Prognostic Significance of Muscle Mass in Colorectal Cancer Patients at a Tertiary Cancer Center in the Middle East: A CT Scan-Based Analysis

Prognostic Significance of Muscle Mass in Colorectal Cancer Patients at a Tertiary Cancer Center in the Middle East: A CT Scan-Based Analysis | 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 Article Prognostic Significance of Muscle Mass in Colorectal Cancer Patients at a Tertiary Cancer Center in the Middle East: A CT Scan-Based Analysis Haneen Abaza, Ayat Taqash, Mohammad Abu- Shattal, Fawzi Abuhijla, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4526513/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 06 Sep, 2024 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract Recent reports have shown that pre-treatment low muscle mass may lead to poorer outcomes for cancer patients. We explored the correlation between Visceral Adipose Tissue (VAT), Subcutaneous Adipose Tissue (SAT), and Muscle Mass (MM) as measured by CT scans, and overall survival (OS) following diagnosis of colorectal cancer (CRC). We conducted a retrospective review of medical records and CT scans of patients diagnosed with CRC between 2007–2018. Demographics, pathology, and clinical parameters were collected. Using Image-J software, we measured VAT, SAT, and MM. Survival rates were analyzed using Kaplan-Meier curves, and prognostic factors were assessed using multivariate Cox regression. Analysis included 408 patients with a mean age of 56.9 years and a median follow-up of 93.3 months. Colon and rectum/rectosigmoid colon cancers were equally distributed. The 5-year OS rate was 67.8%. There was no significant difference in OS rates based on SAT or VAT. However, higher MM was associated with a improved 5-year OS rate. Factors such as age, stage, grade, and surgery were also associated to OS rates. These findings suggest that higher muscle mass may lead to better outcomes for CRC patients, highlighting the potential impact of exercise and nutritional interventions on patient outcomes. Biological sciences/Cancer/Gastrointestinal cancer/Colorectal cancer/Colon cancer Biological sciences/Cancer/Gastrointestinal cancer/Colorectal cancer/Rectal cancer Health sciences/Medical research/Outcomes research Health sciences/Risk factors Health sciences/Oncology/Cancer/Cancer imaging Colorectal cancer Middle East Muscle mass Visceral fat Subcutaneous fat Survival CT-based Figures Figure 1 Figure 2 Figure 3 1- Introduction 1.1 Incidence of CRC – Jordan vs. worldwide Colorectal cancer (CRC) ranks as the third most common type of cancer worldwide, accounting for 10.0% of cases according to the latest GLOBCAN statistics ( 1 ). Mortality rates are equal between male and female patients, with both genders accounting for 9.3% and 9.4% of recorded deaths, respectively. The latest report from the Jordan Cancer Registry of 2019 revealed that CRC is the second most prevalent type of cancer in Jordan, accounting for 11.6% of cancer diagnoses, surpassed only by breast cancer (20.3%). Interestingly, CRC appears to affect males more than females, with 13.7% of male cancer cases being CRC compared to 9.7% for females. ( 2 ). In terms of mortality, CRC stands as the second leading cause of cancer-related death in males at 11%, trailing behind lung cancer. Among females, CRC ranks third in terms of mortality at 10.4%, following breast cancer and leukemia ( 2 ). 1.2 Risk factors and BMI Several risk factors have been associated with a higher likelihood of developing CRC, including obesity, physical inactivity, smoking, unhealthy lifestyle, and genetic factors among others ( 3 – 6 ). Body mass index (BMI) is a commonly used measure of body fat calculated based on a person's weight and height (kg/m 2 ) ( 7 ). Although BMI is widely used to measure obesity ( 8 ), it is not an accurate indicator of body fat as it does not account for fat distribution or the weight of bones and muscles ( 9 ). Two types of fat have been linked with obesity; visceral fat and subcutaneous fat, both of which cannot be measured using BMI. Studies have shown that visceral fat, which is the metabolically active form of fat, contributes to the secretion of proinflammatory cytokines and adipokines (tumor necrosis factor and interleukin-6) which induce the high risk of CRC carcinogenesis ( 10 , 11 ). On the other hand, subcutaneous fat is linked to favourable outcome in CRC patients ( 12 ) and can be used as positive metabolic profile for glucose and lipid levels. Unfortunately, BMI cannot distinguish between increased visceral fat, subcutaneous fat, or muscle mass ( 13 ), making it an inadequate tool for assessing cancer risk. While BMI is commonly used in medical practice to assess patient obesity and overall risk, its limitations in accurately assessing body composition make it an imperfect tool for predicting cancer risk. 1.3 CRC and muscle mass Several studies have demonstrated the importance of muscle mass in predicting survival rates and outcomes for CRC patients ( 14 – 16 ). A recent comprehensive review ( 14 ) showed that the frequency of sarcopenia (low muscle mass) in CRC patients ranges between 12% − 60%. Factors associated with sarcopenia can be either patient-related, such as physical inactivity, malnutrition, and body composition, or cancer-related, including weight loss and muscle mass deterioration resulting from treatment ( 17 ). Sarcopenia has also been used as a biomarker to predict chemotherapy tolerance and toxicity in CRC patients ( 17 ) and several studies have used it to predict surgical complications, reduced survival, and poor quality of life in CRC patients ( 18 , 19 ). Patients with low muscle mass are best identified by computed tomography (CT), as it is considered the gold standard method to measure the mass and quality of muscles in addition to other body composition factors ( 20 ). In addition to low muscle mass, elevated levels of fat distribution, particularly abdominal visceral fat, represent significant risk factors in CRC. This is primarily attributed to visceral fat's capability to promote the abdominal tumorigenic environment, thereby increasing the likelihood risk of CRC development through various mechanisms, including enhanced cancer cell proliferation, angiogenesis, and the induction of a protumorigenic microenvironment ( 11 ). Furthermore, visceral fat contributes to systemic chronic inflammation by releasing proinflammatory cytokines and tumour necrosis factor-alpha ( 21 ). 1.4 Aim The objective of this study was to explore how Visceral Adipose Tissue (VAT), Subcutaneous Adipose Tissue (SAT), and Muscle Mass (MM) correlate with overall survival (OS) in colorectal cancer (CRC) patients treated at King Hussein Cancer Center (KHCC), a leading comprehensive cancer center in Jordan. Utilizing CT scans, we measured muscle mass, visceral fat, and subcutaneous fat, and investigated its relationship with demographic variables (such as age and gender) and clinical indicators (including cancer stage, grade, and primary treatment) to patient survival. 2- Materials and Methods We screened a total of 2280 patients with CRC who visited KHCC between 2007 and 2018. Inclusion criteria required patients to have a confirmed diagnosis of CRC regardless of the stage, and an available CT scan at the lower edge of L3 vertebral level before treatment initiation. Patients who had CT scans after treatment interventions, types of cancer other than CRC, CT scans at different levels than L3, or low-quality CT scans were excluded from the study. Patients with missing BMI measures at diagnosis were also excluded. Image-J software (version 1.52a), developed by the U.S. National Institutes of Health (NIH) and available for free in the public domain ( https://imagej.nih.gov/ij/ ), was used to measure the visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), and muscle mass (MM) in square centimeters (cm 2 ) (Fig. 1) . The instructions on how to use ImageJ were followed as mentioned in the instruction manual ( 22 ). Three physicians were trained to measure VAT, SAT, and MM from the CT scans using the same ImageJ version and measuring technique. The threshold values applied to measure the CT scans were determined through visual inspection and experimentation with different thresholds until optimal separation of VAT, SAT, and MM was achieved. Demographic, pathological, and clinical parameters were collected for the patients. Additionally, height and weight at diagnosis were collected to calculate BMI. To evaluate the agreement and reproducibility among the measurements obtained by the three physicians, 78 CT scans were independently measured three times by different physicians. Subsequently, the intraclass correlation coefficient (ICC) was calculated to evaluate the consistency among the measurements obtained by the three physicians. Receiver Operating Characteristic (ROC) curves were generated to determine cutoff points for VAT, SAT, and MM based on gender. Survival rates were estimated using the Kaplan-Meier method and compared between groups using the Log-rank test. Multivariate Cox regression was used to assess prognostic factors. A significance criterion of P ≤ 0.05 was used in the analysis, and all analyses were performed using SAS version 9.4 (SAS Institute Inc, Cary, NC). The data collected in this study adhered to HIPAA-compliant standards and was ethically approved by the Institutional Review Board (IRB) at KHCC (study number: 17 KHCC 99). Informed consent was waived due to retrospective nature of study design. 3- Results 3.1 Agreement and reproducibility: The results of the two-way mixed effects, absolute agreement ICC for VAT, SAT, and MM were 0.88, 0.76, and 0.75, respectively, with a 95% confidence interval (CI) (Table 1 ). ICC values exceeding 0.70 indicate good reliability ( 23 ). These findings suggest that the measurements obtained by the three physicians were consistent and reproducible. Table 1 Intra-class Correlation Coefficient (ICC): two-way mixed effects for absolute agreement 95% Confidence Interval Reading ICC Lower bound Upper bound Visceral adipose tissue 0.86 0.82 0.92 Subcutaneous adipose tissue 0.76 0.64 0.84 Muscle mass 0.75 0.63 0.83 3.2 Descriptive analysis: Of 2280 screened CRC patients, 408 patients diagnosed at KHCC between 2007 and 2018 met our inclusion criteria and were included in the analysis. The mean age at diagnosis was 56.9 ± 13.2 (± SD) years, median follow-up was 93.3 months (range: 40.9–182), and 233 (57.1%) were male patients. Of these patients, 216 (52.9%) had colon cancer and 192 (47.1%) had rectum or rectosigmoid cancer. A total of 350 (85.8%) patients’ cancers were grade 1 or 2. Of the measured CT scans, 210 (51.5%) patients had high VAT, 188 (46.1%) had high SAT, and 228 (55.9%) had high MM. Table 2 shows the descriptive analysis of the demographic of CRC in the sample cohort. Table 2 Descriptive analysis for demographic and clinical outcomes Variable Value N (%) Gender Female 175 (42.9%) Male 233 (57.1%) Age at diagnosis 50–59 101 (24.8%) 60–69 107 (26.2%) 70 75 (18.4%) < 50 125 (30.6%) Median (min-max) 58 (92–21) BMI (cut off 25) Obese /Overweight 289 (70.83%) Underweight/Normal 119 (29.2%) Site Group Colon 216 (52.9%) Rectum / Rectosigmoid 192 (47.1%) Grade G1 16 (3.92%) G2 334 (81.86%) G3 43 (10.54%) G4 2 (0.5%) Unknown 13 (3.19%) TNM Stage Group I 20 (4.9%) II 93 (22.8%) III 175 (42.9%) IV 113 (27.7%) NA 7 (1.7%) Surgery No 112 (27.5%) Yes 296 (72.5%) Radiotherapy No 283 (63.4%) Yes 125 (31.4%) Chemotherapy No 34 (8.3%) Yes 374 (91.7%) VAT cutoff High 210 (51.5%) Low 198 (48.5%) Median (min-max) 210.9 (12.8–682.7) SAT cutoff High 188 (46.1%) Low 220 (53.9%) Median (min-max) 