The Impact of Delay From Diagnosis to Surgeryin Endometrial Cancer

The Impact of Delay From Diagnosis to Surgeryin Endometrial Cancer | 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 Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Impact of Delay From Diagnosis to Surgeryin Endometrial Cancer Dimitrios Zouzoulas, Dimitrios Tsolakidis, Tilemachos Karalis, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3876604/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 05 Dec, 2024 Read the published version in Archives of Gynecology and Obstetrics → Version 1 posted 5 You are reading this latest preprint version Abstract Purpose When oncological waiting lists are prolonged, gynecological-oncology units are forced to delay operations, especially for endometrial cancer (EC) due to its good prognosis among gynecological cancers. The aim of this study is to evaluate the impact of delay in the oncological outcomes of these patients. Methods Retrospective analysis of all women with EC treated in our clinic, 2012–2019. Delay was calculated as the time interval between histological diagnosis of endometrial biopsy and definite surgery. The cut-off point was set at 8 weeks. Patients’ characteristics, treatment options and follow-up information were collected. Primary outcomes were the need of adjuvant treatment and survival rates. Results 259 patients met the inclusion criteria. Based on the 8-week cutoff point patients were divided into two groups: 119 underwent surgery up to 8-weeks (group A) and 140 over 8-weeks (group B). There was no statistical difference in the FIGO stage or the pre-operative CA125 level between the two groups. However, patients in group A were younger, with lower BMI and less comorbidities. Furthermore, patients in group B had a significantly higher probability of receiving pelvic radiation with or without brachytherapy (p = 0.0053). Concerning survival rates, there was a statistically difference in disease-free (p = 0.0312), but no difference was found in overall survival (p = 0.146). Conclusion Delaying EC surgery over 8 weeks may not have an impact on the mortality of the patients, but increases the need of adjuvant pelvic radiation and worsens recurrence rates. As a result, patients experience more side effects which subsequently had negative impact on their quality of life. Endometrial cancer Delay Adjuvant treatment Survival rates Figures Figure 1 Figure 2 Figure 3 WHAT DOES THIS STUDY ADDS TO THE CLINICAL WORK Endometrial cancer patients should be operated as soon as possible form the date of diagnosis, irrespectively of the expected good prognosis of the disease, because delays increase the need of adjuvant pelvic radiation and worsen recurrence rates. INTRODUCTION Endometrial cancer is the most common gynecological malignancy in the developed world [ 1 ] and for the last decades its incidence is increasing [ 2 , 3 ]. Usually, endometrial cancer is diagnosed in an early stage with a favorable 5-year survival at 96%, because of its early symptoms, but when it is diagnosed at an advanced stage, the 5-year survival decreases to 20% [ 4 ]. Thus, it is important to minimize the “wait time” between the diagnosis of endometrial biopsy and the surgery. A prolonged delay may lead to both distant and local tumor growth, allowing the development of poor prognostic characteristics, such as deeper myometrial invasion and lymphovascular space involvement [ 5 ]. Cancer surgery waiting lists are an important health care issue that among many countries [ 6 ]. Studies for other types of cancer [ 7 ], such as breast, colorectal, bladder and melanoma, have shown a decreased survival when waiting times are longer. The effect of the delay on survival for endometrial cancer patients still remains controversial and another immerging issue is the quality of life of these patients. Quality of life is mainly affected by the need of adjuvant treatment after surgery. Almost half of endometrial cancer patients will undergo adjuvant treatment, mainly radiotherapy, based on the stage and the poor prognostic characteristics of the tumor [ 8 ]. So, it is important that physicians are not reassured by the slow-growth rate of the disease when surgery is delayed. METHODS Study characteristics We retrospectively reviewed the medical records of all women with endometrial cancer, who were treated in the 1 st Department of Obstetrics & Gynecology, Aristotle University of Thessaloniki at “Papageorgiou” hospital, from 1 January 2012 until 31 December 2019 and identified those who underwent upfront surgery. In total, 273 patients were diagnosed with endometrial cancer during this period of time. A written approval was received from the Head of the Department and the Scientific Committee of the hospital. Patients Inclusion criteria: Histological confirmation of endometrial cancer. Surgical treatment at our Gynecological – Oncology Unit. Exclusion criteria: Missing important registry data after the diagnosis of endometrial cancer. Administration of neoadjuvant chemotherapy after diagnosis. Presence of a synchronous neoplasm. As a result of the above-mentioned criteria, 7 out of the 273 women with endometrial cancer were excluded due to important missing registry data. Moreover, 2 women were excluded, because they received neoadjuvant chemotherapy after the diagnosis and another 5 women, because they had a synchronous neoplasm. Hence, finally 259 women with endometrial cancer were identified as eligible for further analysis, with no duplicate data and important missing values. The flowchart of the patient selection is shown in Figure 1. Data Collection Data were collected during a period of one month. In order to avoid inconsistencies among different dates of data collection a uniform data collection sheet was used, during the retrospective retrieval of the patient’s medical records. The data sheet included the following information: Patient’s identifiers: Name Hospital identification number Patient’s age BMI Charlson Comorbidity Index (CCI) Tumor marker CA-125 Surgery duration Intraoperative blood loss Disease stage (FIGO staging): I II III IV Intensive Care Unit (ICU) admission Hospital stay Adjuvant Treatment: Monitoring Chemotherapy Pelvic Radiotherapy ± Brachytherapy Brachytherapy Time related data: Date of diagnosis Date of surgery Date of recurrence Date of last follow-up or death Statistical Analysis All analyses were performed using RStudio. For descriptive statistics of qualitative variables, the frequency distribution procedure was run with calculation of the number of cases and percentages. On the other hand, for descriptive statistics of quantitative variables, the mean, median, range, and standard deviation were used to describe central tendency and dispersion. Univariate and multivariate analysis was performed. Disease-free (DFS) and overall survival (OS) analyses were performed using the Kaplan – Meier curves and groups were compared using the log-rank test. Disease-free survival was defined as the time interval between date of diagnosis and date of first recurrence. A p-value of <0.05 was considered as statistically significant. RESULTS This retrospective cohort study included 273 women, who were treated during the period of the study for histologically proven endometrial cancer in the Gynecological – Oncology Unit, 1st Department of Obstetrics & Gynecology, Aristotle University of Thessaloniki, “Papageorgiou” Hospital. After