6 (76.1, 111.1) 0.038 1-year overall survival rate 97.8 98.3 96.9 97.9 3-year overall survival rate 90.6 91.8 85.4 92.7 5-year overall survival rate 83.3 86.2 76.0 86.5 Median cancer-specific survival, months, 95% CI - - 0.018 - - 0.019 1-year cancer-specific survival rate 98.7 99.1 97.9 98.9 3-year cancer-specific survival rate 93.5 95.1 91.7 95.8 5-year cancer-specific survival rate 88.9 92.7 86.5 93.8 Median time to recurrence, months, 95% CI - - 0.003 - - 0.003 1-year cumulative recurrence rate 6.4 4.1 11.5 3.1 3-year cumulative recurrence rate 14.5 10.6 18.8 11.5 5-year cumulative recurrence rate 25.2 13.8 28.1 13.5 *Values are median ± standard deviation. CI, confidence interval; PSM, propensity score matching Figures 2 A-C illustrate the comparisons of OS, CSS, and cumulative recurrence rates between young and elderly patients in the matched cohort. After PSM, the 5-year OS rate was significantly lower in the young group (76.0% vs 86.5%, P = 0.038). Similarly, the 5-year CSS rate was inferior in the young group (86.5% vs 93.8%, P = 0.019). The 5-year cumulative recurrence rate remained higher in the young group both before (25.2% vs 13.8%, P = 0.003) and after PSM (28.1% vs 13.5%, P = 0.003). Univariable and Multivariable Analyses Tables 3 and 4 present the results of univariable and multivariable Cox regression analyses for predicting OS and time-to-recurrence in the PSM cohort, respectively. Factors associated with poor OS after surgery included young age, long-term smoking history, preoperative abnormal blood parameters (≥ 3), larger tumor diameter (≥ 4cm), presence of microvascular invasion, poor ISUP grade, and irregular surveillance. Risk factors for recurrence encompassed young age, preoperative abnormal blood parameters (≥ 3), larger tumor diameter (≥ 4cm), microvascular invasion, presence of satellite nodules, and poor ISUP grade. Compared to elderly patients, young individuals who underwent curative nephrectomy for RCC demonstrated independently and significantly lower survival rates (HR 2.407, 95% CI 1.387–4.177; P = 0.002) and higher recurrence rates (HR 2.824, 95% CI 1.393–5.722; P = 0.004) even after adjusting for histology (ccRCC vs. non-ccRCC), while histologic subtype itself was not prognostic (OS: P = 0.114; recurrence: P = 0.863). Meanwhile, treatment era (post-IO vs pre-IO) was not a significant predictor for OS (HR 1.142, 95% CI 0.717–1.817; P = 0.577) or recurrence (HR 1.047, 95% CI 0.596–1.840; P = 0.872) in the PSM cohort (Tables 3 & 4 ). Table 3 Univariable and multivariable Cox regression analyses predicting overall survival after curative-intent nephrectomy for renal cell carcinoma after propensity score matching Variables UV HR (95% CI) UV P MV HR (95% CI) MV P The Young 1.658 (1.022, 2.690) 0.041 2.407 (1.387, 4.177) 0.002 Male sex 1.002 (0.512, 1.962) 0.995 BMI ≥ 25 1.317 (0.825, 2.103) 0.248 Co-morbidities 1.358 (0.719, 2.564) 0.345 ASA score ≥ 3 0.718 (0.398, 1.295) 0.271 Long-term smoking 3.162 (1.834, 5.450) < 0.001 3.531 (1.719, 7.265) 0.001 Chronic alcohol exposure 0.713 (0.427, 1.191) 0.197 Abnormal blood parameters ≥ 3 8.335 (3.991, 17.406) < 0.001 2.927 (1.134, 7.559) 0.026 Laparoscopic approach 0.892 (0.552, 1.439) 0.638 Clear cell RCC 1.712 (0.927, 3.163) 0.086 NS 0.114 Largest tumor size ≥ 4cm 2.395 (1.448, 3.963) 0.001 3.212 (1.874, 5.506) < 0.001 Microscopic Vascular Invasion 2.213 (1.348, 3.634) 0.002 2.518 (1.427, 4.444) 0.001 Satellite nodules 1.525 (0.890, 2.615) 0.125 ISUP grade ≥ 3 3.437 (2.126, 5.557) < 0.001 2.210 (1.309, 3.729) 0.003 Irregular Surveillance 3.164 (1.875, 5.339) < 0.001 2.220 (1.257, 3.920) 0.006 Post-IO 1.142 (0.717, 1.817) 0.577 ASA, American Society of Anesthesiologists; BMI, body mass index; CI, Confidence interval; HR, Hazard ratio; ISUP, International Society of Urological Pathology; MV, multivariable; RCC, Renal Cell Carcinoma; UV, univariable. Table 4 Univariable and multivariable Cox regression analyses predicting time-to-recurrence after curative-intent nephrectomy for renal cell carcinoma after propensity score matching Variables UV HR (95% CI) UV P MV HR (95% CI) MV P The Young 2.407 (1.324, 4.378) 0.004 2.824 (1.393, 5.722) 0.004 Male sex 1.184 (0.555, 2.525) 0.663 BMI ≥ 25 1.222 (0.697, 2.140) 0.484 Co-morbidities 1.255 (0.624, 2.523) 0.524 ASA score ≥ 3 0.598 (0.290, 1.233) 0.164 Long-term smoking 2.255 (1.217, 4.178) 0.010 2.153 (0.939, 4.940) 0.070 Chronic alcohol exposure 0.586 (0.306, 1.124) 0.108 Abnormal blood parameters ≥ 3 7.051 (3.397, 14.634) < 0.001 3.433 (1.293, 9.114) 0.013 Laparoscopic approach 0.798 (0.443, 1.438) 0.453 Clear cell RCC 0.942 (0.480, 1.849) 0.863 Largest tumor size ≥ 4cm 2.445 (1.335, 4.481) 0.004 2.009 (1.006, 4.010) 0.048 Microscopic Vascular Invasion 4.100 (2.337, 7.194) < 0.001 3.076 (1.612, 5.871) 0.001 Satellite nodules 3.725 (2.104, 6.592) < 0.001 2.960 (1.575, 5.563) 0.001 ISUP grade ≥ 3 6.018 (3.382, 10.708) < 0.001 3.306 (1.753, 6.234) < 0.001 Irregular Surveillance 1.657 (0.925,2.967) 0.089 1.652 (0.891, 3.062) 0.111 Post-IO 1.047 (0.596, 1.840) 0.872 ASA, American Society of Anesthesiologists; BMI, body mass index; CI, Confidence interval; HR, Hazard ratio; ISUP, International Society of Urological Pathology; MV, multivariable; RCC, Renal Cell Carcinoma; UV, univariable. DISCUSSION This multicenter retrospective study compared the clinicopathological features and long-term oncological outcomes of young (< 40 years) and elderly (≥ 75 years) patients who underwent curative nephrectomy for RCC. Through PSM and multivariate Cox regression analysis, our results demonstrated that younger patients had significantly lower OS, CSS rates, and higher recurrence rates compared to elderly patients after nephrectomy for RCC. These findings have important implications for postoperative monitoring, follow-up, and anti-recurrence treatment strategies, especially for young RCC patients. To some extent, our findings may challenge the traditional notion that younger patients generally have a better prognosis. While some previous studies have reported better outcomes for young RCC patients 18 , our results consistent with research on other malignancies such as hepatocellular carcinoma, gastric cancer, and breast cancer, which suggest that younger patients may have more aggressive tumor characteristics and poorer prognosis. In fact, the disparity in long-term survival outcomes may be attributed to the significantly higher proportion of non-cancer-specific deaths among elderly patients, who often have severe comorbidities and poorer general health conditions that pose potential life-threatening risks 22 , 23 . This explains the notably lower proportion of cancer-specific deaths among elderly patients compared to their younger counterparts. Consequently, when considering the long-term oncological prognosis of elderly cancer patients, CSS rates may be more informative and clinically relevant than overall survival rates. Notably, we observed that the 5-year cumulative recurrence rate was significantly higher in young patients compared to elderly patients (28.1% vs 13.5%, P = 0.003). This difference may reflect the unique biological behavior of tumors in younger patients. Studies have shown that RCC in young patients may have distinct molecular characteristics, leading to higher invasiveness and metastatic potential 24 . Furthermore, the immune systems of younger patients may respond differently to the immune evasion mechanisms of RCC cells, potentially explaining the higher recurrence rates 24 . These results suggest that young patients should be closely monitored for tumor recurrence even after radical surgery. Multivariate analysis in our study revealed that young age is an independent risk factor for decreased overall survival (HR 2.28, 95% CI 1.314–3.951, P = 0.003) and increased recurrence rate (HR 2.82, 95% CI 1.393–5.722, P = 0.004). This underscores the importance of age in RCC prognosis and suggests the need for personalized treatment and follow-up strategies for different age groups. For instance, younger patients may require more frequent and intensive postoperative monitoring, as well as more aggressive adjuvant treatment regimens. Additionally, we found that long-term smoking history, preoperative abnormal blood parameters, larger tumor diameter, microscopic vascular invasion, and poor ISUP grade were significant factors affecting long-term prognosis in RCC patients. These findings are consistent with previous studies and emphasize the importance of these factors in RCC risk stratification and treatment decision-making 25 . Young individuals who smoke frequently or work in environments with secondhand smoke should reduce cigarette exposure and actively minimize exposure to risk factors in daily life 26 . It is also worth noting that younger patients, often in better general health and busy with work, may neglect regular medical check-ups, potentially leading to delayed tumor discovery and more challenging treatment with relatively poorer prognosis. This could be the explanation for why young patients had significantly more ≥ pT1b tumors than older patients (61.5% vs 45.8%, P = 0.030) after propensity matching in this study and this situation should also be given sufficient attention by young patients 27 . A paradoxical finding emerged regarding non-cancer mortality: young patients experienced higher rates (28 events vs 21 in elderly) despite their general health advantage. Our analysis revealed starkly contrasting etiological patterns—trauma accounted for 46.4% of young non-cancer deaths (including 7 traffic accidents and 6 suicides), while premature cardiovascular events represented 32.1% (primarily myocardial infarction/cardiac arrest). These findings suggest risk-taking behaviors and undiagnosed cardiometabolic comorbidities may underlie premature mortality in this population. Conversely, elderly non-cancer deaths predominantly reflected expected age-related decline (cardiovascular 71.4%, respiratory 19.0%). Importantly, this apparent mortality paradox may be partially explained by competing risk dynamics: elderly patients' elevated baseline mortality risk is attenuated by earlier cancer-specific deaths, thereby reducing observed non-cancer events. Crucially, cancer-specific mortality remained significantly elevated in young patients (17.7% vs 7.3%, P < 0.01), confirming their inherent biological vulnerability to disease progression independent of non-cancer mortality patterns. Furthermore, our era-stratified analysis revealed no significant survival differences between pre-IO and post-IO groups, suggesting that immunotherapy advancements—while transformative for advanced RCC—may have limited impact on outcomes in early-stage disease treated with curative nephrectomy. This aligns with current guidelines recommending adjuvant therapy primarily for high-risk localized RCC rather than early-stage cases. Our study has several limitations. Firstly, as a retrospective study, selection bias may exist. Although PSM was used to reduce this bias, it cannot be completely eliminated. For instance, many young tumor patients may be more aggressive in treatment decision-making, particularly in surgical strategy, while in the elderly population, considerations of physical condition and underlying diseases may lead to more conservative treatment strategies or even abandonment of surgical treatment. This age-related treatment strategy bias objectively exists. Secondly, we did not obtain some important information that might affect prognosis, such as molecular marker data and detailed treatment information. Thirdly, although our follow-up time was relatively long, it may still be insufficient to fully assess the long-term prognosis of RCC, especially for younger patients. Fourth, while we addressed era effects through stratified analysis and Cox regression, the non-significant results (P = 0.057–0.872) should be interpreted cautiously given the cohort's focus on early-stage disease where