268.1 (7.4–839.4) MM cutoff High 228 (55.9%) Low 180 (44.1%) Median (min-max) 190.5 (69.0–395.8) Follow-up (Months) N = 263 Mean (± SD) 96.5 (± 36) Median (min-max) 93.3( 40.9–182) Table 3 summarizes the cut-off points for the area under the curve (AUC) for MM, VAT and SAT, stratified according to gender. The ROC curves are for MM, VAT and SAT for male and females are represented in the supplementary materials (Figs. 1s- 6s ). Table 3 AUC cut off points for MM, VAT and SAT, stratified according to gender: Variable Gender Cutoff point AUC MM Male 245.141 55.91% Female 131.479 60.43% VF Male 218.351 55.99% Female 179.858 56.86% SCF Male 250.019 55.77% Female 325.92 50.45% 3.3. Survival analysis: At the follow-up time in March 2022, 145 patients (35.4%) of the patients had died. The median survival of the entire cohort was 96.3 months (95% CI 63.1, 72.2) and the 5-year OS rate was 67.8% (Fig. 2) . Patients who had surgery had a higher survival rate compared with those who did not have surgery (80.7% vs 33.6% P < 0.0001). Tumors of grades 1 and 2 were compared with tumors of grades 3 and 4 and showed a significantly better survival rate (71.0% vs. 46.7% P = 0.0015). Additionally, significant differences in survival rates between age groups and TNM stages were observed ( P = 0.0014 and P < 0.0001 respectively) (Table 4 ). Table 4 Univariate Analysis of 5-Year OS in CRC Patients Variable Value 5-year OS rate (95% CI) P-value VAT High 67.9 (61.4, 74.1) 0.6351 Low 67.6 (61.9, 73.9) SAT High 67.9 (61.9, 74.4) 0.742 Low 67.6 (61.2, 73.6) MM High 71.8 (65.8, 77.5) 0.0224 Low 62.7 (55.5, 69.6) TNM stage I 95.0 (81.5, 100.0) < 0.0001 II 88.2 (80.8, 93.9) III 76.8 (70.2, 82.8) IV 32.7 (24.4, 41.6) Surgery No 33.6 (25.2, 42.7) < 0.0001 Yes 80.7 (76.0, 85.0) Age at diagnosis =70 53.0 (41.7, 64.2) Grade G1,G2 71.0 (66.1, 75.6) 0.0015 G3,G4 46.7 (32.4, 61.2) High MM was associated with a better 5-year overall survival rate in CRC patients (71.8% vs. 62.7%, P = 0.0224) (Fig. 3) . In contrast, SAT and VAT were not associated with OS when comparing high to low values (67.9% vs 67.6% P = 0.74), (67.9% vs 67.6%, P = 0.6351), respectively. Moreover, there was no association between BMI and cancer site groups and OS ( P = 0.6085, P = 0.5062, and P = 0.5793 respectively) ( Table 4 ) . Using a multivariate Cox regression adjusting for age, stage, grade, surgery, VAT, SAT, and MM, no significant association was observed for VAT, SAT, or grade with a five-year OS rate (P = 0.474, 0.863, 0.101 respectively). However, there was an association between age, stage, surgery, and MM with a five-year OS rate (P = 0.016, < 0.0001, 0.0001, 0.040 respectively) ( Table 5 ) . Table 5 Multivariate Cox Regression Analysis for CRC Patients Variable Value Hazard Ratio Hazard Ratio (95% Confidence) P-value Adjusted P-value TNM Stage I vs. IV 0.052 0.007 0.389 0.004 < .0001 II vs. IV 0.193 0.102 0.365 < .0001 III vs. IV 0.291 0.191 0.443 < .0001 Surgery Yes vs. No 0.447 0.297 0.674 0.0001 0.0001 Age at diagnosis 1.02 1.004 1.037 0.0162 0.0162 MM High vs. low 0.997 0.994 1 0.0397 0.0397 VAT High vs. low 1.001 0.999 1.003 0.4738 0.4738 SAT High vs. low 1 0.999 1.001 0.8633 0.8633 Grade G1,G2 vs. G3,G4 0.677 0.425 1.079 0.101 0.101 4- Discussion In this study, we investigated the relationship between Visceral Adipose Tissue (VAT), Subcutaneous Adipose Tissue (SAT), and Muscle Mass (MM) measured using CT scans with OS in CRC patients treated at KHCC in Jordan. Our findings showed a significant association between high muscle mass and improved OS rates in CRC patients, aligning with previous research emphasizing the positive impact of increased MM on survival outcomes in cancer patients ( 24 – 26 ). This analysis revealed that OS in CRC patients was influenced by multiple predictive factors, including surgical intervention, tumour grade, TNM stage, and age at diagnosis, all of which demonstrated significant associations with survival outcomes ( 27 , 28 ). The 5-years OS rate of 67.8% (95% CI 63.1–72.2) of our population was similar to other studies conducted in Brazil 63.5% ( 29 ) and a population-based study in 9 European countries 71·1% (95% CI 70·7–71·4) ( 30 ) which can be attributed to similarities in the high level of quality of care provided to CRC patients. A previously published study utilizing data from the Jordan’s cancer registry during the period of 2005–2010 reported a 5-years OS of 58.2% for CRC patients ( 31 ). The notable increase in survival rates between their study and our findings suggests positive progress in the level of care and advancements in treatment modalities over time. To accurately measure MM, VAT, and SAT, our study employed a CT scan-based method ( 32 ) using ImageJ software. Three independent physicians measured the images to ensure data accuracy and reliability. A study conducted in biliary duct cancer patients showed that high MM was associated with a high survival rate (HR 0.46, 95% CI 0.22–0.95, P = 0.037) ( 24 ) which is similar to our results (HR 0.997, 95% CI 0.994–1, P = 0.0397). Another meta-analysis ( 26 ) on rectal cancer patients with sarcopenia showed a poor survival rate (HR 2.10, 95% CI 1.33–3.32, P = 0.001) compared to patients with high MM, which is in line with our results that high muscle mass provides survival benefit for patients with CRC. Based on our knowledge and existing literature highlighting the adverse effects of VAT in the abdominal region, we explored the association between VAT and OS in CRC patients. Interestingly, our findings indicated no significant impact of high VAT (HR 1.001, 95% CI 1.003–0.4738, P = 0.4738) on OS, similar to results from a study on Korean CRC patients (HR 0.656; 95% CI 0.402–1.071; P = 0.092) ( 33 ). However, this is contrary to other studies reporting a significant association between increased VAT (HR 2.61, 95% CI 1.155–5.924, P = 0.020) and poor survival outcomes ( 34 , 35 ). We also investigated the association between SAT and OS in CRC patients, and our findings did not indicate a significance on OS (HR 1.000, 95% CI 0.999–1.001, P = 0.8633). Our results are similar to the above-mentioned study ( 34 ), (HR 1.18, 95% CI 0.614–2.036, P = 0.715) but contrary to the study on Korean CRC patients among other studies (HR 0.505, 95% CI 0.266–0.957; P = 0.036) ( 33 , 35 ). This discrepancy may be attributable to the relatively small sample size and the heterogeneity of the CRC patient population in our study. Genetic factors specific to the Middle Eastern population may also contribute to this variation ( 4 , 5 ). These include IL-17 polymorphisms which play a crucial role in inflammation, and autoimmune diseases and are responsible for CRC growth and invasion ( 4 , 36 ). Moreover, CRC driver mutations like RAS and BRAF mutations vary in their prevalence in Middle Eastern compared to Western countries ( 6 , 37 ). However, this data was not available for the population of patients we studied and further research is needed to study these variable and their interplay with body composition and effect on CRC outcome. Additionally, we rigorously controlled for potential confounding factors such as age at diagnosis, gender, tumour grade, and TNM stage, enhancing the validity and reliability of our findings. Our findings in the multivariate analysis revealed that only the age at diagnosis, TNM stage group, surgery, and MM were significant independent predictors of the patient’s survival. Our results are similar to findings in other Middle Eastern populations ( 38 , 39 ) and analyses based on the SEER database ( 40 ). Tumour grade did not emerge as a significant predictor of CRC survival in multivariate analysis, which is contrary to other published research in Western populations like the US and Canada using their National Cancer Database ( 41 ) and Eastern populations such as Korean CRC patients ( 42 ). It is important to ( 17 ) acknowledge the limitations of our study, primarily due to its retrospective design which resulted in missing data that could contribute important insights to the question of body composition and its association with CRC outcome. This includes the absence of lifestyle data encompassing physical activity and diet, both of which have the potential to impact body composition, fat, and muscle distribution, and could be associated with OS in CRC patients ( 43 , 44 ), in addition to their role in cancer prevention ( 45 ). Unfortunately, these data were not present in our electronic medical records at the time of diagnosis nor during the patient’s treatment course. Future research with larger sample sizes and more diverse patient cohorts is needed to better understand the association between body composition and CR outcome. Such studies would help validate our findings and elucidate the underlying mechanisms involved, thereby informing clinical practice to improve CRC outcomes and enhance the quality of life for patients. Additionally, investigations exploring genetic factors and genetic variations across different populations may help to answer questions specific to the Middle Eastern population and provide further insights into the relationship between body composition and survival outcomes in CRC patients. 5- Conclusion This study provides evidence supporting the association between high muscle mass and improved OS rates in CRC patients. Additionally, TNM stage, surgical intervention, and age at diagnosis were identified as significant independent predictors of OS. Notably, VAT and SAT did not demonstrate a significant association with OS. These findings highlight the importance of assessing body composition, especially muscle mass as a valuable prognostic indicator in CRC patients. Furthermore, integrating routine physical activity and promoting healthy lifestyle habits in the management of CRC patients hold potential benefits. Future studies can explore the impact of exercise and nutritional interventions on body composition and OS rates, contributing to the development of comprehensive treatment strategies. In addition, nutritional counselling can be a crucial aspect of CRC patient care. Exploring the effects of tailored nutritional interventions, including increased protein intake, on body composition and muscle mass, OS rates, and quality of life, can provide valuable insights into optimizing patient outcomes. By addressing these areas, we can emphasize the significance of physical activity and healthy lifestyle choices, and incorporate nutritional counselling into the comprehensive care of CRC patients. These factors can have the potential to advance the field and contribute to improved survival rates, enhanced quality of life, and better overall outcomes for individuals with CRC. Declarations Acknowledgments Funding: This research was supported by funds from the Intramural Research Grants Program at King Hussein Cancer Center (Award Number: 17 KHCC 99). Institutional Review Board Statement: This study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Institutional Review Board of King Hussein Cancer Center (Study Number: 17 KHCC 99). Data Availability Statement: The data that support the findings of this study are available upon reasonable request from the corresponding author (A.A). Competing Interest: The authors declare no competing interests. Authors contribution: Conceptualization: (A.A), (M.A.S). Methodology: (A.A), (H.A), (M.A.S). Writing – Original Draft: (H.A). Writing – Review & Editing: (H.A), (A.A), (A.T), (F.A). Data collection: (H.A), (M.A.S), (F.A), (K.A.J), (Z.A.J), (O.A). Formal statistical analysis: (A.T). Data management: (H.A.K). All authors have critically revised the manuscript for important intellectual content, approved the final version to be published, and agreed to be accountable for all aspects of the work. All authors have read and agreed to the published version of the manuscript. References Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA: A Cancer Journal for Clinicians. 