screening the patients based on the inclusion and exclusion criteria, 259 patients were eligible for further analysis in this study. Patients’ characteristics are outlined in Table 1 . The median age of the women at the time of the diagnosis was 64 years old, with an IQR of 56–73. The median BMI was 33.1 kg/m 2 , meaning that most women were obese, which is in accordance with the phenotype of women suffering from endometrial cancer. Furthermore, concerning the performance status of our patients, more than three quarters (83%) of them have mild to moderate comorbidities, which was measured by the Charlson Comorbidities Index. Table 1 Patient Characteristics Patient characteristics Number of patients (N) Percentage (%) Age (years) median : 64 IQR : 56–73 BMI median : 33.1 IQR : 28.3–39.7 CCI median : 3 IQR : 2–4 1–2 88 34 3–4 128 49.4 ≥ 5 32 12.4 unknown 11 4.2 Surgery Delay (weeks) ≤ 8 119 46 > 8 140 54 CA-125 (U/ml) median : 16.2 IQR : 11.1–32 FIGO Stage I 185 71.5 II 34 13.1 III 33 12.7 IV 7 2.7 Surgery Duration (min) median : 120 IQR : 90–168.8 Blood Loss (cc) median : 200 IQR : 100–300 ICU Admission 4 1.5 Hospital Stay (days) median : 7 IQR : 6–8 According to the FIGO staging system: 185 patients (71.5%) had Stage I, 34 (13.1%) had Stage II, 33 (12.7%) had Stage III and 7 (25.6%) had Stage IV disease. The median values of CA-125 was 16.2 (U/ml), with an IQR of 11.1–32, which is within normal range (< 35 U/ml). Moreover, regarding the perioperative data, the median duration of surgery was 120 minutes, with an IQR of 90–168.8 and the median blood loss was 200cc, with an IQR of 100–300. Only 4 (1.5%) patients required ICU admission and the median hospitalization was one week, with an IQR of 6–8 days. On the other hand, after surgical treatment all women were discussed at a multidisciplinary tumor board and the adjuvant treatment was decided. Approximately, 60% of the patients were offered some type of adjuvant therapy. According to the MDT decision: 101 patients (39%) did not receive any type of postoperative therapy and underwent only close follow-up (monitoring), 51 patients (19.7%) received only brachytherapy, 67 patients (25.9%) received pelvic radiotherapy with or without subsequent brachytherapy and 40 patients (15.4%) were offered systematic therapy (chemotherapy). Adjuvant treatments are summarized in Table 2 . Table 2 Treatment Options Adjuvant treatment Number of patients (N) Percentage (%) Monitoring 101 39 Brachytherapy 51 19.7 Pelvic Radiotherapy ± Brachytherapy 67 25.9 Chemotherapy 40 15.4 The main endpoint of our study was the impact of delay from diagnosis to surgery. The cut-off point was set at 8 weeks and two almost equal in number groups of patients were resulted: Group A (≤ 8weeks) and Group B (> 8weeks) with 119 (46%) and 140 (54%) patients, respectively. Patients that experienced the longer delay were those of Group B with > 8weeks, who were statistically significantly older (Group B: 66 vs. Group A: 62 years old, p = 0.014), had a higher BMI (Group B: 34.1 vs. Group A: 31.1, p = 0.012) with more comorbidities (p = 0.009). Although there was difference between the two groups in the pre-operative CA-125 values and the FIGO stage, the patients were equally distributed between the two groups in early (I and II) and advanced (III and IV) stages. Additionally, concerning perioperative data, no statistically significant difference was found in surgery duration, ICU admission and hospitalization, while surprisingly blood loss was significantly lower in Group B (> 8weeks). Regarding of adjuvant treatment, only pelvic radiotherapy with or without subsequent brachytherapy was found to be statistically significant different, in favor of Group A (≤ 8weeks). Patients in Group B were offered extensive radiation fields compared to Group A, more than double in number (Group A: 21 vs. Group B: 46). The aforementioned data are detailed presented in Tables 3 and 4 . Table 3 Comparison based on Surgery Delay Treatment Group A (≤ 8weeks) median (IQR) Group B (> 8weeks) median (IQR) p-value Population (N) 119 (46%) 140 (54%) - Age (years) 62 (54.5–70) 66 (57.8–74) 0.014 BMI 31.1 (25.8–35.5) 34.1 (29.2–42.6) 0.012 CCI 3 (2–4) 3 (2–4) 0.009 CA-125 (U/ml) 14.9 (10.2–33.6) 16.6 (11.4–30) 0.494 FIGO Stage I 87 98 > 0.05 II 12 22 > 0.05 III 16 17 > 0.05 IV 4 3 > 0.05 Surgery Duration (min) 130 120 0.418 Blood Loss (cc) 300 (150–250) 150 (100–250) 8weeks) (N) p-value Monitoring 53 48 0.07 Brachytherapy 25 26 0.6231 Pelvic Radiotherapy ± Brachytherapy 21 46 0.005 Chemotherapy 20 20 0.5758 In order to identify which factors were associated with the need of adjuvant pelvic radiotherapy with or without subsequent brachytherapy, univariate and multivariate analyses were conducted. The relevant data are shown in Table 5 . The univariate analysis revealed that age and delay of surgery were the only statistically significant variables (p < 0.001). But, in the final model (with factors with a p < 0.2) for the multivariable analysis we included also the CCI (p = 0.135). The odds for adjuvant radiotherapy are increased by about 1.05 times as patient’s age increases by one year, after adjusting for the other factors. The related p-value is 0.027 which means that this is a statistically significant result at a 5% level. Furthermore, the odds for adjuvant radiation are 2.3 times higher for patients with a delay > 8weeks compared to patients with a delay < 8 weeks, adjusted for all the other variables in the model. The related p-value is 0.009 which means that this is a statistically significant result at a 5% level. . Table 5 Pelvic Radiotherapy ± Brachytherapy (Logistic regression) Univariate model Multivariate model OR 95% CI p-value OR 95% CI p-value Age (years) 1.4 1.01, 1.07 0.005 1.05 0.002, 0.13 0.027 Delay ≤ 8 weeks 1 1 > 8 weeks 2.28 1.18, 4.18 0.006 2.3 1.25, 4.35 0.009 BMI 0.998 0.957, 1.039 0.929 CCI 1.14 0.96, 1.37 0.135 0.88 0.64, 1.16 0.403 CA-125 0.998 0.993, 1.001 0.516 . All women that were included in the study had frequent follow-up, with a median of approximately 48 months and an IQR of 18–78 months. Survival rates were calculated using Kaplan-Meier curves. In the analysis between the two groups, the median OS in Group A and B was > 120 and 117 months, respectively and the median DFS was > 120 months and 110 months, respectively. By using log-rank tests, there was no statistical significant difference in the OS (p = 0.15), but a statistical significant difference was observed in DFS (p = 0.031) between the two groups in favor of Group A (≤ 8weeks). These results are shown in Figs. 2 and 3 . DISCUSSION To our knowledge this is the only study in the literature, not based in a national registry database, that analyzed waiting time from diagnosis to surgery for all endometrial cancer patients concerning survival rates and the need for adjuvant treatment, which often affects patient’s quality of life. Most publications [ 4 , 5 , 9 , 10 ] in the literature are large epidemiological studies with a high ratio of missing data. In contrast, our study comes from a single university center with a gynecological oncology unit with a detailed database. Previous single center studies are either underpowered and outdated [ 11 ] or did not have as endpoints both survival and quality of life as endpoints [ 12 – 14 ]. The cut-off point of surgery delay in cases with endometrial cancer was defined differently among