systemic therapy utilization is inherently low. CONCLUSION This study demonstrates that younger patients have a higher risk of recurrence and lower overall survival rates after curative nephrectomy compared to elderly patients. These findings highlight the importance of age as a prognostic factor in RCC and suggest the need for personalized treatment and follow-up strategies for different age groups, with particular attention and more aggressive follow-up and anti-recurrence prevention treatment strategies for young RCC patients. Future research should focus on the molecular characteristics of RCC in young patients and the development of novel treatment strategies for this population. Abbreviations ASA American Society of Anesthesiologists BMI body mass index CSS cancer specific survival CT computed tomography CI confidence interval HR hazard ratio ISUP International Society of Urological Pathology MRI magnetic resonance imaging MV multivariable OS overall survival PSM propensity score matching RCC Renal cell carcinoma UV univariable. Declarations Ethics approval and consent to participate: The study was conducted in accordance with the Declaration of Helsinki. Informed consent was waived due to the retrospective nature of the study by the Institutional Review Board of Zhangjiagang Hospital affiliated to Soochow University (ZJGYYLL-2023-11-lw002) Consent for publication: All authors have read and approved the final manuscript, consented to its submission to Asian Journal of Urology, and agreed to transfer copyright to the publisher upon acceptance for publication. Competing interests: None. Funding: None. Author Contribution ZW Sun, DL Yang and WW Lu contributed equally to this work. Drs ZC Xiu and HX Gu had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: ZW Sun, DL Yang, WW Lu, ZC Xiu and HX Gu; Acquisition, analysis, or interpretation of data: ZW Sun, DL Yang, WW Lu, JW Lu, L Xu, ZX Gao, ZC Xiu, BY Zhu, ZR Li, Y Wu and HX Gu; Drafting of the manuscript: ZW Sun, DL Yang, WW Lu, ZC Xiu; Critical revision of the manuscript for important intellectual content: ZC Xiu, HX Gu; Statistical analysis: ZW Sun, DL Yang, WW Lu, ZC Xiu and HX Gu; Obtained funding: None. Administrative, technical, or material support: ZC Xiu, HX Gu; Study supervision: ZC Xiu, HX Gu; Final approval of manuscript: All authors. Acknowledgements: None. Authors' information (optional) : Not applicable. Availability of data and materials: Not applicable. References Makino T, Kadomoto S, Izumi K, Mizokami A. Epidemiology and Prevention of Renal Cell Carcinoma. Cancers (Basel). 2022;14(16):4059. Sung H, Ferlay J, Siegel RL, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021;71(3):209–49. Bahadoram S, Davoodi M, Hassanzadeh S, Bahadoram M, Barahman M, Mafakher L. Renal cell carcinoma: an overview of the epidemiology, diagnosis, and treatment. G Ital Nefrol. 2022;39(3):2022–vol3. [pii]. Conroy S, Catto J, Bex A, et al. Diagnosis, treatment, and survival from kidney cancer: real-world National Health Service England data between 2013 and 2019. BJU Int. 2023;132(5):541–53. Ljungberg B, Albiges L, Abu-Ghanem Y, et al. European Association of Urology Guidelines on Renal Cell Carcinoma: The 2019 Update. Eur Urol. 2019;75(5):799–810. Campbell SC, Clark PE, Chang SS, Karam JA, Souter L, Uzzo RG. Renal Mass and Localized Renal Cancer: Evaluation, Management, and Follow-Up: AUA Guideline: Part I. J Urol. 2021;206(2):199–208. Li KP, Chen SY, Wang CY, Li XR, Yang L. Perioperative and oncologic outcomes of minimally-invasive surgery for renal cell carcinoma with venous tumor thrombus: a systematic review and meta-analysis of comparative trials. Int J Surg. 2023;109(9):2762–73. Kaldany A, Blum KA, Paulucci DJ et al. An evaluation of race, ethnicity, age, and sex-based representation in phase I to II renal cell carcinoma clinical trials in the United States. Urol Oncol . 2018;36(8):363.e1-363.e6. Palumbo C, Pecoraro A, Rosiello G, et al. Renal cell carcinoma incidence rates and trends in young adults aged 20–39 years. Cancer Epidemiol. 2020;67:101762. Lee LS, Yuen JS, Sim HG. Renal cell carcinoma in young patients is associated with poorer prognosis. Ann Acad Med Singap. 2011;40(9):401–6. Gopee-Ramanan P, Chin SS, Lim C, Shanbhogue KP, Schieda N, Krishna S. Renal Neoplasms in Young Adults. Radiographics. 2022;42(2):433–50. Wang J, Wang J, Li Q, et al. Young breast cancer patients who develop distant metastasis after surgery have better survival outcomes compared with elderly counterparts. Oncotarget. 2017;8(27):44851–9. Cheng L, Chen S, Wu W, et al. Gastric cancer in young patients: a separate entity with aggressive features and poor prognosis. J Cancer Res Clin Oncol. 2020;146(11):2937–47. Panian J, Lin X, Simantov R, Derweesh I, Choueiri TK, McKay RR. The Impact of Age and Gender on Outcomes of Patients With Advanced Renal Cell Carcinoma Treated With Targeted Therapy. Clin Genitourin Cancer. 2020;18(5):e598–609. Joung JY, Kwon WA, Lim J, et al. Second Primary Cancer Risk among Kidney Cancer Patients in Korea: A Population-Based Cohort Study. Cancer Res Treat. 2018;50(1):293–301. Abu-Ghanem Y, Powles T, Capitanio U, et al. Should patients with low-risk renal cell carcinoma be followed differently after nephron-sparing surgery vs Curative Nephrectomy. BJU Int. 2021;128(3):386–94. Volpe A, Capitanio U, Falsaperla M, et al. Partial nephrectomy for renal tumors: recommendations of the Italian Society of Urology RCC working group. Minerva Urol Nephrol. 2024;76(1):9–21. Liu F, Davaro F, Wong R, Siddiqui S, Hamilton Z. Young age is associated with decreased recurrence for renal cell carcinoma. Can J Urol. 2022;29(3):11142–9. Tang F, Lu Z, He C, Zhang H, Wu W, He Z. 53 years old is a reasonable cut-off value to define young and old patients in clear cell renal cell carcinoma: a study based on TCGA and SEER database. BMC Cancer. 2021;21(1):638. Abdulfatah E, Kennedy JM, Hafez K, et al. Clinicopathological characterisation of renal cell carcinoma in young adults: a contemporary update and review of literature. Histopathology. 2020;76(6):875–87. Pu JL, Chen Z, Yao LQ et al. Long-term oncological prognosis after curative-intent liver resection for hepatocellular carcinoma in the young versus the elderly: multicentre propensity score-matching study. BJS Open. 2022;6(1). Pericleous M, Khan SA. Epidemiology of HPB malignancy in the elderly. Eur J Surg Oncol. 2021;47(3 Pt A):503–13. Kellokumpu I, Kairaluoma M, Mecklin JP, et al. Impact of Age and Comorbidity on Multimodal Management and Survival from Colorectal Cancer: A Population-Based Study. J Clin Med. 2021;10(8):1751. Akhavan A, Richards M, Shnorhavorian M, Goldin A, Gow K, Merguerian PA. Renal cell carcinoma in children, adolescents and young adults: a National Cancer Database study. J Urol. 2015;193(4):1336–41. Bukavina L, Bensalah K, Bray F, et al. Epidemiology of Renal Cell Carcinoma: 2022 Update. Eur Urol. 2022;82(5):529–42. Choi E, Becker H, Jung H. Health-related quality of life in adolescents and young adults with and without cancer, using propensity score matching. J Cancer Surviv. 2023;17(2):279–89. Smith A, Fogarasi M, Lustberg MB, Nekhlyudov L. Perspectives of adolescent and young adult cancer survivors: review of community-based discussion boards. J Cancer Surviv. 2022;16(5):1079–89. Additional Declarations No competing interests reported. Supplementary Files TABLES1.docx AttachedfileVisualandVideoAbstractTemplates2021081721011.jpg 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-8299759","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":571275433,"identity":"7c136457-eb71-416d-bc30-18c22b044c85","order_by":0,"name":"Zhi-Wei Sun","email":"","orcid":"","institution":"Zhangjiagang Hospital affiliated to Soochow University","correspondingAuthor":false,"prefix":"","firstName":"Zhi-Wei","middleName":"","lastName":"Sun","suffix":""},{"id":571275434,"identity":"7800bace-e6c5-404a-a7f5-8e5dc88d8044","order_by":1,"name":"Dong-Liang Yang","email":"","orcid":"","institution":"Department of Cardiology, The Affiliated Hospital of Nantong University","correspondingAuthor":false,"prefix":"","firstName":"Dong-Liang","middleName":"","lastName":"Yang","suffix":""},{"id":571275435,"identity":"843eba0d-506e-4ef3-b559-ca6417d1a988","order_by":2,"name":"Wei-Wei Lu","email":"","orcid":"","institution":"Department of Cardiology, The Affiliated Hospital of Nantong University","correspondingAuthor":false,"prefix":"","firstName":"Wei-Wei","middleName":"","lastName":"Lu","suffix":""},{"id":571275437,"identity":"d475855a-28ec-4874-914e-631740624c80","order_by":3,"name":"Jia-Wei Lu","email":"","orcid":"","institution":"Zhangjiagang Hospital affiliated to Soochow University","correspondingAuthor":false,"prefix":"","firstName":"Jia-Wei","middleName":"","lastName":"Lu","suffix":""},{"id":571275438,"identity":"570e2339-e91c-46ec-b2e4-4151ae8fd8c9","order_by":4,"name":"Li Xu","email":"","orcid":"","institution":"Zhangjiagang Hospital affiliated to Soochow University","correspondingAuthor":false,"prefix":"","firstName":"Li","middleName":"","lastName":"Xu","suffix":""},{"id":571275439,"identity":"b288d884-5c29-4e26-bbea-13734ec18ab9","order_by":5,"name":"Zhi-Xiang Gao","email":"","orcid":"","institution":"Zhangjiagang Hospital affiliated to Soochow University","correspondingAuthor":false,"prefix":"","firstName":"Zhi-Xiang","middleName":"","lastName":"Gao","suffix":""},{"id":571275440,"identity":"ff081461-9569-406d-a523-1a4a8b2ad1b3","order_by":6,"name":"Bing-Ye Zhu","email":"","orcid":"","institution":"Department of Urology, Affiliated Nantong Hospital of Shanghai University","correspondingAuthor":false,"prefix":"","firstName":"Bing-Ye","middleName":"","lastName":"Zhu","suffix":""},{"id":571275447,"identity":"e86c88c9-9fe2-4a12-999d-1ad777e50433","order_by":7,"name":"Zhi-Ran Li","email":"","orcid":"","institution":"Department of Andrology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School","correspondingAuthor":false,"prefix":"","firstName":"Zhi-Ran","middleName":"","lastName":"Li","suffix":""},{"id":571275449,"identity":"bb580f6b-6bf4-4c8f-af63-fe42868964b9","order_by":8,"name":"You Wu","email":"","orcid":"","institution":"Department of Urology, Affiliated Hospital of Nantong University, China","correspondingAuthor":false,"prefix":"","firstName":"You","middleName":"","lastName":"Wu","suffix":""},{"id":571275452,"identity":"ce173512-b9f2-4afa-844b-1e4999f9ed46","order_by":9,"name":"Hong-Xing Gu","email":"","orcid":"","institution":"Zhangjiagang Hospital affiliated to Soochow University","correspondingAuthor":false,"prefix":"","firstName":"Hong-Xing","middleName":"","lastName":"Gu","suffix":""},{"id":571275454,"identity":"31442267-b406-4a21-b77c-ff1ec80a7cca","order_by":10,"name":"Zi-Chao Xiu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABFElEQVRIie3RsWrDMBCA4TMCd1HwVmQC6hMUFAymQ0lexSLgLKEUunjooEmTHyCloS9R8HxBkCyGrC3J4BLI7K1LGyqTqRAbsmXQP4r7OCQBuFwXGjJx4MHN+ruuMzyeVN3Cw7sMo3AGsTcrEWhDkm5CMCtRig+ISU8fCXQRsTYVfuptAhuVVr23LR9dmy+7Zchv1WkSqqVYvOj9gzfHlQiLfUT7qbBkHMV4mgReDibU5ImAVGxQGJn3k4agLFqITyiYX02khjEwOW/IpO4kgU/tI5d2kqU+W6iGTLu3hLkvkGVpxGhJBmppIrqZPmIi2u9iX2xXM3HPR6vc2/08G371Onm3fzrkbaQtcd64y+Vyuf73B7naazBNVyjrAAAAAElFTkSuQmCC","orcid":"","institution":"Department of Urology, The Second Hospital, Cheeloo College of Medicine, Shandong University","correspondingAuthor":true,"prefix":"","firstName":"Zi-Chao","middleName":"","lastName":"Xiu","suffix":""}],"badges":[],"createdAt":"2025-12-07 12:38:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8299759/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8299759/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":100017378,"identity":"a890937e-3d63-4d80-894f-f4e3a865636f","added_by":"auto","created_at":"2026-01-12 07:10:24","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":311717,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscript.docx","url":"https://assets-eu.researchsquare.com/files/rs-8299759/v1/d090738ad8eb51d6ef6d7677.docx"},{"id":100361925,"identity":"e8e1f91f-1322-4558-a41d-9b1327761f67","added_by":"auto","created_at":"2026-01-16 07:45:57","extension":"jpg","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":129225,"visible":true,"origin":"","legend":"","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8299759/v1/bf0a9279e5f1625ddadb8673.jpg"},{"id":100017376,"identity":"5c3db78a-b284-4368-8753-a46a013ecd14","added_by":"auto","created_at":"2026-01-12 07:10:24","extension":"jpg","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":51299,"visible":true,"origin":"","legend":"","description":"","filename":"Figure2A.