2021;71(3):209 – 49. Health JMo. Cancer Incidence in Jordan. Cancer Incidence in Jordan. Jordan2018. p. 45. Lewandowska A, Rudzki G, Lewandowski T, Stryjkowska-Góra A, Rudzki S. Title: Risk Factors for the Diagnosis of Colorectal Cancer. Cancer Control. 2022;29:10732748211056692. Al Obeed OA, Vaali-Mohamed MA, Alkhayal KA, Bin Traiki TA, Zubaidi AM, Arafah M, et al. IL-17 and colorectal cancer risk in the Middle East: gene polymorphisms and expression. Cancer Manag Res. 2018;10:2653–61. Oukkal M, Bouzid K, Bounedjar A, Alnajar A, Taleb FA, Alsharm A, et al. Middle East and North Africa Registry to Characterize Rate of RAS Testing Status in Newly Diagnosed Patients with Metastatic Colorectal Cancer. Turk J Gastroenterol. 2023;34(2):118–27. Garawin T, Lowe K, Kafatos G, Murray S. The prevalence RAS and BRAF mutations among patients in the Middle East and Northern Africa with metastatic colorectal cancer. Journal of Clinical Oncology. 2016;34(15_suppl):e15077-e. Shaukat A, Dostal A, Menk J, Church TR. BMI Is a Risk Factor for Colorectal Cancer Mortality. Dig Dis Sci. 2017;62(9):2511–7. Simillis C, Taylor B, Ahmad A, Lal N, Afxentiou T, Powar MP, et al. A systematic review and meta-analysis assessing the impact of body mass index on long-term survival outcomes after surgery for colorectal cancer. European Journal of Cancer. 2022;172:237–51. Humphreys S. The unethical use of BMI in contemporary general practice. Br J Gen Pract. 2010;60(578):696–7. Donohoe CL, Doyle SL, Reynolds JV. Visceral adiposity, insulin resistance and cancer risk. Diabetol Metab Syndr. 2011;3:12. Lee JY, Lee HS, Lee DC, Chu SH, Jeon JY, Kim NK, et al. Visceral fat accumulation is associated with colorectal cancer in postmenopausal women. PLoS One. 2014;9(11):e110587. Kim JM, Chung E, Cho ES, Lee JH, Shin SJ, Lee HS, et al. Impact of subcutaneous and visceral fat adiposity in patients with colorectal cancer. Clin Nutr. 2021;40(11):5631–8. Shuster A, Patlas M, Pinthus JH, Mourtzakis M. The clinical importance of visceral adiposity: a critical review of methods for visceral adipose tissue analysis. Br J Radiol. 2012;85(1009):1–10. Vergara-Fernandez O, Trejo-Avila M, Salgado-Nesme N. Sarcopenia in patients with colorectal cancer: A comprehensive review. World J Clin Cases. 2020;8(7):1188–202. van Roekel EH, Bours MJL, Te Molder MEM, Breedveld-Peters JJL, Olde Damink SWM, Schouten LJ, et al. Associations of adipose and muscle tissue parameters at colorectal cancer diagnosis with long-term health-related quality of life. Qual Life Res. 2017;26(7):1745–59. Meyer HJ, Strobel A, Wienke A, Surov A. Prognostic Role of Low-Skeletal Muscle Mass on Staging Computed Tomography in Metastasized Colorectal Cancer: A Systematic Review and Meta-Analysis. Clin Colorectal Cancer. 2022;21(3):e213-e25. Cespedes Feliciano EM, Avrutin E, Caan BJ, Boroian A, Mourtzakis M. Screening for low muscularity in colorectal cancer patients: a valid, clinic-friendly approach that predicts mortality. Journal of Cachexia, Sarcopenia and Muscle. 2018;9(5):898–908. Tsaousi G, Kokkota S, Papakostas P, Stavrou G, Doumaki E, Kotzampassi K. Body composition analysis for discrimination of prolonged hospital stay in colorectal cancer surgery patients. European Journal of Cancer Care. 2017;26(6):e12491. Heus C, Cakir H, Lak A, Doodeman HJ, Houdijk APJ. Visceral obesity, muscle mass and outcome in rectal cancer surgery after neo-adjuvant chemo-radiation. International Journal of Surgery. 2016;29:159–64. ÉB NB, Daly LE, Power DG, Cushen SJ, MacEneaney P, Ryan AM. Computed tomography diagnosed cachexia and sarcopenia in 725 oncology patients: is nutritional screening capturing hidden malnutrition? J Cachexia Sarcopenia Muscle. 2018;9(2):295–305. Dusserre E, Moulin P, Vidal H. Differences in mRNA expression of the proteins secreted by the adipocytes in human subcutaneous and visceral adipose tissues. Biochim Biophys Acta. 2000;1500(1):88–96. Gomez-Perez SL, Haus JM, Sheean P, Patel B, Mar W, Chaudhry V, et al. Measuring Abdominal Circumference and Skeletal Muscle From a Single Cross-Sectional Computed Tomography Image: A Step-by-Step Guide for Clinicians Using National Institutes of Health ImageJ. JPEN J Parenter Enteral Nutr. 2016;40(3):308–18. Koo TK, Li MY. A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research. Journal of chiropractic medicine. 2016;15(2):155–63. Limpawattana P, Theerakulpisut D, Wirasorn K, Sookprasert A, Khuntikeo N, Chindaprasirt J. The impact of skeletal muscle mass on survival outcome in biliary tract cancer patients. PLoS One. 2018;13(10):e0204985. Lopez P, Newton RU, Taaffe DR, Singh F, Buffart LM, Spry N, et al. Associations of fat and muscle mass with overall survival in men with prostate cancer: a systematic review with meta-analysis. Prostate Cancer and Prostatic Diseases. 2022;25(4):615–26. Zhu Y, Guo X, Zhang Q, Yang Y. Prognostic value of sarcopenia in patients with rectal cancer: A meta-analysis. PLOS ONE. 2022;17(6):e0270332. Joachim C, Macni J, Drame M, Pomier A, Escarmant P, Veronique-Baudin J, et al. Overall survival of colorectal cancer by stage at diagnosis: Data from the Martinique Cancer Registry. Medicine. 2019;98(35):e16941. Andreoni B, Chiappa A, Bertani E, Bellomi M, Orecchia R, Zampino M, et al. Surgical outcomes for colon and rectal cancer over a decade: results from a consecutive monocentric experience in 902 unselected patients. World J Surg Oncol. 2007;5:73. Aguiar Junior S, Oliveira MM, Silva D, Mello CAL, Calsavara VF, Curado MP. SURVIVAL OF PATIENTS WITH COLORECTAL CANCER IN A CANCER CENTER. Arq Gastroenterol. 2020;57(2):172–7. Cardoso R, Guo F, Heisser T, De Schutter H, Van Damme N, Nilbert MC, et al. Overall and stage-specific survival of patients with screen-detected colorectal cancer in European countries: A population-based study in 9 countries. The Lancet Regional Health - Europe. 2022;21:100458. Sharkas GF, Arqoub KH, Khader YS, Tarawneh MR, Nimri OF, Al-zaghal MJ, et al. Colorectal Cancer in Jordan: Survival Rate and Its Related Factors. Journal of Oncology. 2017;2017:3180762. Goulart A, Malheiro N, Rios H, Sousa N, Leão P. Influence of Visceral Fat in the Outcomes of Colorectal Cancer. Dig Surg. 2019;36(1):33–40. Kim J-M, Chung E, Cho E-S, Lee J-H, Shin S-J, Lee HS, et al. Impact of subcutaneous and visceral fat adiposity in patients with colorectal cancer. Clinical Nutrition. 2021;40(11):5631–8. Basile D, Bartoletti M, Polano M, Bortot L, Gerratana L, Di Nardo P, et al. Prognostic role of visceral fat for overall survival in metastatic colorectal cancer: A pilot study. Clinical Nutrition. 2021;40(1):286–94. Park JW, Chang SY, Lim JS, Park SJ, Park JJ, Cheon JH, et al. Impact of Visceral Fat on Survival and Metastasis of Stage III Colorectal Cancer. Gut Liver. 2022;16(1):53–61. Kolls JK, Lindén A. Interleukin-17 family members and inflammation. Immunity. 2004;21(4):467–76. Saharti S. KRAS/NRAS/BRAF Mutation Rate in Saudi Academic Hospital Patients With Colorectal Cancer. Cureus. 2022;14(4):e24392. Alyabsi M, Sabatin F, Ramadan M, Jazieh AR. Colorectal cancer survival among Ministry of National Guard-Health Affairs (MNG-HA) population 2009–2017: retrospective study. BMC Cancer. 2021;21(1):954. Zare-Bandamiri M, Khanjani N, Jahani Y, Mohammadianpanah M. Factors Affecting Survival in Patients with Colorectal Cancer in Shiraz, Iran. Asian Pac J Cancer Prev. 2016;17(1):159–63. Xie Y, Huang Y, Ruan Q, Wang H, Liang X, Hu Z, et al. Impact of Tumor Site on Lymph Node Status and Survival in Colon Cancer. Journal of Cancer. 2019;10(11):2376–83. Alese OB, Zhou W, Jiang R, Zakka K, Huang Z, Okoli C, et al. Predictive and Prognostic Effects of Primary Tumor Size on Colorectal Cancer Survival. Front Oncol. 2021;11:728076. Lee JM, Han YD, Cho MS, Hur H, Min BS, Lee KY, et al. Impact of tumor sidedness on survival and recurrence patterns in colon cancer patients. Ann Surg Treat Res. 2019;96(6):296–304. Yun Z, Hao W, Peizhong Peter W, Sevtap S, Jennifer W, Tyler W, et al. Dietary patterns and colorectal cancer recurrence and survival: a cohort study. BMJ Open. 2013;3(2):e002270. Dashti SG, Win AK, Hardikar SS, Glombicki SE, Mallenahalli S, Thirumurthi S, et al. Physical activity and the risk of colorectal cancer in Lynch syndrome. Int J Cancer. 2018;143(9):2250–60. Chan AT, Giovannucci EL. Primary prevention of colorectal cancer. Gastroenterology. 2010;138(6):2029-43.e10. Additional Declarations No competing interests reported. Supplementary Files Figure1sROCCurvefemaleMM.png Figure 1s: ROC curve for muscle mass in female. Figure2sROCCurvemaleMM.png Figure 2s: ROC curve for muscle mass male. Figure3sROCCurveFemaleVF.png Figure 3s: ROC curve for visceral adipose tissue in female. Figure4sROCCurvemaleVF.png Figure 4s: ROC curve for visceral adipose tissue in male. Figure5sROCCurvefemaleSCF.png Figure 5s: ROC curve for subcutaneous adipose tissue in female. Figure6sROCCurvemaleSCF.png Figure 6s: ROC curve for subcutaneous adipose tissue in male. Cite Share Download PDF Status: Published Journal Publication published 06 Sep, 2024 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 13 Jun, 2024 Reviews received at journal 09 Jun, 2024 Reviewers agreed at journal 09 Jun, 2024 Reviews received at journal 09 Jun, 2024 Reviewers agreed at journal 09 Jun, 2024 Reviewers invited by journal 08 Jun, 2024 Editor assigned by journal 07 Jun, 2024 Editor invited by journal 07 Jun, 2024 Submission checks completed at journal 05 Jun, 2024 First submitted to journal 04 Jun, 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. 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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-4526513","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":314141467,"identity":"7baa3c1c-c571-4520-9fc3-48c3047ba54c","order_by":0,"name":"Haneen Abaza","email":"","orcid":"","institution":"King Hussein Cancer Center","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Haneen","middleName":"","lastName":"Abaza","suffix":""},{"id":314141468,"identity":"9f8b809e-635a-400e-9334-c14b7fb0323b","order_by":1,"name":"Ayat Taqash","email":"","orcid":"","institution":"King Hussein Cancer Center","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ayat","middleName":"","lastName":"Taqash","suffix":""},{"id":314141469,"identity":"eb1405b2-c080-4082-afcd-f1a1de267f61","order_by":2,"name":"Mohammad Abu- Shattal","email":"","orcid":"","institution":"King Hussein Cancer Center","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Mohammad","middleName":"Abu-","lastName":"Shattal","suffix":""},{"id":314141470,"identity":"70b17ce4-b0d3-4179-ba27-22bffaf1e0c5","order_by":3,"name":"Fawzi Abuhijla","email":"","orcid":"","institution":"King Hussein Cancer Center","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Fawzi","middleName":"","lastName":"Abuhijla","suffix":""},{"id":314141472,"identity":"38546e2d-3472-4551-a963-1dceeb508f88","order_by":4,"name":"Hadeel Abdel-Khaleq","email":"","orcid":"","institution":"King Hussein Cancer Center","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Hadeel","middleName":"","lastName":"Abdel-Khaleq","suffix":""},{"id":314141474,"identity":"ac3bdd83-cd3e-4c40-ab2a-1ea22f0c169c","order_by":5,"name":"Omar Awadallah","email":"","orcid":"","institution":"Jordan University Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Omar","middleName":"","lastName":"Awadallah","suffix":""},{"id":314141477,"identity":"924a68be-0784-4d67-9db8-848c1b5de857","order_by":6,"name":"Khaled