published papers. Cut-off points from 6 to 12 weeks have been described in the literature. In our study we found that 8 weeks is the optimal cut-off point, based on the fact that our population was equally distributed and the fact that this cut-off point was also used in a recent large national registry study [ 9 ] which included both low and high risk patients with endometrial cancer. A time interval of at least 8 weeks might seem too long for the prognosis of cancer patients, but it can be explained, if we seek for the reasons of this delay. Three of the largest national registry studies concluded that the two main reasons of treatment delay are: 1) comorbidities – preoperative medical optimization and 2) referral to centralized high-volume gynecological oncology centers. Most endometrial cancer patients are menopausal (at least over 50 years old), obese with more than one comorbidity, categorize them as high-risk patients for surgery. These patients require a careful preoperative check-up and an established prehabilitation program [ 15 ]. High volume tertiary cancer centers with longer surgery wait lists should not be viewed as a disadvantage, because a referral to a gynecologic oncologist has a positive impact on the survival of endometrial cancer patients [ 16 ]. These facts are in accordance with our findings, as the median age of our patients was 64 years old, with a median BMI of 33 and almost half of our patients had moderate comorbidities. Our gynecological oncology unit of a tertiary university hospital has a well-established prehabilitation program which can last up to 4 weeks. So, the waiting time until surgery is counterweighted by the medical optimization of the patients in this period. Concerning the main endpoint of our study, which was the impact of delay from diagnosis to surgery by setting the cut-off point at 8 weeks. Group A (≤ 8weeks) and Group B (> 8weeks) were almost equal (no statistical significance) in terms of population, FIGO stage, surgery duration, ICU admission and hospitalization. However, patients with the longer waiting time (Group B) had a statistically older age, higher BMI and more comorbidities compared to Group A. This can be explained by the fact that older, obese and patients with comorbidities undergo extensive preoperative check-ups and longer prehabilitation programs to improve their preoperative physical performance. Another paradox fact is that patients with longer waiting times have a statistically lower intraoperative blood loss. This is possible explained by the use of advanced bipolar energy from 2017, when also the 4week prehabilitation program was implemented. Furthermore, after analyzing adjuvant treatments between the two groups, a statistically significant higher (more than double) need for adjuvant pelvic radiotherapy with or without subsequent brachytherapy was found in Group B (> 8weeks) patients. After univariate and multivariate analysis for possible confounding factors, delay > 8weeks and older age were the only statistically significant factors. Our results are contradicted with the ones from the only study in the literature that analyzes the need of adjuvant treatment [ 12 ], where the authors found out that longer time interval between diagnosis and surgery did not increase the need for adjuvant therapy. This could be explained by the fact that our study included both low- and high-risk endometrial cancer patients, while the other authors only looked at low-risk disease. Last but not least, concerning survival rates, there is no study in the medical bibliography, that correlate the surgery delay to the recurrence rate, disease-free and overall survival. Our data showed that patients with a longer delay from diagnosis to surgery had a statistically significant higher chance of developing a recurrence. On the other hand, no statistical significance was found in the overall survival between the two groups. There are many available data in the literature concerning the mortality of endometrial cancer and the impact of surgery delay. The majority of them show a negative impact of surgery delay on mortality. However, data from national registries [ 4 , 5 , 9 , 10 ] should be carefully interpreted, as all authors state that the causes of death were not available in their databases. Data from other high-volume centers are reporting conflicting results. Dolly et al. [ 14 ] found that longer wait times (up to 12weeks) had a statistically worse overall survival, while Matsuo et al. [ 13 ] showed no correlation with overall survival. The main limitation of our study is its retrospective nature and its geographical limitation since it’s a single center study. In contrast, the most important strength of our study is the lack of missing data (< 5%) and that all consecutive patients irrelevant to their stage and risk factors, were included in the study. This gains even more value in the emerging era of molecular classification [ 17 ] and the new FIGO classification [ 18 ] where type I and II disease terms are abandoned and patients between low- / high-risk groups are shifting. CONCLUSIONS Older, obese and multi-morbid patients of endometrial cancer have a higher chance of longer surgery delay, due to need for extensive preoperative examinations and medical optimization. Delaying endometrial cancer surgery over 8 weeks may not have an impact on the mortality of the patients, but increases the need of adjuvant pelvic radiation and worsens recurrence rates. As a result, patients experience more side effects which subsequently worsen their quality of life. Declarations The authors whose names are listed above certify that they have NO affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers’ bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements), or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript. AUTHOR CONTRIBUTION D. Zouzoulas: Writing – original draft preparation, Data collection, Data analysis D. Tsolakidis: Conceptualization, Writing – review and editing, Methodology T. Karalis: Data collection M. Aristotelidis: Data collection M. Topalidou: Resources G. Grimbizis: Validation, Supervision Funding : No funding for this study Conflicts of interest : The authors declare that they have no conflict of interest Availability of data and material : All data is available in the Excel file Code availability : RStudio free software was used References Jemal A, Bray F, Center MM et al (2011) Global cancer statistics. CA Cancer J Clin 61:69–90. https://doi.org/10.3322/caac.20107 Ghezzi F, Cromi A, Bergamini V et al (2006) Laparoscopic-assisted vaginal hysterectomy versus total laparoscopic hysterectomy for the management of endometrial cancer: a randomized clinical trial. J Minim Invasive Gynecol 13:114–120. https://doi.org/10.1016/j.jmig.2005.11.013 de la Orden SG, Reza MM, Blasco JA et al (2008) Laparoscopic Hysterectomy in the Treatment of Endometrial Cancer: A Systematic Review. 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Int J Gynecol Obstet 162:383–394. https://doi.org/10.1002/ijgo.14923 Cite Share Download PDF Status: Published Journal Publication published 05 Dec, 2024 Read the published version in Archives of Gynecology and Obstetrics → Version 1 posted Reviewers agreed at journal 04 Mar, 2024 Reviewers invited by journal 09 Feb, 2024 Editor invited by journal 08 Feb, 2024 Editor assigned by journal 18 Jan, 2024 First submitted to journal 17 Jan, 2024 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. 