Risk factors and survival of colorectal cancer patients with RAS/BRAF gene mutations

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Kazachenko, Vitaly P. Shubin, Evgeniy A. Khomyakov, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7657018/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose Compare long-term outcomes in patients with colorectal cancer with KRAS , NRAS , and BRAF gene mutations and wild-type genes. Methods The study had cohort retrospective design. The overall survival (OS) for 611 patients and disease-free survival (DFS) for 490 patients were evaluated using the Kaplan-Meier estimator as primary endpoint. Relative OS and DFS of patients with gene mutations and wild-type genes and risk factor analysis were performed as secondary endpoints. Results Patients with NRAS gene mutations had worse OS (p-value = 0.04) and patients with KRAS gene mutation had worse DFS (p-value = 0.02) both compared to wild-type genes patients. 3-year OS rate was 86%, 74% 67% and 78% and 3-year DFS rate was 50%, 34% 50% and 46% for patients with the wild-type genes, KRAS , NRAS and BRAF gene mutations, respectively. Complete cytoreduction (HR 0.20, p-value < 0.005) and stage II (HR 0.07, p-value = 0.01) of the disease were associated with a lower risk of death. A KRAS gene mutations (HR 1.61, p-value = 0.01), neoadjuvant chemotherapy (HR 1.52, p-value = 0.04), and incomplete resection (HR 1.83, p-value = 0.03) were associated with a high risk of recurrence, while stages I-III compared with stage IV (HR 0.32, p-value = 0.01; HR 0.22, p-value < 0.005; HR 0.26, p-value < 0.005) were associated with a lower risk of recurrence. Conclusion RAS/ BRAF mutations associated with worse CRC survival, however, advanced stage, incomplete cytoreduction and resection (R1) are also significant risk factors for death and CRC recurrence. Thus, early colorectal cancer diagnostic and radical and complete tumor resection allow to improve overall and disease-free survival for all patients. Colorectal cancer overall survival risk factors KRAS BRAF NRAS Figures Figure 1 Figure 2 Introduction Colorectal cancer (CRC) is the third most commonly diagnosed cancer and the second leading cause of oncologic death worldwide [ 1 ]. The RAS/RAF/MAPK/ERK signaling pathway plays an important role in the development of CRC as in most epithelial neoplasms and serves as a target for anti-EGFR therapy [ 2 ]. However, in 50–60% of cases CRC does not respond to anti-EGFR therapy [ 3 ]. This is due to the somatic activation of the RAS/RAF/MAPK/ERK pathway by KRAS , NRAS and BRAF genes mutations [ 4 ]. Patients with such mutations have lower rates of overall and disease-free survival, shorter time to relapse, and survival after relapse [ 5 – 11 ]. In recent studies more attention has been paid to the type of mutations, since the survival rates do not seem to differ between patients with RAS/ BRAF gene mutations and wild-type genes [ 12 ]. The study by Tonello M. et al. [ 12 ] showed that the median survival of patients with G12R, G13A, G13C, G13V, Q61H, K117N, A146V KRAS mutations with peritoneal carcinomatosis after cytoreductive surgery was more than 120 months while the median survival of patients with G12A, G12C, G12D, G12S, G12V, G13D, A59E, A59V, A146T KRAS mutations was 31.2 months. In Russian studies, long-term oncological outcomes in patients with the RAS/ BRAF gene mutations were assessed in two contradictory studies with grade IV colorectal cancer patients [ 13 , 14 ]. In one study, the presence of mutations did not affect overall and disease–free survival, while in the other mutations were poor prognosis predictors. Thus, the survival of patients with CRC with a RAS/ BRAF mutations in the Russian cohort remains unclear. Aim The aim of the study was to compare long-term outcomes in patients with colorectal cancer with KRAS , NRAS , and BRAF gene mutations and wild-type genes. Materials and methods This retrospective cohort study was performed on the basis of the database of the Department of Laboratory Genetics of the Ryzhikh National Medical Research Center of Coloproctology of the Ministry of Health of the Russian Federation. The database included 682 patients who underwent molecular genetic testing for mutations in the KRAS , NRAS , and BRAF genes from 01.2020 to 06.2023. The comparative analysis included 647 patients, and the overall survival analysis included 611 patients while disease-free survival analysis included 490 patients. Additional