Al-Ja’fari","email":"","orcid":"","institution":"Jordan Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Khaled","middleName":"","lastName":"Al-Ja’fari","suffix":""},{"id":314141478,"identity":"76aad2d2-0535-469d-8a99-4c9ef1ffd24d","order_by":7,"name":"Zaid Al-Ja’fari","email":"","orcid":"","institution":"Istiklal Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Zaid","middleName":"","lastName":"Al-Ja’fari","suffix":""},{"id":314141480,"identity":"e0365e29-53de-413f-852e-bdb50bd08ca4","order_by":8,"name":"Amal Al-Omari","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAArklEQVRIiWNgGAWjYPACCTkJCRDNQ4IWY5K1MCTOkCBWKX//4aMbfu6xSJ85u/nhBwYZGyJcdCMt7WbPM4nc2TLHjCUYeNKIsOYGj9kNngMSufMkctiAfjlMWIf8+TNmN/8ckEiXI1qLwYEcs9tAWxKkidZiCPTLbZkDEoYzZ6QZSyQQ4xe584eP3XxzoE5e4kbyww8fe4gIMVSQ2EOqDgaGH6RrGQWjYBSMguEPAJNnNZiWEGyXAAAAAElFTkSuQmCC","orcid":"","institution":"King Hussein Cancer Center","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Amal","middleName":"","lastName":"Al-Omari","suffix":""}],"badges":[],"createdAt":"2024-06-04 08:46:32","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4526513/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4526513/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-024-68503-7","type":"published","date":"2024-09-06T16:05:10+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":59118875,"identity":"61460f91-911f-47a9-81ff-035cc2268196","added_by":"auto","created_at":"2024-06-26 14:32:49","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2226697,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCT scans for CRC patients at the lower edge of L3 level, at different thresholds using ImageJ:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA. CT scan of CRC patient at lower edge of L3 level.\u003c/p\u003e\n\u003cp\u003eB. The area in red is the fat (visceral and subcutaneous) after setting the threshold between (10-90). The visceral fat was selected and measured at the indicated threshold.\u003c/p\u003e\n\u003cp\u003eC. Visceral fat was cut out, leaving subcutaneous fat alone to be measured at the same threshold (10-90).\u003c/p\u003e\n\u003cp\u003eD. The area in red is the muscle area after setting the threshold between (90-170). The area was selected and measured at the indicated threshold.\u003c/p\u003e","description":"","filename":"OnlineFigure1CT.png","url":"https://assets-eu.researchsquare.com/files/rs-4526513/v1/731a3032b647eb9f5d9937ef.png"},{"id":59121565,"identity":"ee434901-b353-4912-8969-4607f39589e0","added_by":"auto","created_at":"2024-06-26 14:56:49","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":81539,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKaplan-Meier plot demonstrating 5-year OS probability for CRC patients.\u003c/strong\u003e The 5-year OS rate for CRC is 67.8% (\u003cstrong\u003e95% CI\u003c/strong\u003e 63.1 - 72.2). Of the entire cohort, 263 CRC patients were alive at follow-up time (64.5%).\u003c/p\u003e","description":"","filename":"OnlineFigure2overallsurvival.png","url":"https://assets-eu.researchsquare.com/files/rs-4526513/v1/237682f2a2be56b96dc05f49.png"},{"id":59118880,"identity":"9453b03d-701e-4348-ab3d-e69fc341b7e9","added_by":"auto","created_at":"2024-06-26 14:32:49","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":85221,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKaplan-Meier plot demonstrating OS probability for CRC patients stratified by MM, high vs. low\u003c/strong\u003e. The 5-year OS rate for CRC patients with high muscle mass was 71.8% (95% CI 65.8 - 77.5) and for patients with low muscle mass 62.7% (95% CI 55.5 - 69.6), p-value= 0.02.\u003c/p\u003e","description":"","filename":"OnlineFigure3OSMM.png","url":"https://assets-eu.researchsquare.com/files/rs-4526513/v1/1907b87bffbe2636dcca485b.png"},{"id":64185731,"identity":"6d5b5e0a-7bae-4013-9b70-17b9368214ef","added_by":"auto","created_at":"2024-09-09 16:21:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3896745,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4526513/v1/ebbeae81-019c-4873-9e40-34bb8a5273c9.pdf"},{"id":59119638,"identity":"0514f4db-b135-4fd0-be0e-3000e2e45d09","added_by":"auto","created_at":"2024-06-26 14:40:49","extension":"png","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":13326,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 1s: ROC curve for muscle mass in female.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure1sROCCurvefemaleMM.png","url":"https://assets-eu.researchsquare.com/files/rs-4526513/v1/18420859f251c1a643b66a9d.png"},{"id":59120741,"identity":"a07a25cd-56ed-4d54-865c-26dfc939fc8d","added_by":"auto","created_at":"2024-06-26 14:48:49","extension":"png","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":13908,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 2s: ROC curve for muscle mass male.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure2sROCCurvemaleMM.png","url":"https://assets-eu.researchsquare.com/files/rs-4526513/v1/c63f80a4e02a02ee114089bd.png"},{"id":59119641,"identity":"45506c8c-51c8-4cf1-ab9b-04779e08c46a","added_by":"auto","created_at":"2024-06-26 14:40:49","extension":"png","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":13521,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 3s: ROC curve for visceral adipose tissue in female.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure3sROCCurveFemaleVF.png","url":"https://assets-eu.researchsquare.com/files/rs-4526513/v1/1ea8484f2b773121371e6220.png"},{"id":59119642,"identity":"e4ae3b37-b1d7-4f3a-ac7c-14730caf41f9","added_by":"auto","created_at":"2024-06-26 14:40:49","extension":"png","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":14072,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 4s: ROC curve for visceral adipose tissue in male.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure4sROCCurvemaleVF.png","url":"https://assets-eu.researchsquare.com/files/rs-4526513/v1/e7ad4ef62cd1034a2f3d3cfb.png"},{"id":59118878,"identity":"24097c1d-ba43-4eb2-8f0c-466a5365a9af","added_by":"auto","created_at":"2024-06-26 14:32:49","extension":"png","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":13751,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 5s: ROC curve for subcutaneous adipose tissue in female.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure5sROCCurvefemaleSCF.png","url":"https://assets-eu.researchsquare.com/files/rs-4526513/v1/85087bdbc52b00706e8fcfef.png"},{"id":59118883,"identity":"c36e5c8a-88a1-41ce-a948-60db7e7ed9ad","added_by":"auto","created_at":"2024-06-26 14:32:50","extension":"png","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":14211,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 6s: ROC curve for subcutaneous adipose tissue in male.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure6sROCCurvemaleSCF.png","url":"https://assets-eu.researchsquare.com/files/rs-4526513/v1/c4163697de3aaa3bf866c7f4.png"}],"financialInterests":"No competing interests reported.","formattedTitle":"Prognostic Significance of Muscle Mass in Colorectal Cancer Patients at a Tertiary Cancer Center in the Middle East: A CT Scan-Based Analysis","fulltext":[{"header":"1- Introduction","content":"\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003e1.1 Incidence of CRC \u0026ndash; Jordan vs. worldwide\u003c/h2\u003e \u003cp\u003eColorectal cancer (CRC) ranks as the third most common type of cancer worldwide, accounting for 10.0% of cases according to the latest GLOBCAN statistics (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Mortality rates are equal between male and female patients, with both genders accounting for 9.3% and 9.4% of recorded deaths, respectively.\u003c/p\u003e \u003cp\u003eThe latest report from the Jordan Cancer Registry of 2019 revealed that CRC is the second most prevalent type of cancer in Jordan, accounting for 11.6% of cancer diagnoses, surpassed only by breast cancer (20.3%). Interestingly, CRC appears to affect males more than females, with 13.7% of male cancer cases being CRC compared to 9.7% for females. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). In terms of mortality, CRC stands as the second leading cause of cancer-related death in males at 11%, trailing behind lung cancer. Among females, CRC ranks third in terms of mortality at 10.4%, following breast cancer and leukemia (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e1.2 Risk factors and BMI\u003c/h2\u003e \u003cp\u003eSeveral risk factors have been associated with a higher likelihood of developing CRC, including obesity, physical inactivity, smoking, unhealthy lifestyle, and genetic factors among others (\u003cspan additionalcitationids=\"CR4 CR5\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBody mass index (BMI) is a commonly used measure of body fat calculated based on a person's weight and height (kg/m\u003csup\u003e2\u003c/sup\u003e) (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Although BMI is widely used to measure obesity (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e), it is not an accurate indicator of body fat as it does not account for fat distribution or the weight of bones and muscles (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Two types of fat have been linked with obesity; visceral fat and subcutaneous fat, both of which cannot be measured using BMI. Studies have shown that visceral fat, which is the metabolically active form of fat, contributes to the secretion of proinflammatory cytokines and adipokines (tumor necrosis factor and interleukin-6) which induce the high risk of CRC carcinogenesis (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). On the other hand, subcutaneous fat is linked to favourable outcome in CRC patients (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e) and can be used as positive metabolic profile for glucose and lipid levels.\u003c/p\u003e \u003cp\u003eUnfortunately, BMI cannot distinguish between increased visceral fat, subcutaneous fat, or muscle mass (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e), making it an inadequate tool for assessing cancer risk. While BMI is commonly used in medical practice to assess patient obesity and overall risk, its limitations in accurately assessing body composition make it an imperfect tool for predicting cancer risk.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e1.3 CRC and muscle mass\u003c/h2\u003e \u003cp\u003eSeveral studies have demonstrated the importance of muscle mass in predicting survival rates and outcomes for CRC patients (\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). A recent comprehensive review (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e) showed that the frequency of sarcopenia (low muscle mass) in CRC patients ranges between 12% \u0026minus;\u0026thinsp;60%.