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19:51:28","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":32256,"visible":true,"origin":"","legend":"\u003cp\u003ePatients selection flowchart\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-3876604/v1/37b9245211c909c9bdceb809.png"},{"id":51083963,"identity":"bfcd6d25-7dae-4c8e-8c77-da5f76ff66ee","added_by":"auto","created_at":"2024-02-13 19:43:28","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":38354,"visible":true,"origin":"","legend":"\u003cp\u003eDisease-free survival (DFS) based on Surgery Delay\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-3876604/v1/807acab59fe79406c81f2b28.png"},{"id":51083964,"identity":"ba69f06e-218a-429a-803e-82e6b944947a","added_by":"auto","created_at":"2024-02-13 19:43:28","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":38085,"visible":true,"origin":"","legend":"\u003cp\u003eOverall survival (OS) based on Surgery Delay\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-3876604/v1/426cb6ebe9d96e8e2f84d21b.png"},{"id":70964730,"identity":"d68cac4a-4a11-4d0e-b1ec-c66215312a18","added_by":"auto","created_at":"2024-12-09 16:14:56","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":781567,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3876604/v1/797515ae-f8f4-45d7-8d89-c595beee3cce.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003eThe Impact of Delay From Diagnosis to Surgeryin Endometrial Cancer\u003c/p\u003e","fulltext":[{"header":"WHAT DOES THIS STUDY ADDS TO THE CLINICAL WORK","content":"\u003cp\u003eEndometrial cancer patients should be operated as soon as possible form the date of diagnosis, irrespectively of the expected good prognosis of the disease, because delays increase the need of adjuvant pelvic radiation and worsen recurrence rates.\u003c/p\u003e"},{"header":"INTRODUCTION","content":"\u003cp\u003eEndometrial cancer is the most common gynecological malignancy in the developed world [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] and for the last decades its incidence is increasing [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Usually, endometrial cancer is diagnosed in an early stage with a favorable 5-year survival at 96%, because of its early symptoms, but when it is diagnosed at an advanced stage, the 5-year survival decreases to 20% [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Thus, it is important to minimize the \u0026ldquo;wait time\u0026rdquo; between the diagnosis of endometrial biopsy and the surgery. A prolonged delay may lead to both distant and local tumor growth, allowing the development of poor prognostic characteristics, such as deeper myometrial invasion and lymphovascular space involvement [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Cancer surgery waiting lists are an important health care issue that among many countries [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Studies for other types of cancer [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], such as breast, colorectal, bladder and melanoma, have shown a decreased survival when waiting times are longer. The effect of the delay on survival for endometrial cancer patients still remains controversial and another immerging issue is the quality of life of these patients. Quality of life is mainly affected by the need of adjuvant treatment after surgery. Almost half of endometrial cancer patients will undergo adjuvant treatment, mainly radiotherapy, based on the stage and the poor prognostic characteristics of the tumor [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. So, it is important that physicians are not reassured by the slow-growth rate of the disease when surgery is delayed.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eStudy characteristics\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWe retrospectively reviewed the medical records of all women with endometrial cancer, who were treated in the 1\u003csup\u003est\u003c/sup\u003e Department of Obstetrics \u0026amp; Gynecology, Aristotle University of Thessaloniki at \u0026ldquo;Papageorgiou\u0026rdquo; hospital, from 1 January 2012 until 31 December 2019 and identified those who underwent upfront surgery. \u0026nbsp;In total, 273 patients were diagnosed with endometrial cancer during this period of time. A written approval was received from the Head of the Department and the Scientific Committee of the hospital.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003ePatients\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInclusion criteria:\u003c/strong\u003e\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003eHistological confirmation of endometrial cancer.\u003c/li\u003e\n \u003cli\u003eSurgical treatment at our Gynecological \u0026ndash; Oncology Unit.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eExclusion criteria:\u003c/strong\u003e\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003eMissing important registry data after the diagnosis of endometrial cancer.\u003c/li\u003e\n \u003cli\u003eAdministration of neoadjuvant chemotherapy after diagnosis.\u003c/li\u003e\n \u003cli\u003ePresence of a synchronous neoplasm.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eAs a result of the above-mentioned criteria, 7 out of the 273 women with endometrial cancer were excluded due to important missing registry data. Moreover, 2 women were excluded, because they received neoadjuvant chemotherapy after the diagnosis and another 5 women, because they had a synchronous neoplasm. Hence, finally 259 women with endometrial cancer were identified as eligible for further analysis, with no duplicate data and important missing values. The flowchart of the patient selection is shown in Figure 1.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eData Collection\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eData were collected during a period of one month. In order to avoid inconsistencies among different dates of data collection a uniform data collection sheet was used, during the retrospective retrieval of the patient\u0026rsquo;s medical records. The data sheet included the following information:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003ePatient\u0026rsquo;s identifiers:\u003cul style=\"list-style-type: circle;\"\u003e\n \u003cli\u003eName\u003c/li\u003e\n \u003cli\u003eHospital identification number\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/li\u003e\n \u003cli\u003ePatient\u0026rsquo;s age\u003c/li\u003e\n \u003cli\u003eBMI\u003c/li\u003e\n \u003cli\u003eCharlson Comorbidity Index (CCI)\u003c/li\u003e\n \u003cli\u003eTumor marker CA-125\u003c/li\u003e\n \u003cli\u003eSurgery duration\u003c/li\u003e\n \u003cli\u003eIntraoperative blood loss\u003c/li\u003e\n \u003cli\u003eDisease stage (FIGO staging):\u003cul style=\"list-style-type: circle;\"\u003e\n \u003cli\u003eI\u003c/li\u003e\n \u003cli\u003eII\u003c/li\u003e\n \u003cli\u003eIII\u003c/li\u003e\n \u003cli\u003eIV\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/li\u003e\n \u003cli\u003eIntensive Care Unit (ICU) admission\u003c/li\u003e\n \u003cli\u003eHospital stay\u003c/li\u003e\n \u003cli\u003eAdjuvant Treatment:\u003cul style=\"list-style-type: circle;\"\u003e\n \u003cli\u003eMonitoring\u003c/li\u003e\n \u003cli\u003eChemotherapy\u003c/li\u003e\n \u003cli\u003ePelvic Radiotherapy \u0026plusmn; Brachytherapy\u003c/li\u003e\n \u003cli\u003eBrachytherapy\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/li\u003e\n \u003cli\u003eTime related data:\u003cul style=\"list-style-type: circle;\"\u003e\n \u003cli\u003eDate of diagnosis\u003c/li\u003e\n \u003cli\u003eDate of surgery\u003c/li\u003e\n \u003cli\u003eDate of recurrence\u003c/li\u003e\n \u003cli\u003eDate of last follow-up or death\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eStatistical Analysis\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAll analyses were performed using RStudio. For descriptive statistics of qualitative variables, the frequency distribution procedure was run with calculation of the number of cases and percentages. On the other hand, for descriptive statistics of quantitative variables, the mean, median, range, and standard deviation were used to describe central tendency and dispersion. Univariate and multivariate analysis was performed. Disease-free (DFS) and overall survival (OS) analyses were performed using the Kaplan \u0026ndash; Meier curves and groups were compared using the log-rank test. Disease-free survival was defined as the time interval between date of diagnosis and date of first recurrence. A p-value of \u0026lt;0.05 was considered as statistically significant.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eThis retrospective cohort study included 273 women, who were treated during the period of the study for histologically proven endometrial cancer in the Gynecological \u0026ndash; Oncology Unit, 1st Department of Obstetrics \u0026amp; Gynecology, Aristotle University of Thessaloniki, \u0026ldquo;Papageorgiou\u0026rdquo; Hospital. After screening the patients based on the inclusion and exclusion criteria, 259 patients were eligible for further analysis in this study.\u003c/p\u003e \u003cp\u003ePatients\u0026rsquo; characteristics are outlined in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The median age of the women at the time of the diagnosis was 64 years old, with an IQR of 56\u0026ndash;73. The median BMI was 33.1 kg/m\u003csup\u003e2\u003c/sup\u003e, meaning that most women were obese, which is in accordance with the phenotype of women suffering from endometrial cancer. Furthermore, concerning the performance status of our patients, more than three quarters (83%) of them have mild to moderate comorbidities, which was measured by the Charlson Comorbidities Index.\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\u003ePatient Characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003ePatient characteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber of patients (N)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercentage (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003emedian\u003c/b\u003e: 64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eIQR\u003c/b\u003e: 56\u0026ndash;73\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003emedian\u003c/b\u003e: 33.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eIQR\u003c/b\u003e: 28.3\u0026ndash;39.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCCI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003emedian\u003c/b\u003e: 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eIQR\u003c/b\u003e: 2\u0026ndash;4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026ndash;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u0026ndash;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e49.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eunknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSurgery Delay (weeks)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026le; 8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCA-125 (U/ml)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003emedian\u003c/b\u003e: 16.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eIQR\u003c/b\u003e: 11.1\u0026ndash;32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFIGO Stage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e185\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e71.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSurgery Duration (min)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003emedian\u003c/b\u003e: 120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eIQR\u003c/b\u003e: 90\u0026ndash;168.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBlood Loss (cc)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003emedian\u003c/b\u003e: 200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eIQR\u003c/b\u003e: 100\u0026ndash;300\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eICU Admission\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHospital Stay (days)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003emedian\u003c/b\u003e: 7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eIQR\u003c/b\u003e: 6\u0026ndash;8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAccording to the FIGO staging system: 185 patients (71.5%) had Stage I, 34 (13.1%) had Stage II, 33 (12.7%) had Stage III and 7 (25.6%) had Stage IV disease. The median values of CA-125 was 16.2 (U/ml), with an IQR of 11.1\u0026ndash;32, which is within normal range (\u0026lt;\u0026thinsp;35 U/ml). Moreover, regarding the perioperative data, the median duration of surgery was 120 minutes, with an IQR of 90\u0026ndash;168.8 and the median blood loss was 200cc, with an IQR of 100\u0026ndash;300. Only 4 (1.5%) patients required ICU admission and the median hospitalization was one week, with an IQR of 6\u0026ndash;8 days.\u003c/p\u003e \u003cp\u003eOn the other hand, after surgical treatment all women were discussed at a multidisciplinary tumor board and the adjuvant treatment was decided. Approximately, 60% of the patients were offered some type of adjuvant therapy. According to the MDT decision: 101 patients (39%) did not receive any type of postoperative therapy and underwent only close follow-up (monitoring), 51 patients (19.7%) received only brachytherapy, 67 patients (25.9%) received pelvic radiotherapy with or without subsequent brachytherapy and 40 patients (15.4%) were offered systematic therapy (chemotherapy). Adjuvant treatments are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\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\u003eTreatment Options\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=\"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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAdjuvant treatment\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eNumber of patients (N)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePercentage (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMonitoring\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBrachytherapy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e19.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePelvic Radiotherapy\u0026thinsp;\u0026plusmn;\u0026thinsp;Brachytherapy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e25.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChemotherapy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e15.