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8299759/v1/d0ed80880a5261d84f2540f7.jpg"},{"id":100361674,"identity":"08445829-81d8-44b6-890a-0f89a6213124","added_by":"auto","created_at":"2026-01-16 07:45:29","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":20096,"visible":true,"origin":"","legend":"","description":"","filename":"TABLE1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8299759/v1/8faf7284c3bcc9cf63603ccd.docx"},{"id":100362046,"identity":"8b5de473-fe04-4a68-8569-bdc27742fc3d","added_by":"auto","created_at":"2026-01-16 07:46:07","extension":"jpg","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":50323,"visible":true,"origin":"","legend":"","description":"","filename":"Figure2B.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8299759/v1/ca9092e2f1301720dd46a997.jpg"},{"id":100361904,"identity":"19228648-4d7f-4e38-9ed7-14227f47c9fd","added_by":"auto","created_at":"2026-01-16 07:45:55","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":17102,"visible":true,"origin":"","legend":"","description":"","filename":"TABLE2.docx","url":"https://assets-eu.researchsquare.com/files/rs-8299759/v1/5bb2b69087873538fe5e69f1.docx"},{"id":100361700,"identity":"626e3c0a-7ecb-49b0-8e60-9466ae59fccf","added_by":"auto","created_at":"2026-01-16 07:45:31","extension":"jpg","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":52687,"visible":true,"origin":"","legend":"","description":"","filename":"Figure2C.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8299759/v1/69e718e8eddb0fc0fd854031.jpg"},{"id":100017383,"identity":"c1748fd6-bc6f-434f-92f3-d32b9247c502","added_by":"auto","created_at":"2026-01-12 07:10:25","extension":"docx","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":19081,"visible":true,"origin":"","legend":"","description":"","filename":"TABLE3.docx","url":"https://assets-eu.researchsquare.com/files/rs-8299759/v1/315adb818fc88f35dc4dbf9c.docx"},{"id":100017390,"identity":"bf2faa17-f1d3-49ee-9b70-1ca479e7488c","added_by":"auto","created_at":"2026-01-12 07:10:25","extension":"docx","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":19043,"visible":true,"origin":"","legend":"","description":"","filename":"TABLE4.docx","url":"https://assets-eu.researchsquare.com/files/rs-8299759/v1/768a1fa3154dc74d2ce7ff9d.docx"},{"id":100362161,"identity":"0d82def1-bb55-469d-bff9-d7854c9cab31","added_by":"auto","created_at":"2026-01-16 07:46:15","extension":"docx","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":17638,"visible":true,"origin":"","legend":"","description":"","filename":"TABLES1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8299759/v1/b50cf0d24adf0beb52313719.docx"},{"id":100017393,"identity":"6fd6c504-f637-49d8-b9da-f8d0b862a7aa","added_by":"auto","created_at":"2026-01-12 07:10:25","extension":"json","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":11462,"visible":true,"origin":"","legend":"","description":"","filename":"1470ee15c3f3401ca58bdfb2f28e99b0.json","url":"https://assets-eu.researchsquare.com/files/rs-8299759/v1/69812e364704b688d58677f5.json"},{"id":100362277,"identity":"c1ec1c2e-4d98-47f6-9141-2672a029dc7c","added_by":"auto","created_at":"2026-01-16 07:46:28","extension":"jpg","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":423303,"visible":true,"origin":"","legend":"","description":"","filename":"AttachedfileVisualandVideoAbstractTemplates2021081721011.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8299759/v1/5a2c8af92ed0b7f435116762.jpg"},{"id":100362657,"identity":"50a1f8a4-591f-43df-9c95-e14f9e89c027","added_by":"auto","created_at":"2026-01-16 07:47:50","extension":"docx","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":15664,"visible":true,"origin":"","legend":"","description":"","filename":"CoverLetterd1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8299759/v1/74581022523aa332781cf995.docx"},{"id":100017409,"identity":"48b86ee0-2751-4e21-b08d-0326fbac4955","added_by":"auto","created_at":"2026-01-12 07:10:26","extension":"xml","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":168768,"visible":true,"origin":"","legend":"","description":"","filename":"1470ee15c3f3401ca58bdfb2f28e99b01enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-8299759/v1/eae462f21c90782a87286666.xml"},{"id":100362759,"identity":"7964a700-eaec-4b13-9f33-b17c8294ef09","added_by":"auto","created_at":"2026-01-16 07:48:02","extension":"jpg","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":129225,"visible":true,"origin":"","legend":"","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8299759/v1/9503f6d36e2b0746d04e623c.jpg"},{"id":100017398,"identity":"f8daf814-b59f-46cc-b782-7c49870ad46a","added_by":"auto","created_at":"2026-01-12 07:10:25","extension":"jpg","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":51299,"visible":true,"origin":"","legend":"","description":"","filename":"Figure2A.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8299759/v1/9f1818304237753d3839d4c6.jpg"},{"id":100362916,"identity":"c90d6c66-213c-47ba-84fc-1fe0c5dd1286","added_by":"auto","created_at":"2026-01-16 07:48:16","extension":"jpg","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":50323,"visible":true,"origin":"","legend":"","description":"","filename":"Figure2B.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8299759/v1/5dbc6cc78cd1e2bcf98e0ece.jpg"},{"id":100361760,"identity":"9a19f82b-0a49-4654-8189-7815c1e793bd","added_by":"auto","created_at":"2026-01-16 07:45:41","extension":"jpg","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":52687,"visible":true,"origin":"","legend":"","description":"","filename":"Figure2C.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8299759/v1/f74b234c3286199743f8f791.jpg"},{"id":100362484,"identity":"5c591396-8b67-4c49-8d8d-49cfb812520c","added_by":"auto","created_at":"2026-01-16 07:46:51","extension":"jpeg","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":129225,"visible":true,"origin":"","legend":"","description":"","filename":"Figure1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8299759/v1/efc8d78fade2e783d1c31ff8.jpeg"},{"id":100362482,"identity":"babe75dd-c820-432b-951c-01701a670cd9","added_by":"auto","created_at":"2026-01-16 07:46:51","extension":"jpeg","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":51299,"visible":true,"origin":"","legend":"","description":"","filename":"Figure2A.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8299759/v1/6494bab690327bf631b3d274.jpeg"},{"id":100017401,"identity":"8421135d-f495-4ff8-bb13-2c35e4a46c18","added_by":"auto","created_at":"2026-01-12 07:10:25","extension":"jpeg","order_by":20,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":50323,"visible":true,"origin":"","legend":"","description":"","filename":"Figure2B.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8299759/v1/4320fa425f9f8b34a9bc9864.jpeg"},{"id":100361986,"identity":"49a1ddcf-2f59-43a9-95ab-1ff7dc898cf5","added_by":"auto","created_at":"2026-01-16 07:46:01","extension":"jpeg","order_by":21,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":52687,"visible":true,"origin":"","legend":"","description":"","filename":"Figure2C.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8299759/v1/0cf3a7d625d4997d805727a2.jpeg"},{"id":100361665,"identity":"9a7035cd-44aa-409b-af10-a22423b4d9ac","added_by":"auto","created_at":"2026-01-16 07:45:29","extension":"png","order_by":22,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":38039,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure1.png","url":"https://assets-eu.researchsquare.com/files/rs-8299759/v1/95f5c1d3705fdc0c4b3817a8.png"},{"id":100017404,"identity":"267becdf-1d96-4f81-b00c-7c580dfd57da","added_by":"auto","created_at":"2026-01-12 07:10:25","extension":"png","order_by":23,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":16537,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure2A.png","url":"https://assets-eu.researchsquare.com/files/rs-8299759/v1/ba6de483c03ab1eb33d334ff.png"},{"id":100017395,"identity":"aa1c855b-8ac7-4dae-bcf1-d2c69d72f360","added_by":"auto","created_at":"2026-01-12 07:10:25","extension":"png","order_by":24,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":16093,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure2B.png","url":"https://assets-eu.researchsquare.com/files/rs-8299759/v1/ef28ec9b6857150940e73f28.png"},{"id":100017400,"identity":"fec4d8f5-767e-4f86-bdc9-d768016ab889","added_by":"auto","created_at":"2026-01-12 07:10:25","extension":"png","order_by":25,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":17173,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure2C.png","url":"https://assets-eu.researchsquare.com/files/rs-8299759/v1/86736e185ec0f980861bdfd2.png"},{"id":100017399,"identity":"2d3b3e1f-cfd0-4054-bf4e-6a9265217b7b","added_by":"auto","created_at":"2026-01-12 07:10:25","extension":"png","order_by":26,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":38039,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure1.png","url":"https://assets-eu.researchsquare.com/files/rs-8299759/v1/5346620a668f00be96cd389f.png"},{"id":100361959,"identity":"94c1d6c5-1d6e-4691-89c1-d2583e20c059","added_by":"auto","created_at":"2026-01-16 07:45:58","extension":"png","order_by":27,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":16537,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure2A.png","url":"https://assets-eu.researchsquare.com/files/rs-8299759/v1/48f9512e4dca5f3af1be50d2.png"},{"id":100017403,"identity":"acb3e88e-a54f-477a-8be1-7d62109ac6f3","added_by":"auto","created_at":"2026-01-12 07:10:25","extension":"png","order_by":28,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":16093,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure2B.png","url":"https://assets-eu.researchsquare.com/files/rs-8299759/v1/c876225f62461aa611676887.png"},{"id":100017408,"identity":"ad2b408e-74a6-484a-b48a-734f9ef97567","added_by":"auto","created_at":"2026-01-12 07:10:26","extension":"png","order_by":29,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":17173,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure2C.png","url":"https://assets-eu.researchsquare.com/files/rs-8299759/v1/0b5ed900a11e4c0395870f5f.png"},{"id":100362491,"identity":"df46d708-62ff-4c46-8a83-4af3d9d6348a","added_by":"auto","created_at":"2026-01-16 07:46:53","extension":"xml","order_by":30,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":170392,"visible":true,"origin":"","legend":"","description":"","filename":"1470ee15c3f3401ca58bdfb2f28e99b01structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8299759/v1/2f23e61e95d34f41fa37ea0e.xml"},{"id":100017405,"identity":"3161146b-6858-4802-8b48-1bc54fc9867b","added_by":"auto","created_at":"2026-01-12 07:10:26","extension":"html","order_by":31,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":183678,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8299759/v1/9429c5cf62dc9fedda175a5d.html"},{"id":100017373,"identity":"bff9efcc-0a9c-4804-bbdd-18040e7374f5","added_by":"auto","created_at":"2026-01-12 07:10:24","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":129225,"visible":true,"origin":"","legend":"\u003cp\u003eSelection of the study population\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8299759/v1/c66b0f78d60c74270f9c1ff9.jpg"},{"id":100017374,"identity":"b384dcce-fce3-4b07-9e29-b6ac21dcc749","added_by":"auto","created_at":"2026-01-12 07:10:24","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":187789,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan–Meier curves comparing the young and the elderly in the propensity score-matched cohort (\u003cstrong\u003e2A\u003c/strong\u003e Cumulative incidence of overall survival; \u003cem\u003eP\u003c/em\u003e= 0.038; \u003cstrong\u003e2B\u003c/strong\u003e Cancer-specific survival; \u003cem\u003eP\u003c/em\u003e = 0.019;\u003cstrong\u003e 2C\u003c/strong\u003e Cumulative recurrence; \u003cem\u003eP\u003c/em\u003e = 0.003.)