\u003c/p\u003e \u003cp\u003eFactors associated with sarcopenia can be either patient-related, such as physical inactivity, malnutrition, and body composition, or cancer-related, including weight loss and muscle mass deterioration resulting from treatment (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Sarcopenia has also been used as a biomarker to predict chemotherapy tolerance and toxicity in CRC patients (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) and several studies have used it to predict surgical complications, reduced survival, and poor quality of life in CRC patients (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePatients with low muscle mass are best identified by computed tomography (CT), as it is considered the gold standard method to measure the mass and quality of muscles in addition to other body composition factors (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn addition to low muscle mass, elevated levels of fat distribution, particularly abdominal visceral fat, represent significant risk factors in CRC. This is primarily attributed to visceral fat's capability to promote the abdominal tumorigenic environment, thereby increasing the likelihood risk of CRC development through various mechanisms, including enhanced cancer cell proliferation, angiogenesis, and the induction of a protumorigenic microenvironment (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Furthermore, visceral fat contributes to systemic chronic inflammation by releasing proinflammatory cytokines and tumour necrosis factor-alpha (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e1.4 Aim\u003c/h2\u003e \u003cp\u003eThe objective of this study was to explore how Visceral Adipose Tissue (VAT), Subcutaneous Adipose Tissue (SAT), and Muscle Mass (MM) correlate with overall survival (OS) in colorectal cancer (CRC) patients treated at King Hussein Cancer Center (KHCC), a leading comprehensive cancer center in Jordan. Utilizing CT scans, we measured muscle mass, visceral fat, and subcutaneous fat, and investigated its relationship with demographic variables (such as age and gender) and clinical indicators (including cancer stage, grade, and primary treatment) to patient survival.\u003c/p\u003e \u003c/div\u003e"},{"header":"2- Materials and Methods","content":"\u003cp\u003eWe screened a total of 2280 patients with CRC who visited KHCC between 2007 and 2018. Inclusion criteria required patients to have a confirmed diagnosis of CRC regardless of the stage, and an available CT scan at the lower edge of L3 vertebral level before treatment initiation. Patients who had CT scans after treatment interventions, types of cancer other than CRC, CT scans at different levels than L3, or low-quality CT scans were excluded from the study. Patients with missing BMI measures at diagnosis were also excluded.\u003c/p\u003e \u003cp\u003eImage-J software (version 1.52a), developed by the U.S. National Institutes of Health (NIH) and available for free in the public domain (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://imagej.nih.gov/ij/\u003c/span\u003e\u003cspan address=\"https://imagej.nih.gov/ij/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), was used to measure the visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), and muscle mass (MM) in square centimeters (cm\u003csup\u003e2\u003c/sup\u003e) \u003cb\u003e(Fig.\u0026nbsp;1)\u003c/b\u003e. The instructions on how to use ImageJ were followed as mentioned in the instruction manual (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Three physicians were trained to measure VAT, SAT, and MM from the CT scans using the same ImageJ version and measuring technique. The threshold values applied to measure the CT scans were determined through visual inspection and experimentation with different thresholds until optimal separation of VAT, SAT, and MM was achieved.\u003c/p\u003e \u003cp\u003eDemographic, pathological, and clinical parameters were collected for the patients. Additionally, height and weight at diagnosis were collected to calculate BMI. To evaluate the agreement and reproducibility among the measurements obtained by the three physicians, 78 CT scans were independently measured three times by different physicians. Subsequently, the intraclass correlation coefficient (ICC) was calculated to evaluate the consistency among the measurements obtained by the three physicians.\u003c/p\u003e \u003cp\u003eReceiver Operating Characteristic (ROC) curves were generated to determine cutoff points for VAT, SAT, and MM based on gender. Survival rates were estimated using the Kaplan-Meier method and compared between groups using the Log-rank test. Multivariate Cox regression was used to assess prognostic factors. A significance criterion of P\u0026thinsp;\u0026le;\u0026thinsp;0.05 was used in the analysis, and all analyses were performed using SAS version 9.4 (SAS Institute Inc, Cary, NC).\u003c/p\u003e \u003cp\u003e The data collected in this study adhered to HIPAA-compliant standards and was ethically approved by the Institutional Review Board (IRB) at KHCC (study number: 17 KHCC 99). Informed consent was waived due to retrospective nature of study design.\u003c/p\u003e"},{"header":"3- Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Agreement and reproducibility:\u003c/h2\u003e \u003cp\u003eThe results of the two-way mixed effects, absolute agreement ICC for VAT, SAT, and MM were 0.88, 0.76, and 0.75, respectively, with a 95% confidence interval (CI) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). ICC values exceeding 0.70 indicate good reliability (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). These findings suggest that the measurements obtained by the three physicians were consistent and reproducible.\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\u003eIntra-class Correlation Coefficient (ICC): two-way mixed effects for absolute agreement\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=\"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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e95% Confidence Interval\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReading\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eICC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLower bound\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUpper bound\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\u003eVisceral adipose tissue\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSubcutaneous adipose tissue\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMuscle mass\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Descriptive analysis:\u003c/h2\u003e \u003cp\u003eOf 2280 screened CRC patients, 408 patients diagnosed at KHCC between 2007 and 2018 met our inclusion criteria and were included in the analysis.\u003c/p\u003e \u003cp\u003eThe mean age at diagnosis was 56.9\u0026thinsp;\u0026plusmn;\u0026thinsp;13.2 (\u0026plusmn;\u0026thinsp;SD) years, median follow-up was 93.3 months (range: 40.9\u0026ndash;182), and 233 (57.1%) were male patients. Of these patients, 216 (52.9%) had colon cancer and 192 (47.1%) had rectum or rectosigmoid cancer. A total of 350 (85.8%) patients\u0026rsquo; cancers were grade 1 or 2. Of the measured CT scans, 210 (51.5%) patients had high VAT, 188 (46.1%) had high SAT, and 228 (55.9%) had high MM. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the descriptive analysis of the demographic of CRC in the sample cohort.\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\u003eDescriptive analysis for demographic and clinical outcomes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eValue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e175 (42.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e233 (57.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cb\u003eAge at diagnosis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50\u0026ndash;59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e101 (24.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60\u0026ndash;69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e107 (26.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75 (18.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e125 (30.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedian (min-max)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58 (92\u0026ndash;21)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eBMI (cut off 25)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eObese /Overweight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e289 (70.83%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnderweight/Normal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e119 (29.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eSite Group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eColon\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e216 (52.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRectum / Rectosigmoid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e192 (47.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cb\u003eGrade\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eG1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (3.92%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eG2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e334 (81.86%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eG3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43 (10.54%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eG4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (0.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (3.19%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cb\u003eTNM Stage Group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (4.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93 (22.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e175 (42.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e113 (27.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (1.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eSurgery\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e112 (27.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e296 (72.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eRadiotherapy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e283 (63.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e125 (31.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eChemotherapy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34 (8.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e374 (91.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eVAT cutoff\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e210 (51.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e198 (48.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedian (min-max)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e210.9 (12.8\u0026ndash;682.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eSAT cutoff\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e188 (46.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e220 (53.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedian (min-max)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e268.1 (7.4\u0026ndash;839.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eMM cutoff\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e228 (55.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e180 (44.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedian (min-max)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e190.5 (69.0\u0026ndash;395.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eFollow-up (Months)\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eN\u0026thinsp;=\u0026thinsp;263\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean (\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96.5 (\u0026plusmn;\u0026thinsp;36)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedian (min-max)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93.3( 40.9\u0026ndash;182)\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\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e summarizes the cut-off points for the area under the curve (AUC) for MM, VAT and SAT, stratified according to gender. The ROC curves are for MM, VAT and SAT for male and females are represented in the supplementary materials (Figs.\u0026nbsp;1s- 6s\u003cb\u003e).