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe main endpoint of our study was the impact of delay from diagnosis to surgery. The cut-off point was set at 8 weeks and two almost equal in number groups of patients were resulted: Group A (\u0026le; 8weeks) and Group B (\u0026gt;\u0026thinsp;8weeks) with 119 (46%) and 140 (54%) patients, respectively. Patients that experienced the longer delay were those of Group B with \u0026gt;\u0026thinsp;8weeks, who were statistically significantly older (Group B: 66 vs. Group A: 62 years old, p\u0026thinsp;=\u0026thinsp;0.014), had a higher BMI (Group B: 34.1 vs. Group A: 31.1, p\u0026thinsp;=\u0026thinsp;0.012) with more comorbidities (p\u0026thinsp;=\u0026thinsp;0.009). Although there was difference between the two groups in the pre-operative CA-125 values and the FIGO stage, the patients were equally distributed between the two groups in early (I and II) and advanced (III and IV) stages. Additionally, concerning perioperative data, no statistically significant difference was found in surgery duration, ICU admission and hospitalization, while surprisingly blood loss was significantly lower in Group B (\u0026gt;\u0026thinsp;8weeks). Regarding of adjuvant treatment, only pelvic radiotherapy with or without subsequent brachytherapy was found to be statistically significant different, in favor of Group A (\u0026le; 8weeks). Patients in Group B were offered extensive radiation fields compared to Group A, more than double in number (Group A: 21 vs. Group B: 46). The aforementioned data are detailed presented in Tables\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison based on Surgery Delay\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=\"left\" 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=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eTreatment\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGroup A (\u0026le; 8weeks)\u003c/p\u003e \u003cp\u003emedian (IQR)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eGroup B (\u0026gt;\u0026thinsp;8weeks)\u003c/p\u003e \u003cp\u003emedian (IQR)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePopulation (N)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e119 (46%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e140 (54%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62 (54.5\u0026ndash;70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66 (57.8\u0026ndash;74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.014\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.1 (25.8\u0026ndash;35.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34.1 (29.2\u0026ndash;42.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.012\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCCI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (2\u0026ndash;4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (2\u0026ndash;4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.009\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCA-125 (U/ml)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.9 (10.2\u0026ndash;33.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.6 (11.4\u0026ndash;30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e0.494\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFIGO Stage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSurgery Duration (min)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e0.418\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBlood Loss (cc)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e300 (150\u0026ndash;250)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e150 (100\u0026ndash;250)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eICU Admission\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e0.6271\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHospital Stay (days)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (6-8.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (6\u0026ndash;8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e0.742\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\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 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAdjuvant Treatment based on Surgery Delay\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=\"left\" 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=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eTreatment\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGroup A (\u0026le; 8weeks) (N)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eGroup B (\u0026gt;\u0026thinsp;8weeks)\u003c/p\u003e \u003cp\u003e(N)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMonitoring\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBrachytherapy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e0.6231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePelvic Radiotherapy\u0026thinsp;\u0026plusmn;\u0026thinsp;Brachytherapy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChemotherapy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e0.5758\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn order to identify which factors were associated with the need of adjuvant pelvic radiotherapy with or without subsequent brachytherapy, univariate and multivariate analyses were conducted. The relevant data are shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. The univariate analysis revealed that age and delay of surgery were the only statistically significant variables (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). But, in the final model (with factors with a p\u0026thinsp;\u0026lt;\u0026thinsp;0.2) for the multivariable analysis we included also the CCI (p\u0026thinsp;=\u0026thinsp;0.135). The odds for adjuvant radiotherapy are increased by about 1.05 times as patient\u0026rsquo;s age increases by one year, after adjusting for the other factors. The related p-value is 0.027 which means that this is a statistically significant result at a 5% level. Furthermore, the odds for adjuvant radiation are 2.3 times higher for patients with a delay\u0026thinsp;\u0026gt;\u0026thinsp;8weeks compared to patients with a delay\u0026thinsp;\u0026lt;\u0026thinsp;8 weeks, adjusted for all the other variables in the model. The related p-value is 0.009 which means that this is a statistically significant result at a 5% level.\u003c/p\u003e \u003cp\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 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePelvic Radiotherapy\u0026thinsp;\u0026plusmn;\u0026thinsp;Brachytherapy (Logistic regression)\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=\"left\" 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=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eUnivariate model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eMultivariate model\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.01, 1.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.002, 0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.027\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDelay\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le; 8 weeks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\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\u003e\u0026gt;\u0026thinsp;8 weeks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.18, 4.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.25, 4.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.009\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.998\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.957, 1.039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.929\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\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\u003e\u003cb\u003eCCI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.96, 1.