\u003c/p\u003e","description":"","filename":"Figure2A.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8299759/v1/d11f750babaffafaff1b3b19.jpg"},{"id":107524587,"identity":"68107759-7799-4b3c-bca1-a3a3130178a9","added_by":"auto","created_at":"2026-04-22 09:29:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":999239,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8299759/v1/718dc556-1052-4d52-8cf9-0b484462c035.pdf"},{"id":100362403,"identity":"c678145d-982d-4066-a5f9-ffa1f1e2685d","added_by":"auto","created_at":"2026-01-16 07:46:42","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":16276,"visible":true,"origin":"","legend":"","description":"","filename":"TABLES1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8299759/v1/cb47d6838fc7e81e0fe01380.docx"},{"id":100361643,"identity":"4613aa2b-7599-4189-bc65-daaf055b55b6","added_by":"auto","created_at":"2026-01-16 07:45:26","extension":"jpg","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":423303,"visible":true,"origin":"","legend":"","description":"","filename":"AttachedfileVisualandVideoAbstractTemplates2021081721011.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8299759/v1/66759f56a8f0dd004be2c13c.jpg"}],"financialInterests":"No competing interests reported.","formattedTitle":"Evaluating the Role of Age in Post-Nephrectomy Outcomes for Patients with Early-Stage Renal Cell Carcinoma: A Retrospective Multi-Centre Cohort Study","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eRenal cell carcinoma (RCC) represents a significant global health burden, ranking as the 16th most common cancer worldwide\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. According to GLOBOCAN 2020, there were approximately 431,288 new cases and 179,368 deaths attributed to kidney cancer globally in 2020\u003csup\u003e2\u003c/sup\u003e. The incidence of RCC increases with age, with about 50% of cases occurring in individuals aged 65 years and older\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Curative nephrectomy remains the gold standard curative treatment for RCC, especially for early-stage and unifocal tumors\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. The overall prognosis for patients undergoing this procedure is generally favorable, with some studies reporting 5-year recurrence-free survival rates exceeding 80%\u003csup\u003e7\u003c/sup\u003e. However, a concerning trend has emerged: the rising incidence of RCC among younger populations, with rates in individuals aged 20\u0026ndash;39 years increasing from 0.9 per 100,000 in 1975 to 1.6 per 100,000 in 2015\u003csup\u003e8,9\u003c/sup\u003e. Influenced by evolving lifestyle factors and environmental exposures, there is a discernible demographic shift towards younger populations affected by sporadic renal neoplasms. This trend underscores the necessity for a more nuanced approach to long-term prognostication and therapeutic management in young adults, where biopsy and active surveillance are less frequently implemented compared with their older counterparts\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eNumerous studies have revealed that age difference at cancer diagnosis was significantly correlated with long-term postoperative outcomes in a spectrum of malignancies, encompassing gastric adenocarcinoma, breast neoplasms, and colorectal carcinomas\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. While increased age has traditionally been associated with higher surgical risks and postoperative complications, emerging evidence across various malignancies suggests that younger patients may present with more aggressive tumor characteristics and worse overall survival following curative resection\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Age at diagnosis has long been recognized as a critical factor influencing cancer outcomes, but its impact on RCC prognosis remains a subject of debate\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn the context of RCC, the impact of age on outcomes remains controversial. Some studies have reported better outcomes for younger patients, with one analysis showing a 5-year relative survival rate of 85.7% for patients aged 20\u0026ndash;39 years compared to 74.1% for those over 60\u003csup\u003e18,19\u003c/sup\u003e. Conversely, other research indicates that younger patients may present with higher-grade and more advanced-stage tumors, as well as a higher proportion of rare non-clear cell subtypes associated with poorer prognoses\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. The discrepancies in these findings can be attributed to several factors. Firstly, the definition of \"young\" and \"elderly\" varies across studies, with different age cut-offs used for categorization. Secondly, the higher proportion of non-cancer-specific deaths among elderly patients may skew overall survival analyses, suggesting that cancer-specific survival might be a more appropriate measure of oncological outcomes\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Additionally, many existing studies are single-center with relatively small sample sizes, potentially limiting the generalizability of their findings.\u003c/p\u003e \u003cp\u003eTo address these limitations and provide a more comprehensive understanding of age-related prognostic differences in RCC, we conducted a single-center study comparing long-term overall survival, cancer-specific survival, and recurrence rates between young (\u0026lt;\u0026thinsp;40 years) and elderly (\u0026ge;\u0026thinsp;75 years) patients undergoing curative-intent nephrectomy for RCC. Propensity score matching (PSM) was employed to balance baseline characteristics between the two groups, aiming to offer insights that could inform personalized treatment strategies and follow-up protocols for RCC patients across different age groups.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Patient Population\u003c/h2\u003e \u003cp\u003eData from a multicenter database were obtained after obtaining approval from 5 institutions\u0026rsquo; review boards, as well as informed consent for the use of data for research purposes from all patients on admission or before their Operation. We identified 1644 patients who underwent curative nephrectomy for early-stage (T1-T2) solitary RCC between January 2008.06 and December 2023.06. To account for therapeutic advances, patients were stratified into pre-immunotherapy (pre-IO: year 2008\u0026ndash;2015) and post-immunotherapy (post-IO: year 2016\u0026ndash;2023) eras based on the landmark approval of immune checkpoint inhibitors for RCC in 2015. All patients were pathologically confirmed to have RCC postoperatively. The diagnosis of RCC was confirmed on postoperative histopathological examination. Histologic subtype was categorized according to WHO 2022 classification, including clear cell RCC (ccRCC), papillary, chromophobe, and unclassified RCC.\u003c/p\u003e \u003cp\u003eExclusion criteria were as follows: age\u0026thinsp;\u0026lt;\u0026thinsp;18 years old; history of chronic hepatic or renal insufficiency; Palliative surgery; concomitant malignancy or prior anti-tumor therapy; perioperative 90-day mortality; severe postoperative complications prolonging hospital stay; missing important clinical data; and loss to follow-up within 1 year after surgery. After applying these criteria, 357 patients were included in the final analysis cohort. The study was conducted in accordance with the Declaration of Helsinki. Informed consent was waived due to the retrospective nature of the study by the Institutional Review Board of Zhangjiagang Hospital affiliated to Soochow University (ZJGYYLL-2023-11-lw002).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eClinical Characteristics\u003c/h3\u003e\n\u003cp\u003ePatient clinical characteristics included age, sex, body mass index (BMI), co-morbidities, American Society of Anesthesiologists (ASA) score, long-term smoking, chronic alcohol exposure, abnormal blood parameters, surgical approach, maximum tumor diameter, microvascular invasion, satellite nodules, International Society of Urological Pathology (ISUP) grade, and regular surveillance. Curative nephrectomy includes radical nephrectomy and nephron-sparing surgery. Co-morbidities comprised hypertension, diabetes mellitus, chronic obstructive pulmonary disease and cardiovascular diseases. Abnormal blood parameters were defined as the presence of three or more of the following: leukocytosis (\u0026gt;\u0026thinsp;10\u0026times;10^9/L), anemia (hemoglobin\u0026thinsp;\u0026lt;\u0026thinsp;90 g/L), thrombocytosis or thrombocytopenia (platelet count\u0026thinsp;\u0026lt;\u0026thinsp;100\u0026times;10^9/L or \u0026gt;\u0026thinsp;450\u0026times;10^9/L), elevated C-reactive protein (\u0026gt;\u0026thinsp;10 mg/L), abnormal serum calcium levels (\u0026lt;\u0026thinsp;2.20 mmol/L or \u0026gt;\u0026thinsp;2.75 mmol/L), and prolonged coagulation time (\u0026gt;\u0026thinsp;16 seconds).\u003c/p\u003e\n\u003ch3\u003eStudy Endpoints and Propensity Score Matching\u003c/h3\u003e\n\u003cp\u003eThis study focused on three primary outcomes: overall survival (OS), cancer-specific survival (CSS), and time-to-recurrence (TTR). OS was defined as the interval between the date of nephrectomy and either death from any cause or the last documented follow-up for those still alive. CSS was measured from the time of surgery until death attributed to RCC, with patients who died from other causes or remained alive at last contact considered as censored observations. TTR was the time from surgical intervention to the first detected recurrence, with those who died without documented recurrence or remained recurrence-free at last follow-up treated as censored cases.\u003c/p\u003e \u003cp\u003eTo balance differences in baseline characteristics between young (\u0026lt;\u0026thinsp;40 years) and elderly (\u0026ge;\u0026thinsp;75 years) patients, propensity score matching (PSM) was performed using a 1:1 nearest neighbor matching algorithm without replacement and a caliper width of 0.1 standard deviations of the logit of the propensity score. Variables included in the PSM model were sex, BMI, smoking status, alcohol consumption, abnormal blood parameters, surgical approach, maximum tumor diameter, microvascular invasion, satellite nodules, ISUP grade, and Irregular Surveillance. As ASA score and co-morbidities are intrinsic variables known to be related to age, these were not matched in the PSM model.\u003c/p\u003e\n\u003ch3\u003eFollow-up Protocol\u003c/h3\u003e\n \u003cp\u003eFollowing hospital discharge, a unified post-operative surveillance strategy was implemented across all participating medical centers to monitor potential cancer recurrence. This standardized approach ensured consistency in patient follow-up procedures throughout the multi-institutional study. Postoperative follow-up included the first evaluation at 1 month after surgery, followed by regular check-ups every 2\u0026ndash;3 months for the first 2 years, then every 6 months thereafter. Each surveillance visit included physical examination, laboratory tests, and abdominal ultrasonography and/or enhanced computed tomography (CT) or magnetic resonance imaging (MRI). Irregular surveillance was defined as any deviation from the prescribed follow-up schedule, which included follow-up intervals exceeding the recommended timeframes, missed appointments, or cases where recurrences were detected through symptomatic presentation or incidental findings rather than scheduled screenings.