\u003c/b\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\u003eAUC cut off points for MM, VAT and SAT, stratified according to gender:\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=\"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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCutoff point\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAUC\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eMM\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e245.141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e55.91%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e131.479\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e60.43%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eVF\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e218.351\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e55.99%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e179.858\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e56.86%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eSCF\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e250.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e55.77%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e325.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e50.45%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Survival analysis:\u003c/h2\u003e \u003cp\u003eAt the follow-up time in March 2022, 145 patients (35.4%) of the patients had died. The median survival of the entire cohort was 96.3 months (95% CI 63.1, 72.2) and the 5-year OS rate was 67.8% \u003cb\u003e(Fig.\u0026nbsp;2)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003ePatients who had surgery had a higher survival rate compared with those who did not have surgery (80.7% vs 33.6% \u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.0001). Tumors of grades 1 and 2 were compared with tumors of grades 3 and 4 and showed a significantly better survival rate (71.0% vs. 46.7% \u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.0015). Additionally, significant differences in survival rates between age groups and TNM stages were observed (\u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.0014 and \u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.0001 respectively) (Table\u0026nbsp;\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 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate Analysis of 5-Year OS in CRC Patients\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=\"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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eValue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5-year OS rate (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\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\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eVAT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e67.9 (61.4, 74.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.6351\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e67.6 (61.9, 73.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eSAT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e67.9 (61.9, 74.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.742\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e67.6 (61.2, 73.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eMM\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e71.8 (65.8, 77.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.0224\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e62.7 (55.5, 69.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003eTNM stage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e95.0 (81.5, 100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e88.2 (80.8, 93.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e76.8 (70.2, 82.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32.7 (24.4, 41.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eSurgery\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33.6 (25.2, 42.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e80.7 (76.0, 85.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003eAge at diagnosis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70.3 (62.0, 78.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.0014\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50\u0026ndash;59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e67.3 (57.9, 76.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60\u0026ndash;69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e75.5 (66.9, 83.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;=70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e53.0 (41.7, 64.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eGrade\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eG1,G2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e71.0 (66.1, 75.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.0015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eG3,G4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46.7 (32.4, 61.2)\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\u003eHigh MM was associated with a better 5-year overall survival rate in CRC patients (71.8% vs. 62.7%, \u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.0224) \u003cb\u003e(Fig.\u0026nbsp;3)\u003c/b\u003e. In contrast, SAT and VAT were not associated with OS when comparing high to low values (67.9% vs 67.6% \u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.74), (67.9% vs 67.6%, \u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.6351), respectively. Moreover, there was no association between BMI and cancer site groups and OS (\u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.6085, \u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.5062, and \u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.5793 respectively) \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eUsing a multivariate Cox regression adjusting for age, stage, grade, surgery, VAT, SAT, and MM, no significant association was observed for VAT, SAT, or grade with a five-year OS rate (P\u0026thinsp;=\u0026thinsp;0.474, 0.863, 0.101 respectively). However, there was an association between age, stage, surgery, and MM with a five-year OS rate (P\u0026thinsp;=\u0026thinsp;0.016, \u0026lt;\u0026thinsp;0.0001, 0.0001, 0.040 respectively) \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e\u003cb\u003e)\u003c/b\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\u003eMultivariate Cox Regression Analysis for CRC Patients\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=\"char\" char=\".\" 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 \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eValue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHazard Ratio\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eHazard Ratio\u003c/p\u003e \u003cp\u003e(95% Confidence)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAdjusted P-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eTNM Stage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI vs. IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.389\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eII vs. IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.365\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIII vs. IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.291\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.191\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.443\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSurgery\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes vs. No\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.447\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.297\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.674\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge at diagnosis\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\u003e1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0162\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMM\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh vs. low\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.997\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.994\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0397\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0397\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVAT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh vs. low\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.4738\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.4738\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSAT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh vs. low\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.8633\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.8633\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGrade\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eG1,G2 vs. G3,G4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.677\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.425\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.101\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4- Discussion","content":"\u003cp\u003eIn this study, we investigated the relationship between Visceral Adipose Tissue (VAT), Subcutaneous Adipose Tissue (SAT), and Muscle Mass (MM) measured using CT scans with OS in CRC patients treated at KHCC in Jordan. Our findings showed a significant association between high muscle mass and improved OS rates in CRC patients, aligning with previous research emphasizing the positive impact of increased MM on survival outcomes in cancer patients (\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). This analysis revealed that OS in CRC patients was influenced by multiple predictive factors, including surgical intervention, tumour grade, TNM stage, and age at diagnosis, all of which demonstrated significant associations with survival outcomes (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe 5-years OS rate of 67.8% (95% CI 63.1\u0026ndash;72.2) of our population was similar to other studies conducted in Brazil 63.5% (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e) and a population-based study in 9 European countries 71\u0026middot;1% (95% CI 70\u0026middot;7\u0026ndash;71\u0026middot;4) (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e) which can be attributed to similarities in the high level of quality of care provided to CRC patients. A previously published study utilizing data from the Jordan\u0026rsquo;s cancer registry during the period of 2005\u0026ndash;2010 reported a 5-years OS of 58.2% for CRC patients (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). The notable increase in survival rates between their study and our findings suggests positive progress in the level of care and advancements in treatment modalities over time.\u003c/p\u003e \u003cp\u003eTo accurately measure MM, VAT, and SAT, our study employed a CT scan-based method (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e) using ImageJ software. Three independent physicians measured the images to ensure data accuracy and reliability.\u003c/p\u003e \u003cp\u003eA study conducted in biliary duct cancer patients showed that high MM was associated with a high survival rate (HR 0.46, 95% CI 0.22\u0026ndash;0.95, \u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.037) (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) which is similar to our results (HR 0.997, 95% CI 0.994\u0026ndash;1, \u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.0397). Another meta-analysis (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e) on rectal cancer patients with sarcopenia showed a poor survival rate (HR 2.10, 95% CI 1.33\u0026ndash;3.32, \u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.001) compared to patients with high MM, which is in line with our results that high muscle mass provides survival benefit for patients with CRC.