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.64, 1.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.403\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCA-125\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.998\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.993, 1.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.516\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e.\u003c/p\u003e \u003cp\u003eAll women that were included in the study had frequent follow-up, with a median of approximately 48 months and an IQR of 18\u0026ndash;78 months. Survival rates were calculated using Kaplan-Meier curves. In the analysis between the two groups, the median OS in Group A and B was \u0026gt;\u0026thinsp;120 and 117 months, respectively and the median DFS was \u0026gt;\u0026thinsp;120 months and 110 months, respectively. By using log-rank tests, there was no statistical significant difference in the OS (p\u0026thinsp;=\u0026thinsp;0.15), but a statistical significant difference was observed in DFS (p\u0026thinsp;=\u0026thinsp;0.031) between the two groups in favor of Group A (\u0026le; 8weeks). These results are shown in Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eTo our knowledge this is the only study in the literature, not based in a national registry database, that analyzed waiting time from diagnosis to surgery for all endometrial cancer patients concerning survival rates and the need for adjuvant treatment, which often affects patient\u0026rsquo;s quality of life. Most publications [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] in the literature are large epidemiological studies with a high ratio of missing data. In contrast, our study comes from a single university center with a gynecological oncology unit with a detailed database. Previous single center studies are either underpowered and outdated [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] or did not have as endpoints both survival and quality of life as endpoints [\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe cut-off point of surgery delay in cases with endometrial cancer was defined differently among published papers. Cut-off points from 6 to 12 weeks have been described in the literature. In our study we found that 8 weeks is the optimal cut-off point, based on the fact that our population was equally distributed and the fact that this cut-off point was also used in a recent large national registry study [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] which included both low and high risk patients with endometrial cancer.\u003c/p\u003e \u003cp\u003eA time interval of at least 8 weeks might seem too long for the prognosis of cancer patients, but it can be explained, if we seek for the reasons of this delay. Three of the largest national registry studies concluded that the two main reasons of treatment delay are: 1) comorbidities \u0026ndash; preoperative medical optimization and 2) referral to centralized high-volume gynecological oncology centers. Most endometrial cancer patients are menopausal (at least over 50 years old), obese with more than one comorbidity, categorize them as high-risk patients for surgery. These patients require a careful preoperative check-up and an established prehabilitation program [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. High volume tertiary cancer centers with longer surgery wait lists should not be viewed as a disadvantage, because a referral to a gynecologic oncologist has a positive impact on the survival of endometrial cancer patients [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. These facts are in accordance with our findings, as the median age of our patients was 64 years old, with a median BMI of 33 and almost half of our patients had moderate comorbidities. Our gynecological oncology unit of a tertiary university hospital has a well-established prehabilitation program which can last up to 4 weeks. So, the waiting time until surgery is counterweighted by the medical optimization of the patients in this period.\u003c/p\u003e \u003cp\u003eConcerning the main endpoint of our study, which was the impact of delay from diagnosis to surgery by setting the cut-off point at 8 weeks. Group A (\u0026le; 8weeks) and Group B (\u0026gt;\u0026thinsp;8weeks) were almost equal (no statistical significance) in terms of population, FIGO stage, surgery duration, ICU admission and hospitalization. However, patients with the longer waiting time (Group B) had a statistically older age, higher BMI and more comorbidities compared to Group A. This can be explained by the fact that older, obese and patients with comorbidities undergo extensive preoperative check-ups and longer prehabilitation programs to improve their preoperative physical performance. Another paradox fact is that patients with longer waiting times have a statistically lower intraoperative blood loss. This is possible explained by the use of advanced bipolar energy from 2017, when also the 4week prehabilitation program was implemented.\u003c/p\u003e \u003cp\u003eFurthermore, after analyzing adjuvant treatments between the two groups, a statistically significant higher (more than double) need for adjuvant pelvic radiotherapy with or without subsequent brachytherapy was found in Group B (\u0026gt;\u0026thinsp;8weeks) patients. After univariate and multivariate analysis for possible confounding factors, delay\u0026thinsp;\u0026gt;\u0026thinsp;8weeks and older age were the only statistically significant factors. Our results are contradicted with the ones from the only study in the literature that analyzes the need of adjuvant treatment [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], where the authors found out that longer time interval between diagnosis and surgery did not increase the need for adjuvant therapy. This could be explained by the fact that our study included both low- and high-risk endometrial cancer patients, while the other authors only looked at low-risk disease.\u003c/p\u003e \u003cp\u003eLast but not least, concerning survival rates, there is no study in the medical bibliography, that correlate the surgery delay to the recurrence rate, disease-free and overall survival. Our data showed that patients with a longer delay from diagnosis to surgery had a statistically significant higher chance of developing a recurrence. On the other hand, no statistical significance was found in the overall survival between the two groups. There are many available data in the literature concerning the mortality of endometrial cancer and the impact of surgery delay. The majority of them show a negative impact of surgery delay on mortality. However, data from national registries [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] should be carefully interpreted, as all authors state that the causes of death were not available in their databases. Data from other high-volume centers are reporting conflicting results. Dolly et al. [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] found that longer wait times (up to 12weeks) had a statistically worse overall survival, while Matsuo et al. [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] showed no correlation with overall survival.