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eContinuous variables were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation or median (interquartile range) and compared using Student's t-test or Mann-Whitney U test as appropriate. Categorical variables were expressed as numbers (percentages) and compared using chi-square test or Fisher's exact test. Survival curves were generated using the Kaplan-Meier method and compared with the log-rank test. Univariable and multivariable Cox proportional hazards regression models were used to identify independent prognostic factors for OS, CSS, and recurrence. Variables with P\u0026thinsp;\u0026lt;\u0026thinsp;0.1 in univariable analysis were included in the multivariable model. Hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated. Treatment era (post-IO vs pre-IO) was included as a covariate in Cox regression models. Survival outcomes between pre-IO and post-IO groups were compared using Kaplan-Meier analysis. All statistical analyses were performed using SPSS version 26.0 (IBM Corp., Armonk, NY, USA). Two-sided P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003ePatient Characteristics and Baseline Comparisons\u003c/h2\u003e \u003cp\u003eFollowing the application of inclusion and exclusion criteria, our study encompassed 357 patients who underwent curative nephrectomy for early-stage RCC \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. The cohort comprised 234 young patients (65.5%) with a median age of 33.6 years (range: 18\u0026ndash;39 years) and 123 elderly patients (34.5%) with a median age of 78.9 years (range: 75\u0026ndash;93 years). PSM yielded 96 pairs of young and elderly patients. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e summarizes the clinical and operative characteristics of both groups before and after PSM. In the matched cohort, young and elderly patients showed no significant differences in tumor features and surgical variables, except for the prevalence of comorbidities (6.3% vs 34.4%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and ASA score\u0026thinsp;\u0026ge;\u0026thinsp;3 (4.2% vs 49.0%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and larger tumor size (61.5% vs 45.8%, P\u0026thinsp;=\u0026thinsp;0.030). Histologic subtype distribution did not differ between matched young and elderly groups (ccRCC 79.2% vs 84.4%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.350).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparisons of patients\u0026rsquo; clinical characteristics and operative variables between the young and the elderly before and after propensity score matching.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e Variables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eThe entire cohort\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eThe PSM cohort\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe Young\u003c/p\u003e \u003cp\u003e(\u0026lt;\u0026thinsp;40 years old)\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;234)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThe Elderly\u003c/p\u003e \u003cp\u003e(\u0026ge;\u0026thinsp;75 years old)\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;123)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eThe Young\u003c/p\u003e \u003cp\u003e(\u0026lt;\u0026thinsp;40 years old)\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;96)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eThe Elderly\u003c/p\u003e \u003cp\u003e(\u0026ge;\u0026thinsp;75 years old)\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;96)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, years*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e33.6 (4.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e78.9 (3.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e34.2 (4.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e79.1 (4.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.673\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale sex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e205 (87.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e99 (80.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e84 (87.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e82 (85.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.190\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u0026thinsp;\u0026ge;\u0026thinsp;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e64 (27.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e59 (48.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e45 (46.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e40 (41.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.468\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCo-morbidities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8 (3.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43 (35.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6 (6.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e33 (34.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eASA score\u0026thinsp;\u0026ge;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9 (3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e57 (46.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4 (4.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e47 (49.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLong-term smoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29 (12.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37 (30.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24 (25.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e26 (27.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.742\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic alcohol exposure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e44 (18.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e51 (41.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e35 (36.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e31 (32.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.543\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbnormal blood parameters\u0026thinsp;\u0026ge;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11 (4.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19 (15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9 (9.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11 (11.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.637\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLaparoscopic approach\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e119 (50.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46 (37.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e37 (38.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e39 (40.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.768\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLargest tumor size\u0026thinsp;\u0026ge;\u0026thinsp;4cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e118 (50.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e54 (43.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.241\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e59 (61.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e44 (45.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.030\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClear cell RCC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e186 (79.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e102 (82.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.434\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e76 (79.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e81 (84.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.350\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMicroscopic Vascular Invasion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e47 (20.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30 (24.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.347\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e22 (22.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e23 (24.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.865\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSatellite nodules\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e48 (20.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15 (12.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e22 (22.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e15 (15.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.200\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eISUP grade\u0026thinsp;\u0026ge;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e69 (29.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31 (25.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.392\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26 (27.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e23 (24.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.619\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIrregular Surveillance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e72 (30.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25 (20.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e23 (24.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e23 (24.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.999\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e* Values are mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation. RCC, Renal Cell Carcinoma.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eASA, American Society of Anesthesiologists; BMI, body mass index; CI, confidence interval; ISUP, International Society of Urological Pathology; PSM, propensity score matching.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eLong-term Oncological Outcomes\u003c/h3\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents a comparison of long-term oncological outcomes between young and elderly groups before and after PSM. The overall recurrence rate was significantly higher in the young group both before (32.9% vs 17.1%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and after PSM (34.4% vs 16.7%, P\u0026thinsp;=\u0026thinsp;0.005). During the follow-up period, overall mortality rates were comparable between groups before PSM (39.3% vs 29.3%, P\u0026thinsp;=\u0026thinsp;0.060), but the young group exhibited higher mortality after PSM (46.9% vs 29.2%, P\u0026thinsp;=\u0026thinsp;0.011). Cancer-specific mortality rates were consistently higher in the young group both before (17.5% vs 8.0%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and after PSM (17.7% vs 7.3%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01). In the entire cohort (N\u0026thinsp;=\u0026thinsp;357), pre-IO (n\u0026thinsp;=\u0026thinsp;156) and post-IO (n\u0026thinsp;=\u0026thinsp;201) groups demonstrated comparable 5-year oncologic outcomes (OS: 80.1% vs 87.6%, P\u0026thinsp;=\u0026thinsp;0.057; CSS: 89.7% vs 90.5%, P\u0026thinsp;=\u0026thinsp;0.138; and recurrence rates: 26.3% vs 17.9%, P\u0026thinsp;=\u0026thinsp;0.126) (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparisons of long-term oncological outcomes between the young and the elderly before and after propensity score matching\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eEntire cohort\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003ePSM cohort\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe Young\u003c/p\u003e \u003cp\u003e(\u0026lt;\u0026thinsp;40 years old)\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;234)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThe Elderly\u003c/p\u003e \u003cp\u003e(\u0026ge;\u0026thinsp;75years old)\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;123)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eThe Young\u003c/p\u003e \u003cp\u003e(\u0026lt;\u0026thinsp;40 years old)\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;96)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eThe Elderly\u003c/p\u003e \u003cp\u003e(\u0026ge;\u0026thinsp;75 years old)\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;96)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePeriod of follow-up, months*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71.8 (3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70.9 (2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.362\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e71.0 (5.