\u003c/p\u003e \u003cp\u003eBased on our knowledge and existing literature highlighting the adverse effects of VAT in the abdominal region, we explored the association between VAT and OS in CRC patients. Interestingly, our findings indicated no significant impact of high VAT (HR 1.001, 95% CI 1.003\u0026ndash;0.4738, \u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.4738) on OS, similar to results from a study on Korean CRC patients (HR 0.656; 95% CI 0.402\u0026ndash;1.071; \u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.092) (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). However, this is contrary to other studies reporting a significant association between increased VAT (HR 2.61, 95% CI 1.155\u0026ndash;5.924, \u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.020) and poor survival outcomes (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWe also investigated the association between SAT and OS in CRC patients, and our findings did not indicate a significance on OS (HR 1.000, 95% CI 0.999\u0026ndash;1.001, \u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.8633). Our results are similar to the above-mentioned study (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e), (HR 1.18, 95% CI 0.614\u0026ndash;2.036, \u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.715) but contrary to the study on Korean CRC patients among other studies (HR 0.505, 95% CI 0.266\u0026ndash;0.957; \u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.036) (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis discrepancy may be attributable to the relatively small sample size and the heterogeneity of the CRC patient population in our study. Genetic factors specific to the Middle Eastern population may also contribute to this variation (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). These include IL-17 polymorphisms which play a crucial role in inflammation, and autoimmune diseases and are responsible for CRC growth and invasion (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). Moreover, CRC driver mutations like RAS and BRAF mutations vary in their prevalence in Middle Eastern compared to Western countries (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). However, this data was not available for the population of patients we studied and further research is needed to study these variable and their interplay with body composition and effect on CRC outcome.\u003c/p\u003e \u003cp\u003eAdditionally, we rigorously controlled for potential confounding factors such as age at diagnosis, gender, tumour grade, and TNM stage, enhancing the validity and reliability of our findings. Our findings in the multivariate analysis revealed that only the age at diagnosis, TNM stage group, surgery, and MM were significant independent predictors of the patient\u0026rsquo;s survival. Our results are similar to findings in other Middle Eastern populations (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e) and analyses based on the SEER database (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). Tumour grade did not emerge as a significant predictor of CRC survival in multivariate analysis, which is contrary to other published research in Western populations like the US and Canada using their National Cancer Database (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e) and Eastern populations such as Korean CRC patients (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIt is important to (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) acknowledge the limitations of our study, primarily due to its retrospective design which resulted in missing data that could contribute important insights to the question of body composition and its association with CRC outcome. This includes the absence of lifestyle data encompassing physical activity and diet, both of which have the potential to impact body composition, fat, and muscle distribution, and could be associated with OS in CRC patients (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e), in addition to their role in cancer prevention (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e). Unfortunately, these data were not present in our electronic medical records at the time of diagnosis nor during the patient\u0026rsquo;s treatment course.\u003c/p\u003e \u003cp\u003eFuture research with larger sample sizes and more diverse patient cohorts is needed to better understand the association between body composition and CR outcome. Such studies would help validate our findings and elucidate the underlying mechanisms involved, thereby informing clinical practice to improve CRC outcomes and enhance the quality of life for patients. Additionally, investigations exploring genetic factors and genetic variations across different populations may help to answer questions specific to the Middle Eastern population and provide further insights into the relationship between body composition and survival outcomes in CRC patients.\u003c/p\u003e"},{"header":"5- Conclusion","content":"\u003cp\u003eThis study provides evidence supporting the association between high muscle mass and improved OS rates in CRC patients. Additionally, TNM stage, surgical intervention, and age at diagnosis were identified as significant independent predictors of OS. Notably, VAT and SAT did not demonstrate a significant association with OS. These findings highlight the importance of assessing body composition, especially muscle mass as a valuable prognostic indicator in CRC patients.\u003c/p\u003e \u003cp\u003eFurthermore, integrating routine physical activity and promoting healthy lifestyle habits in the management of CRC patients hold potential benefits. Future studies can explore the impact of exercise and nutritional interventions on body composition and OS rates, contributing to the development of comprehensive treatment strategies.\u003c/p\u003e \u003cp\u003eIn addition, nutritional counselling can be a crucial aspect of CRC patient care. Exploring the effects of tailored nutritional interventions, including increased protein intake, on body composition and muscle mass, OS rates, and quality of life, can provide valuable insights into optimizing patient outcomes.\u003c/p\u003e \u003cp\u003eBy addressing these areas, we can emphasize the significance of physical activity and healthy lifestyle choices, and incorporate nutritional counselling into the comprehensive care of CRC patients. These factors can have the potential to advance the field and contribute to improved survival rates, enhanced quality of life, and better overall outcomes for individuals with CRC.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAcknowledgments\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This research was supported by funds from the Intramural Research Grants Program at King Hussein Cancer Center (Award Number: 17 KHCC 99).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInstitutional Review Board Statement:\u003c/strong\u003e This study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Institutional Review Board of King Hussein Cancer Center (Study Number: 17 KHCC 99).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u003c/strong\u003e The data that support the findings of this study are available upon reasonable request from the corresponding author (A.A).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interest:\u003c/strong\u003e The authors declare no competing interests.\u003c/p\u003e\n\u003ch1\u003eAuthors contribution:\u0026nbsp;\u003c/h1\u003e\n\u003cp\u003e\u003cstrong\u003eConceptualization:\u0026nbsp;\u003c/strong\u003e(A.A), (M.A.S). \u003cstrong\u003eMethodology:\u0026nbsp;\u003c/strong\u003e(A.A), (H.A), (M.A.S). \u003cstrong\u003eWriting \u0026ndash; Original Draft:\u0026nbsp;\u003c/strong\u003e(H.A). \u003cstrong\u003eWriting \u0026ndash; Review \u0026amp; Editing:\u003c/strong\u003e (H.A), (A.A), (A.T), (F.A). \u003cstrong\u003eData collection:\u003c/strong\u003e (H.A), (M.A.S), (F.A), (K.A.J), (Z.A.J), (O.A). \u003cstrong\u003eFormal statistical analysis:\u003c/strong\u003e (A.T). \u003cstrong\u003eData management:\u003c/strong\u003e (H.A.K). All authors have critically revised the manuscript for important intellectual content, approved the final version to be published, and agreed to be accountable for all aspects of the work. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA: A Cancer Journal for Clinicians. 2021;71(3):209\u0026thinsp;\u0026ndash;\u0026thinsp;49.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHealth JMo. Cancer Incidence in Jordan. Cancer Incidence in Jordan. Jordan2018. p. 45.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLewandowska A, Rudzki G, Lewandowski T, Stryjkowska-G\u0026oacute;ra A, Rudzki S. Title: Risk Factors for the Diagnosis of Colorectal Cancer. Cancer Control. 2022;29:10732748211056692.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAl Obeed OA, Vaali-Mohamed MA, Alkhayal KA, Bin Traiki TA, Zubaidi AM, Arafah M, et al. IL-17 and colorectal cancer risk in the Middle East: gene polymorphisms and expression. Cancer Manag Res. 2018;10:2653\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOukkal M, Bouzid K, Bounedjar A, Alnajar A, Taleb FA, Alsharm A, et al. Middle East and North Africa Registry to Characterize Rate of RAS Testing Status in Newly Diagnosed Patients with Metastatic Colorectal Cancer. Turk J Gastroenterol. 2023;34(2):118\u0026ndash;27.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGarawin T, Lowe K, Kafatos G, Murray S. The prevalence RAS and BRAF mutations among patients in the Middle East and Northern Africa with metastatic colorectal cancer. Journal of Clinical Oncology. 2016;34(15_suppl):e15077-e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShaukat A, Dostal A, Menk J, Church TR. BMI Is a Risk Factor for Colorectal Cancer Mortality. Dig Dis Sci. 2017;62(9):2511\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSimillis C, Taylor B, Ahmad A, Lal N, Afxentiou T, Powar MP, et al. A systematic review and meta-analysis assessing the impact of body mass index on long-term survival outcomes after surgery for colorectal cancer. European Journal of Cancer. 2022;172:237\u0026ndash;51.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHumphreys S. The unethical use of BMI in contemporary general practice. Br J Gen Pract. 2010;60(578):696\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDonohoe CL, Doyle SL, Reynolds JV. Visceral adiposity, insulin resistance and cancer risk. Diabetol Metab Syndr. 2011;3:12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee JY, Lee HS, Lee DC, Chu SH, Jeon JY, Kim NK, et al. Visceral fat accumulation is associated with colorectal cancer in postmenopausal women. PLoS One. 2014;9(11):e110587.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim JM, Chung E, Cho ES, Lee JH, Shin SJ, Lee HS, et al. Impact of subcutaneous and visceral fat adiposity in patients with colorectal cancer. Clin Nutr. 2021;40(11):5631\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShuster A, Patlas M, Pinthus JH, Mourtzakis M. The clinical importance of visceral adiposity: a critical review of methods for visceral adipose tissue analysis. Br J Radiol. 2012;85(1009):1\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVergara-Fernandez O, Trejo-Avila M, Salgado-Nesme N. Sarcopenia in patients with colorectal cancer: A comprehensive review. World J Clin Cases. 2020;8(7):1188\u0026ndash;202.