\u003c/p\u003e \u003cp\u003eThe main limitation of our study is its retrospective nature and its geographical limitation since it\u0026rsquo;s a single center study. In contrast, the most important strength of our study is the lack of missing data (\u0026lt;\u0026thinsp;5%) and that all consecutive patients irrelevant to their stage and risk factors, were included in the study. This gains even more value in the emerging era of molecular classification [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] and the new FIGO classification [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] where type I and II disease terms are abandoned and patients between low- / high-risk groups are shifting.\u003c/p\u003e"},{"header":"CONCLUSIONS","content":"\u003cp\u003eOlder, obese and multi-morbid patients of endometrial cancer have a higher chance of longer surgery delay, due to need for extensive preoperative examinations and medical optimization. Delaying endometrial cancer surgery over 8 weeks may not have an impact on the mortality of the patients, but increases the need of adjuvant pelvic radiation and worsens recurrence rates. As a result, patients experience more side effects which subsequently worsen their quality of life.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eThe authors whose names are listed above certify that they have NO affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers\u0026rsquo; bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements), or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAUTHOR CONTRIBUTION\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eD. Zouzoulas: Writing \u0026ndash; original draft preparation, Data collection, Data analysis\u003c/p\u003e\n\u003cp\u003eD. Tsolakidis: \u0026nbsp;Conceptualization, Writing \u0026ndash; review and editing, Methodology\u003c/p\u003e\n\u003cp\u003eT. Karalis: \u0026nbsp;Data collection\u003c/p\u003e\n\u003cp\u003eM. Aristotelidis: Data collection\u003c/p\u003e\n\u003cp\u003eM. Topalidou: Resources\u003c/p\u003e\n\u003cp\u003eG. Grimbizis: Validation, Supervision\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eFunding\u003c/strong\u003e:\u003c/em\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eNo funding for this study\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eConflicts of interest\u003c/strong\u003e:\u003c/em\u003e The authors declare that they have no conflict of interest\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e:\u0026nbsp;\u003c/em\u003eAll data is available in the Excel file\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eCode availability\u003c/strong\u003e:\u003c/em\u003e RStudio free software was used\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eJemal A, Bray F, Center MM et al (2011) Global cancer statistics. 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Int J Gynecol Obstet 162:383\u0026ndash;394. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/ijgo.14923\u003c/span\u003e\u003cspan address=\"10.1002/ijgo.14923\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"archives-of-gynecology-and-obstetrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"arch","sideBox":"Learn more about [Archives of Gynecology and Obstetrics](https://www.springer.com/journal/404)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/arch/default.aspx","title":"Archives of Gynecology and Obstetrics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Endometrial cancer, Delay, Adjuvant treatment, Survival rates","lastPublishedDoi":"10.21203/rs.3.rs-3876604/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3876604/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eWhen oncological waiting lists are prolonged, gynecological-oncology units are forced to delay operations, especially for endometrial cancer (EC) due to its good prognosis among gynecological cancers. The aim of this study is to evaluate the impact of delay in the oncological outcomes of these patients.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eRetrospective analysis of all women with EC treated in our clinic, 2012\u0026ndash;2019. Delay was calculated as the time interval between histological diagnosis of endometrial biopsy and definite surgery. The cut-off point was set at 8 weeks. Patients\u0026rsquo; characteristics, treatment options and follow-up information were collected. Primary outcomes were the need of adjuvant treatment and survival rates.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003e259 patients met the inclusion criteria. Based on the 8-week cutoff point patients were divided into two groups: 119 underwent surgery up to 8-weeks (group A) and 140 over 8-weeks (group B). There was no statistical difference in the FIGO stage or the pre-operative CA125 level between the two groups. However, patients in group A were younger, with lower BMI and less comorbidities. Furthermore, patients in group B had a significantly higher probability of receiving pelvic radiation with or without brachytherapy (p\u0026thinsp;=\u0026thinsp;0.0053). Concerning survival rates, there was a statistically difference in disease-free (p\u0026thinsp;=\u0026thinsp;0.0312), but no difference was found in overall survival (p\u0026thinsp;=\u0026thinsp;0.146).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eDelaying EC surgery over 8 weeks may not have an impact on the mortality of the patients, but increases the need of adjuvant pelvic radiation and worsens recurrence rates. As a result, patients experience more side effects which subsequently had negative impact on their quality of life.\u003c/p\u003e","manuscriptTitle":"The Impact of Delay From Diagnosis to Surgeryin Endometrial Cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-13 19:43:23","doi":"10.21203/rs.3.rs-3876604/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2024-03-04T16:20:28+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-02-09T13:18:06+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Archives of Gynecology and Obstetrics","date":"2024-02-08T19:27:49+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-01-18T06:52:48+00:00","index":"","fulltext":""},{"type":"submitted","content":"Archives of Gynecology and Obstetrics","date":"2024-01-17T11:43:50+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"archives-of-gynecology-and-obstetrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"arch","sideBox":"Learn more about [Archives of Gynecology and Obstetrics](https://www.springer.com/journal/404)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/arch/default.aspx","title":"Archives of Gynecology and Obstetrics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"91b108d7-aaf0-48d8-828b-f4840fe811c3","owner":[],"postedDate":"February 13th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-12-09T16:03:36+00:00","versionOfRecord":{"articleIdentity":"rs-3876604","link":"https://doi.org/10.1007/s00404-024-07855-x","journal":{"identity":"archives-of-gynecology-and-obstetrics","isVorOnly":false,"title":"Archives of Gynecology and Obstetrics"},"publishedOn":"2024-12-05 15:57:40","publishedOnDateReadable":"December 5th, 2024"},"versionCreatedAt":"2024-02-13 19:43:23","video":"","vorDoi":"10.1007/s00404-024-07855-x","vorDoiUrl":"https://doi.org/10.1007/s00404-024-07855-x","workflowStages":[]},"version":"v1","identity":"rs-3876604","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3876604","identity":"rs-3876604","version":["v1"]},"buildId":"cTy_lsJlmDsVRNrSptgXS","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}