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e69.6 (2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.370\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRecurrence during the follow-up\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77 (32.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (17.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33 (34.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16 (16.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDeath during the follow-up\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e92 (39.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36 (29.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.060\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45 (46.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28 (29.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCancer-specific death\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41 (17.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (8.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17 (17.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7 (7.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian overall survival, months, 95% CI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e89.5 (76.5, 102.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93.6 (77.5, 109.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.195\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e77.8 (71.8, 83.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e93.6 (76.1, 111.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1-year overall survival rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e97.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e98.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e96.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e97.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3-year overall survival rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e90.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e91.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e85.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e92.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5-year overall survival rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e83.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e86.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e76.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e86.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian cancer-specific survival, months, 95% CI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1-year cancer-specific survival rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e98.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e99.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e97.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e98.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3-year cancer-specific survival rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e93.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e91.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5-year cancer-specific survival rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e86.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e93.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian time to recurrence, months, 95% CI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1-year cumulative recurrence rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3-year cumulative recurrence rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5-year cumulative recurrence rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e*Values are median\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eCI, confidence interval; PSM, propensity score matching\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFigures \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA-C illustrate the comparisons of OS, CSS, and cumulative recurrence rates between young and elderly patients in the matched cohort. After PSM, the 5-year OS rate was significantly lower in the young group (76.0% vs 86.5%, P\u0026thinsp;=\u0026thinsp;0.038). Similarly, the 5-year CSS rate was inferior in the young group (86.5% vs 93.8%, P\u0026thinsp;=\u0026thinsp;0.019). The 5-year cumulative recurrence rate remained higher in the young group both before (25.2% vs 13.8%, P\u0026thinsp;=\u0026thinsp;0.003) and after PSM (28.1% vs 13.5%, P\u0026thinsp;=\u0026thinsp;0.003).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eUnivariable and Multivariable Analyses\u003c/h2\u003e \u003cp\u003eTables\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e present the results of univariable and multivariable Cox regression analyses for predicting OS and time-to-recurrence in the PSM cohort, respectively. Factors associated with poor OS after surgery included young age, long-term smoking history, preoperative abnormal blood parameters (\u0026ge;\u0026thinsp;3), larger tumor diameter (\u0026ge;\u0026thinsp;4cm), presence of microvascular invasion, poor ISUP grade, and irregular surveillance. Risk factors for recurrence encompassed young age, preoperative abnormal blood parameters (\u0026ge;\u0026thinsp;3), larger tumor diameter (\u0026ge;\u0026thinsp;4cm), microvascular invasion, presence of satellite nodules, and poor ISUP grade. Compared to elderly patients, young individuals who underwent curative nephrectomy for RCC demonstrated independently and significantly lower survival rates (HR 2.407, 95% CI 1.387\u0026ndash;4.177; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002) and higher recurrence rates (HR 2.824, 95% CI 1.393\u0026ndash;5.722; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004) even after adjusting for histology (ccRCC vs. non-ccRCC), while histologic subtype itself was not prognostic (OS: \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.114; recurrence: \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.863). Meanwhile, treatment era (post-IO vs pre-IO) was not a significant predictor for OS (HR 1.142, 95% CI 0.717\u0026ndash;1.817; P\u0026thinsp;=\u0026thinsp;0.577) or recurrence (HR 1.047, 95% CI 0.596\u0026ndash;1.840; P\u0026thinsp;=\u0026thinsp;0.872) in the PSM cohort (Tables\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e \u0026amp; \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariable and multivariable Cox regression analyses predicting overall survival after curative-intent nephrectomy for renal cell carcinoma after propensity score matching\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUV HR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUV \u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMV HR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMV \u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe Young\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.658 (1.022, 2.690)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.407 (1.387, 4.177)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale sex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.002 (0.512, 1.962)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.995\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u0026thinsp;\u0026ge;\u0026thinsp;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.317 (0.825, 2.103)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.248\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCo-morbidities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.358 (0.719, 2.564)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.345\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eASA score\u0026thinsp;\u0026ge;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.718 (0.398, 1.295)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.271\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLong-term smoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.162 (1.834, 5.450)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.531 (1.719, 7.265)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic alcohol exposure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.713 (0.427, 1.191)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.197\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbnormal blood parameters\u0026thinsp;\u0026ge;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.335 (3.991, 17.406)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.927 (1.134, 7.559)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLaparoscopic approach\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.892 (0.552, 1.439)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.638\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClear cell RCC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.712 (0.927, 3.163)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.114\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLargest tumor size\u0026thinsp;\u0026ge;\u0026thinsp;4cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.395 (1.448, 3.963)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.212 (1.874, 5.506)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMicroscopic Vascular Invasion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.213 (1.348, 3.634)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.518 (1.427, 4.444)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSatellite nodules\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.525 (0.890, 2.615)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eISUP grade\u0026thinsp;\u0026ge;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.437 (2.126, 5.557)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.210 (1.309, 3.729)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIrregular Surveillance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.164 (1.875, 5.339)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.220 (1.257, 3.920)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePost-IO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.142 (0.717, 1.817)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.577\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eASA, American Society of Anesthesiologists; BMI, body mass index; CI, Confidence interval; HR, Hazard ratio; ISUP, International Society of Urological Pathology; MV, multivariable; RCC, Renal Cell Carcinoma; UV, univariable.