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003evan Roekel EH, Bours MJL, Te Molder MEM, Breedveld-Peters JJL, Olde Damink SWM, Schouten LJ, et al. Associations of adipose and muscle tissue parameters at colorectal cancer diagnosis with long-term health-related quality of life. Qual Life Res. 2017;26(7):1745\u0026ndash;59.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMeyer HJ, Strobel A, Wienke A, Surov A. Prognostic Role of Low-Skeletal Muscle Mass on Staging Computed Tomography in Metastasized Colorectal Cancer: A Systematic Review and Meta-Analysis. Clin Colorectal Cancer. 2022;21(3):e213-e25.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCespedes Feliciano EM, Avrutin E, Caan BJ, Boroian A, Mourtzakis M. Screening for low muscularity in colorectal cancer patients: a valid, clinic-friendly approach that predicts mortality. Journal of Cachexia, Sarcopenia and Muscle. 2018;9(5):898\u0026ndash;908.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTsaousi G, Kokkota S, Papakostas P, Stavrou G, Doumaki E, Kotzampassi K. Body composition analysis for discrimination of prolonged hospital stay in colorectal cancer surgery patients. European Journal of Cancer Care. 2017;26(6):e12491.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHeus C, Cakir H, Lak A, Doodeman HJ, Houdijk APJ. Visceral obesity, muscle mass and outcome in rectal cancer surgery after neo-adjuvant chemo-radiation. International Journal of Surgery. 2016;29:159\u0026ndash;64.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e\u0026Eacute;B NB, Daly LE, Power DG, Cushen SJ, MacEneaney P, Ryan AM. Computed tomography diagnosed cachexia and sarcopenia in 725 oncology patients: is nutritional screening capturing hidden malnutrition? J Cachexia Sarcopenia Muscle. 2018;9(2):295\u0026ndash;305.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDusserre E, Moulin P, Vidal H. Differences in mRNA expression of the proteins secreted by the adipocytes in human subcutaneous and visceral adipose tissues. Biochim Biophys Acta. 2000;1500(1):88\u0026ndash;96.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGomez-Perez SL, Haus JM, Sheean P, Patel B, Mar W, Chaudhry V, et al. Measuring Abdominal Circumference and Skeletal Muscle From a Single Cross-Sectional Computed Tomography Image: A Step-by-Step Guide for Clinicians Using National Institutes of Health ImageJ. JPEN J Parenter Enteral Nutr. 2016;40(3):308\u0026ndash;18.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKoo TK, Li MY. A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research. Journal of chiropractic medicine. 2016;15(2):155\u0026ndash;63.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLimpawattana P, Theerakulpisut D, Wirasorn K, Sookprasert A, Khuntikeo N, Chindaprasirt J. The impact of skeletal muscle mass on survival outcome in biliary tract cancer patients. PLoS One. 2018;13(10):e0204985.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLopez P, Newton RU, Taaffe DR, Singh F, Buffart LM, Spry N, et al. Associations of fat and muscle mass with overall survival in men with prostate cancer: a systematic review with meta-analysis. Prostate Cancer and Prostatic Diseases. 2022;25(4):615\u0026ndash;26.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhu Y, Guo X, Zhang Q, Yang Y. Prognostic value of sarcopenia in patients with rectal cancer: A meta-analysis. PLOS ONE. 2022;17(6):e0270332.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJoachim C, Macni J, Drame M, Pomier A, Escarmant P, Veronique-Baudin J, et al. Overall survival of colorectal cancer by stage at diagnosis: Data from the Martinique Cancer Registry. Medicine. 2019;98(35):e16941.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAndreoni B, Chiappa A, Bertani E, Bellomi M, Orecchia R, Zampino M, et al. Surgical outcomes for colon and rectal cancer over a decade: results from a consecutive monocentric experience in 902 unselected patients. World J Surg Oncol. 2007;5:73.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAguiar Junior S, Oliveira MM, Silva D, Mello CAL, Calsavara VF, Curado MP. SURVIVAL OF PATIENTS WITH COLORECTAL CANCER IN A CANCER CENTER. Arq Gastroenterol. 2020;57(2):172\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCardoso R, Guo F, Heisser T, De Schutter H, Van Damme N, Nilbert MC, et al. Overall and stage-specific survival of patients with screen-detected colorectal cancer in European countries: A population-based study in 9 countries. The Lancet Regional Health - Europe. 2022;21:100458.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSharkas GF, Arqoub KH, Khader YS, Tarawneh MR, Nimri OF, Al-zaghal MJ, et al. Colorectal Cancer in Jordan: Survival Rate and Its Related Factors. Journal of Oncology. 2017;2017:3180762.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGoulart A, Malheiro N, Rios H, Sousa N, Le\u0026atilde;o P. Influence of Visceral Fat in the Outcomes of Colorectal Cancer. Dig Surg. 2019;36(1):33\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim J-M, Chung E, Cho E-S, Lee J-H, Shin S-J, Lee HS, et al. Impact of subcutaneous and visceral fat adiposity in patients with colorectal cancer. Clinical Nutrition. 2021;40(11):5631\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBasile D, Bartoletti M, Polano M, Bortot L, Gerratana L, Di Nardo P, et al. Prognostic role of visceral fat for overall survival in metastatic colorectal cancer: A pilot study. Clinical Nutrition. 2021;40(1):286\u0026ndash;94.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePark JW, Chang SY, Lim JS, Park SJ, Park JJ, Cheon JH, et al. Impact of Visceral Fat on Survival and Metastasis of Stage III Colorectal Cancer. Gut Liver. 2022;16(1):53\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKolls JK, Lind\u0026eacute;n A. Interleukin-17 family members and inflammation. Immunity. 2004;21(4):467\u0026ndash;76.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSaharti S. KRAS/NRAS/BRAF Mutation Rate in Saudi Academic Hospital Patients With Colorectal Cancer. Cureus. 2022;14(4):e24392.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlyabsi M, Sabatin F, Ramadan M, Jazieh AR. Colorectal cancer survival among Ministry of National Guard-Health Affairs (MNG-HA) population 2009\u0026ndash;2017: retrospective study. BMC Cancer. 2021;21(1):954.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZare-Bandamiri M, Khanjani N, Jahani Y, Mohammadianpanah M. Factors Affecting Survival in Patients with Colorectal Cancer in Shiraz, Iran. Asian Pac J Cancer Prev. 2016;17(1):159\u0026ndash;63.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXie Y, Huang Y, Ruan Q, Wang H, Liang X, Hu Z, et al. Impact of Tumor Site on Lymph Node Status and Survival in Colon Cancer. Journal of Cancer. 2019;10(11):2376\u0026ndash;83.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlese OB, Zhou W, Jiang R, Zakka K, Huang Z, Okoli C, et al. Predictive and Prognostic Effects of Primary Tumor Size on Colorectal Cancer Survival. Front Oncol. 2021;11:728076.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee JM, Han YD, Cho MS, Hur H, Min BS, Lee KY, et al. Impact of tumor sidedness on survival and recurrence patterns in colon cancer patients. Ann Surg Treat Res. 2019;96(6):296\u0026ndash;304.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYun Z, Hao W, Peizhong Peter W, Sevtap S, Jennifer W, Tyler W, et al. Dietary patterns and colorectal cancer recurrence and survival: a cohort study. BMJ Open. 2013;3(2):e002270.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDashti SG, Win AK, Hardikar SS, Glombicki SE, Mallenahalli S, Thirumurthi S, et al. Physical activity and the risk of colorectal cancer in Lynch syndrome. Int J Cancer. 2018;143(9):2250\u0026ndash;60.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChan AT, Giovannucci EL. Primary prevention of colorectal cancer. Gastroenterology. 2010;138(6):2029-43.e10.\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":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Colorectal cancer, Middle East, Muscle mass, Visceral fat, Subcutaneous fat, Survival, CT-based","lastPublishedDoi":"10.21203/rs.3.rs-4526513/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4526513/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eRecent reports have shown that pre-treatment low muscle mass may lead to poorer outcomes for cancer patients. We explored the correlation between Visceral Adipose Tissue (VAT), Subcutaneous Adipose Tissue (SAT), and Muscle Mass (MM) as measured by CT scans, and overall survival (OS) following diagnosis of colorectal cancer (CRC). We conducted a retrospective review of medical records and CT scans of patients diagnosed with CRC between 2007\u0026ndash;2018. Demographics, pathology, and clinical parameters were collected. Using Image-J software, we measured VAT, SAT, and MM. Survival rates were analyzed using Kaplan-Meier curves, and prognostic factors were assessed using multivariate Cox regression. Analysis included 408 patients with a mean age of 56.9 years and a median follow-up of 93.3 months. Colon and rectum/rectosigmoid colon cancers were equally distributed. The 5-year OS rate was 67.8%. There was no significant difference in OS rates based on SAT or VAT. However, higher MM was associated with a improved 5-year OS rate. Factors such as age, stage, grade, and surgery were also associated to OS rates. These findings suggest that higher muscle mass may lead to better outcomes for CRC patients, highlighting the potential impact of exercise and nutritional interventions on patient outcomes.\u003c/p\u003e","manuscriptTitle":"Prognostic Significance of Muscle Mass in Colorectal Cancer Patients at a Tertiary Cancer Center in the Middle East: A CT Scan-Based Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-26 14:32:45","doi":"10.21203/rs.3.rs-4526513/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-06-13T16:42:21+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-09T21:14:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"267268324131159986465965272097135990601","date":"2024-06-09T20:21:51+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-09T10:59:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"313880697449827265697001184780400422153","date":"2024-06-09T10:54:17+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-06-08T13:50:48+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-07T17:42:17+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-06-07T17:38:32+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-06-06T03:59:15+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-06-04T08:45:09+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2bd7b539-08cb-4076-8b83-9504b3d6b6b7","owner":[],"postedDate":"June 26th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":33224378,"name":"Biological sciences/Cancer/Gastrointestinal cancer/Colorectal cancer/Colon cancer"},{"id":33224379,"name":"Biological sciences/Cancer/Gastrointestinal cancer/Colorectal cancer/Rectal cancer"},{"id":33224380,"name":"Health sciences/Medical research/Outcomes research"},{"id":33224381,"name":"Health sciences/Risk factors"},{"id":33224382,"name":"Health sciences/Oncology/Cancer/Cancer imaging"}],"tags":[],"updatedAt":"2024-09-09T16:11:00+00:00","versionOfRecord":{"articleIdentity":"rs-4526513","link":"https://doi.org/10.1038/s41598-024-68503-7","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2024-09-06 16:05:10","publishedOnDateReadable":"September 6th, 2024"},"versionCreatedAt":"2024-06-26 14:32:45","video":"","vorDoi":"10.1038/s41598-024-68503-7","vorDoiUrl":"https://doi.org/10.1038/s41598-024-68503-7","workflowStages":[]},"version":"v1","identity":"rs-4526513","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4526513","identity":"rs-4526513","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}