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariable and multivariable Cox regression analyses predicting time-to-recurrence after curative-intent nephrectomy for renal cell carcinoma after propensity score matching\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUV HR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUV \u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMV HR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMV \u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe Young\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.407 (1.324, 4.378)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.824 (1.393, 5.722)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale sex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.184 (0.555, 2.525)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.663\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u0026thinsp;\u0026ge;\u0026thinsp;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.222 (0.697, 2.140)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.484\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCo-morbidities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.255 (0.624, 2.523)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.524\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eASA score\u0026thinsp;\u0026ge;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.598 (0.290, 1.233)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLong-term smoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.255 (1.217, 4.178)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.153 (0.939, 4.940)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.070\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic alcohol exposure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.586 (0.306, 1.124)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbnormal blood parameters\u0026thinsp;\u0026ge;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.051 (3.397, 14.634)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.433 (1.293, 9.114)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLaparoscopic approach\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.798 (0.443, 1.438)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.453\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClear cell RCC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.942 (0.480, 1.849)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.863\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLargest tumor size\u0026thinsp;\u0026ge;\u0026thinsp;4cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.445 (1.335, 4.481)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.009 (1.006, 4.010)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.048\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMicroscopic Vascular Invasion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.100 (2.337, 7.194)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.076 (1.612, 5.871)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSatellite nodules\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.725 (2.104, 6.592)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.960 (1.575, 5.563)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eISUP grade\u0026thinsp;\u0026ge;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.018 (3.382, 10.708)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.306 (1.753, 6.234)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIrregular Surveillance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.657 (0.925,2.967)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.089\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.652 (0.891, 3.062)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.111\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePost-IO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.047 (0.596, 1.840)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.872\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eASA, American Society of Anesthesiologists; BMI, body mass index; CI, Confidence interval; HR, Hazard ratio; ISUP, International Society of Urological Pathology; MV, multivariable; RCC, Renal Cell Carcinoma; UV, univariable.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis multicenter retrospective study compared the clinicopathological features and long-term oncological outcomes of young (\u0026lt;\u0026thinsp;40 years) and elderly (\u0026ge;\u0026thinsp;75 years) patients who underwent curative nephrectomy for RCC. Through PSM and multivariate Cox regression analysis, our results demonstrated that younger patients had significantly lower OS, CSS rates, and higher recurrence rates compared to elderly patients after nephrectomy for RCC. These findings have important implications for postoperative monitoring, follow-up, and anti-recurrence treatment strategies, especially for young RCC patients.\u003c/p\u003e \u003cp\u003eTo some extent, our findings may challenge the traditional notion that younger patients generally have a better prognosis. While some previous studies have reported better outcomes for young RCC patients\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e, our results consistent with research on other malignancies such as hepatocellular carcinoma, gastric cancer, and breast cancer, which suggest that younger patients may have more aggressive tumor characteristics and poorer prognosis. In fact, the disparity in long-term survival outcomes may be attributed to the significantly higher proportion of non-cancer-specific deaths among elderly patients, who often have severe comorbidities and poorer general health conditions that pose potential life-threatening risks\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. This explains the notably lower proportion of cancer-specific deaths among elderly patients compared to their younger counterparts. Consequently, when considering the long-term oncological prognosis of elderly cancer patients, CSS rates may be more informative and clinically relevant than overall survival rates.\u003c/p\u003e \u003cp\u003eNotably, we observed that the 5-year cumulative recurrence rate was significantly higher in young patients compared to elderly patients (28.1% vs 13.5%, P\u0026thinsp;=\u0026thinsp;0.003). This difference may reflect the unique biological behavior of tumors in younger patients. Studies have shown that RCC in young patients may have distinct molecular characteristics, leading to higher invasiveness and metastatic potential\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Furthermore, the immune systems of younger patients may respond differently to the immune evasion mechanisms of RCC cells, potentially explaining the higher recurrence rates\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. These results suggest that young patients should be closely monitored for tumor recurrence even after radical surgery.\u003c/p\u003e \u003cp\u003eMultivariate analysis in our study revealed that young age is an independent risk factor for decreased overall survival (HR 2.28, 95% CI 1.314\u0026ndash;3.951, P\u0026thinsp;=\u0026thinsp;0.003) and increased recurrence rate (HR 2.82, 95% CI 1.393\u0026ndash;5.722, P\u0026thinsp;=\u0026thinsp;0.004). This underscores the importance of age in RCC prognosis and suggests the need for personalized treatment and follow-up strategies for different age groups. For instance, younger patients may require more frequent and intensive postoperative monitoring, as well as more aggressive adjuvant treatment regimens. Additionally, we found that long-term smoking history, preoperative abnormal blood parameters, larger tumor diameter, microscopic vascular invasion, and poor ISUP grade were significant factors affecting long-term prognosis in RCC patients. These findings are consistent with previous studies and emphasize the importance of these factors in RCC risk stratification and treatment decision-making\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Young individuals who smoke frequently or work in environments with secondhand smoke should reduce cigarette exposure and actively minimize exposure to risk factors in daily life\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. It is also worth noting that younger patients, often in better general health and busy with work, may neglect regular medical check-ups, potentially leading to delayed tumor discovery and more challenging treatment with relatively poorer prognosis. This could be the explanation for why young patients had significantly more\u0026thinsp;\u0026ge;\u0026thinsp;pT1b tumors than older patients (61.5% vs 45.8%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.030) after propensity matching in this study and this situation should also be given sufficient attention by young patients\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eA paradoxical finding emerged regarding non-cancer mortality: young patients experienced higher rates (28 events vs 21 in elderly) despite their general health advantage. Our analysis revealed starkly contrasting etiological patterns\u0026mdash;trauma accounted for 46.4% of young non-cancer deaths (including 7 traffic accidents and 6 suicides), while premature cardiovascular events represented 32.1% (primarily myocardial infarction/cardiac arrest). These findings suggest risk-taking behaviors and undiagnosed cardiometabolic comorbidities may underlie premature mortality in this population. Conversely, elderly non-cancer deaths predominantly reflected expected age-related decline (cardiovascular 71.4%, respiratory 19.0%). Importantly, this apparent mortality paradox may be partially explained by competing risk dynamics: elderly patients' elevated baseline mortality risk is attenuated by earlier cancer-specific deaths, thereby reducing observed non-cancer events. Crucially, cancer-specific mortality remained significantly elevated in young patients (17.7% vs 7.3%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), confirming their inherent biological vulnerability to disease progression independent of non-cancer mortality patterns. Furthermore, our era-stratified analysis revealed no significant survival differences between pre-IO and post-IO groups, suggesting that immunotherapy advancements\u0026mdash;while transformative for advanced RCC\u0026mdash;may have limited impact on outcomes in early-stage disease treated with curative nephrectomy. This aligns with current guidelines recommending adjuvant therapy primarily for high-risk localized RCC rather than early-stage cases.\u003c/p\u003e \u003cp\u003eOur study has several limitations. Firstly, as a retrospective study, selection bias may exist. Although PSM was used to reduce this bias, it cannot be completely eliminated. For instance, many young tumor patients may be more aggressive in treatment decision-making, particularly in surgical strategy, while in the elderly population, considerations of physical condition and underlying diseases may lead to more conservative treatment strategies or even abandonment of surgical treatment. This age-related treatment strategy bias objectively exists. Secondly, we did not obtain some important information that might affect prognosis, such as molecular marker data and detailed treatment information. Thirdly, although our follow-up time was relatively long, it may still be insufficient to fully assess the long-term prognosis of RCC, especially for younger patients. Fourth, while we addressed era effects through stratified analysis and Cox regression, the non-significant results (P\u0026thinsp;=\u0026thinsp;0.057\u0026ndash;0.872) should be interpreted cautiously given the cohort's focus on early-stage disease where systemic therapy utilization is inherently low.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThis study demonstrates that younger patients have a higher risk of recurrence and lower overall survival rates after curative nephrectomy compared to elderly patients. These findings highlight the importance of age as a prognostic factor in RCC and suggest the need for personalized treatment and follow-up strategies for different age groups, with particular attention and more aggressive follow-up and anti-recurrence prevention treatment strategies for young RCC patients. Future research should focus on the molecular characteristics of RCC in young patients and the development of novel treatment strategies for this population.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eASA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAmerican Society of Anesthesiologists\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBMI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ebody mass index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCSS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecancer specific survival\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecomputed tomography\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003econfidence interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ehazard ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eISUP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInternational Society of Urological Pathology\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMRI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emagnetic resonance imaging\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emultivariable\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eoverall survival\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePSM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003epropensity score matching\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRCC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRenal cell carcinoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eUV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eunivariable.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted in accordance with the Declaration of Helsinki. Informed consent was waived due to the retrospective nature of the study by the Institutional Review Board of Zhangjiagang Hospital affiliated to Soochow University (ZJGYYLL-2023-11-lw002)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors have read and approved the final manuscript, consented to its submission to Asian Journal of Urology, and agreed to transfer copyright to the publisher upon acceptance for publication.\u003c/p\u003e\n\u003ch2\u003eCompeting interests:\u003c/h2\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003ch2\u003eFunding:\u003c/h2\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eZW Sun, DL Yang and WW Lu contributed equally to this work. Drs ZC Xiu and HX Gu had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: ZW Sun, DL Yang, WW Lu, ZC Xiu and HX Gu; Acquisition, analysis, or interpretation of data: ZW Sun, DL Yang, WW Lu, JW Lu, L Xu, ZX Gao, ZC Xiu, BY Zhu, ZR Li, Y Wu and HX Gu; Drafting of the manuscript: ZW Sun, DL Yang, WW Lu, ZC Xiu; Critical revision of the manuscript for important intellectual content: ZC Xiu, HX Gu; Statistical analysis: ZW Sun, DL Yang, WW Lu, ZC Xiu and HX Gu; Obtained funding: None. Administrative, technical, or material support: ZC Xiu, HX Gu; Study supervision: ZC Xiu, HX Gu; Final approval of manuscript: All authors.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements:\u003c/h2\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; information (optional)\u003c/strong\u003e: Not applicable.\u003c/p\u003e\n\u003ch2\u003eAvailability of data and materials:\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMakino T, Kadomoto S, Izumi K, Mizokami A. Epidemiology and Prevention of Renal Cell Carcinoma. Cancers (Basel). 2022;14(16):4059.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSung H, Ferlay J, Siegel RL, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021;71(3):209\u0026ndash;49.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBahadoram S, Davoodi M, Hassanzadeh S, Bahadoram M, Barahman M, Mafakher L. Renal cell carcinoma: an overview of the epidemiology, diagnosis, and treatment. G Ital Nefrol. 2022;39(3):2022\u0026ndash;vol3. [pii].\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eConroy S, Catto J, Bex A, et al. Diagnosis, treatment, and survival from kidney cancer: real-world National Health Service England data between 2013 and 2019. BJU Int. 2023;132(5):541\u0026ndash;53.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLjungberg B, Albiges L, Abu-Ghanem Y, et al. European Association of Urology Guidelines on Renal Cell Carcinoma: The 2019 Update. Eur Urol. 2019;75(5):799\u0026ndash;810.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCampbell SC, Clark PE, Chang SS, Karam JA, Souter L, Uzzo RG. Renal Mass and Localized Renal Cancer: Evaluation, Management, and Follow-Up: AUA Guideline: Part I. J Urol. 2021;206(2):199\u0026ndash;208.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi KP, Chen SY, Wang CY, Li XR, Yang L. Perioperative and oncologic outcomes of minimally-invasive surgery for renal cell carcinoma with venous tumor thrombus: a systematic review and meta-analysis of comparative trials. Int J Surg. 2023;109(9):2762\u0026ndash;73.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKaldany A, Blum KA, Paulucci DJ et al. An evaluation of race, ethnicity, age, and sex-based representation in phase I to II renal cell carcinoma clinical trials in the United States. \u003cem\u003eUrol Oncol\u003c/em\u003e. 2018;36(8):363.e1-363.e6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePalumbo C, Pecoraro A, Rosiello G, et al. Renal cell carcinoma incidence rates and trends in young adults aged 20\u0026ndash;39 years. Cancer Epidemiol. 2020;67:101762.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee LS, Yuen JS, Sim HG. Renal cell carcinoma in young patients is associated with poorer prognosis. Ann Acad Med Singap. 2011;40(9):401\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGopee-Ramanan P, Chin SS, Lim C, Shanbhogue KP, Schieda N, Krishna S. Renal Neoplasms in Young Adults. Radiographics. 2022;42(2):433\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang J, Wang J, Li Q, et al. Young breast cancer patients who develop distant metastasis after surgery have better survival outcomes compared with elderly counterparts. Oncotarget. 2017;8(27):44851\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCheng L, Chen S, Wu W, et al. Gastric cancer in young patients: a separate entity with aggressive features and poor prognosis. J Cancer Res Clin Oncol. 2020;146(11):2937\u0026ndash;47.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePanian J, Lin X, Simantov R, Derweesh I, Choueiri TK, McKay RR. The Impact of Age and Gender on Outcomes of Patients With Advanced Renal Cell Carcinoma Treated With Targeted Therapy. Clin Genitourin Cancer. 2020;18(5):e598\u0026ndash;609.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJoung JY, Kwon WA, Lim J, et al. Second Primary Cancer Risk among Kidney Cancer Patients in Korea: A Population-Based Cohort Study. Cancer Res Treat. 2018;50(1):293\u0026ndash;301.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbu-Ghanem Y, Powles T, Capitanio U, et al. Should patients with low-risk renal cell carcinoma be followed differently after nephron-sparing surgery vs Curative Nephrectomy. BJU Int. 2021;128(3):386\u0026ndash;94.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVolpe A, Capitanio U, Falsaperla M, et al. Partial nephrectomy for renal tumors: recommendations of the Italian Society of Urology RCC working group. Minerva Urol Nephrol. 2024;76(1):9\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu F, Davaro F, Wong R, Siddiqui S, Hamilton Z. Young age is associated with decreased recurrence for renal cell carcinoma. Can J Urol. 2022;29(3):11142\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTang F, Lu Z, He C, Zhang H, Wu W, He Z. 53 years old is a reasonable cut-off value to define young and old patients in clear cell renal cell carcinoma: a study based on TCGA and SEER database. BMC Cancer. 2021;21(1):638.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbdulfatah E, Kennedy JM, Hafez K, et al. Clinicopathological characterisation of renal cell carcinoma in young adults: a contemporary update and review of literature. Histopathology. 2020;76(6):875\u0026ndash;87.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePu JL, Chen Z, Yao LQ et al. Long-term oncological prognosis after curative-intent liver resection for hepatocellular carcinoma in the young versus the elderly: multicentre propensity score-matching study. BJS Open. 2022;6(1).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePericleous M, Khan SA. Epidemiology of HPB malignancy in the elderly. Eur J Surg Oncol. 2021;47(3 Pt A):503\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKellokumpu I, Kairaluoma M, Mecklin JP, et al. Impact of Age and Comorbidity on Multimodal Management and Survival from Colorectal Cancer: A Population-Based Study. J Clin Med. 2021;10(8):1751.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAkhavan A, Richards M, Shnorhavorian M, Goldin A, Gow K, Merguerian PA. Renal cell carcinoma in children, adolescents and young adults: a National Cancer Database study. J Urol. 2015;193(4):1336\u0026ndash;41.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBukavina L, Bensalah K, Bray F, et al. Epidemiology of Renal Cell Carcinoma: 2022 Update. Eur Urol. 2022;82(5):529\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChoi E, Becker H, Jung H. Health-related quality of life in adolescents and young adults with and without cancer, using propensity score matching. J Cancer Surviv. 2023;17(2):279\u0026ndash;89.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSmith A, Fogarasi M, Lustberg MB, Nekhlyudov L. Perspectives of adolescent and young adult cancer survivors: review of community-based discussion boards. J Cancer Surviv. 2022;16(5):1079\u0026ndash;89.\u003c/span\u003e\u003c/li\u003e\u003c/ol\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":"Renal cell carcinoma, nephrectomy, Recurrence, Survival, young, elderly","lastPublishedDoi":"10.21203/rs.3.rs-8299759/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8299759/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground \u0026amp; Objectives:\u003c/h2\u003e \u003cp\u003eRenal cell carcinoma (RCC) incidence is rising among both elderly and younger populations. This study aimed to investigate the impact of age on long-term oncological outcomes following curative nephrectomy for early-stage RCC.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA retrospective analysis was conducted using data from 5 Chinese medical centers, including patients who underwent curative nephrectomy for T1-T2 RCC between 2008 and 2023. Patients aged\u0026thinsp;\u0026lt;\u0026thinsp;40 years and \u0026ge;\u0026thinsp;75 years were compared for overall survival (OS), cancer-specific survival (CSS), and recurrence rates. Propensity score matching (PSM) was employed to balance baseline characteristics.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOf 357 patients, 234 (65.5%) were young and 123 (34.5%) were elderly. PSM yielded 96 pairs. In the matched cohort, young patients demonstrated significantly lower 5-year OS (76.0% vs 86.5%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.038) and CSS rates (86.5% vs 93.8%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.019) compared to elderly patients. The 5-year cumulative recurrence rate was higher in young patients (28.1% vs 13.5%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003). Multivariable analysis confirmed young age as an independent risk factor for decreased OS (HR 2.407, 95% CI 1.387\u0026ndash;4.177; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002) and increased recurrence (HR 2.824, 95% CI 1.393\u0026ndash;5.722; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eDiverging from traditional expectations, our study reveals that younger patients experienced poorer long-term outcomes after curative nephrectomy for early-stage RCC. These findings suggest the need for more intensive surveillance and possibly more aggressive treatment strategies for young RCC patients.\u003c/p\u003e","manuscriptTitle":"Evaluating the Role of Age in Post-Nephrectomy Outcomes for Patients with Early-Stage Renal Cell Carcinoma: A Retrospective Multi-Centre Cohort Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-12 07:10:15","doi":"10.21203/rs.3.rs-8299759/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":"a8cea126-3a6a-47f4-941f-349b7aee971b","owner":[],"postedDate":"January 12th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-22T09:28:27+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-12 07:10:15","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8299759","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8299759","identity":"rs-8299759","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}