clinical information (demographic and clinical parameters) was collected based on medical records. Eligibility criteria The study included patients over 18 years old with a verified colorectal cancer who underwent molecular genetic testing for mutations in the KRAS , NRAS , and BRAF genes. Patients with incomplete clinical information in their medical records were excluded from the analysis: • Lack of a formulated diagnosis according to the TNM classification; • No information about primary tumor and the tumor histopathology; • Lost contact with the patient and lost records in patients’ database. Primary endpoint • Overall and disease-free survival in patients with KRAS , NRAS and BRAF gene mutations, and wild-type genes Secondary endpoints • 1-year and 3-year overall and disease-free survival in patients with KRAS , NRAS , BRAF gene mutations and wild-type genes • Risk factors for death and disease recurrence in patients with mutations and wild-type genes Sequencing using the Sanger method To determine mutations in the KRAS (RefSeq_NM_004985) (2-4 exons), NRAS (RefSeq_NM_002524) (2-3 exons), and BRAF (RefSeq_NM_004333) (15 exons) genes, fragments were amplified using polymerase chain reaction on a Veriti programmable thermal cycler (Applied Biosystems, USA) using original oligonucleotide seed primers. Sequencing was performed on an automatic capillary sequencer ABI PRISM 3500 (8 capillaries; Applied Biosystems, USA). The UniPro Ugene v.47 software was used to interpret the sequencing results. The reference sequence was generated in fasta format from an open source https://www.ensembl.org /. Statistical analysis To describe quantitative features median, upper and lower quartiles (IQR – interquartile range), maximum and minimum values were calculated. Absolute and relative frequencies were used to describe categorical features. The difference between the groups was considered significant with a p-value < 0.05. The comparative analysis was performed using the R language version 4.4.1. For statistical comparison, the Chi-square test was used when an expected frequency of observations ≥5 in at least 80% of cells for multipole tables or the exact Fisher test (Fisher's exact test) for categorical features and the Kruskal-Wallis test for quantitative features. The survival analysis was performed using the high-level programming language Python 3.9.10 (libraries scipy version 1.13. and lifelines version 0.29.0) based on the Visual Studio Code text editor, Microsoft. (2022) version 1.87.2 using the Kaplan-Meier estimator with the calculation of median survival and 95% confidence interval (CI). To compare the survival curves, a Log-rank test was performed. When calculating disease-free survival, only episodes of relapse or disease progress were considered as target events. To identify risk factors for death and relapse/disease progress, univariate and multivariate regression models of Cox proportional hazards (Cox proportional hazards model) were constructed with the calculation of the hazard ratio (HR), 95% confidence interval (CI) and p-value. The multivariate regression analysis included only those features that turned out to be risk factors in the univariate analysis and which were not the cause of multicollinearity when simultaneously present with other features. The assumption of risk proportionality was verified by visually evaluating the distribution of Schoenfeld residues over time and calculating the p-value using a test based on the correlation between Schoenfeld residues and time. Ethical statements The study’s protocol was reviewed and approved by the Local Ethical Committee of Ryzhikh National Medical Research Center of Coloproctology (№ 105, 03.02.2025). The study was conducted in accordance with the World Medical Association (WMA) Declaration of Helsinki: Medical Research Involving Human Subjects. Results A comparative analysis of the KRAS , NRAS , and BRAF gene mutations frequency was performed depending on the patients’ demographic and clinical characteristic (Table 1). Table 1. Comparative characteristics of patients with RAS/ BRAF gene mutations. Feature Frequency (%) p-value Wild-type KRAS gene mutations NRAS gene mutations BRAF gene mutations Total patients N=647 (100%) 252 (38.9%) 310 (47.9%) 33 (5.1%) 52 (8%) - Age, years (median, IQR) 58 (46, 66) 61 (51, 68) 67 (52 , 71) 67 (60, 73) < 0.001* Sex: Male Female 131 (52%) 121 (48%) 131 (42.3%) 179 (57.7%) 13 (39,4%) 20 (60,6%) 19 (36,5%) 33 (63,5%) 0.051 Primary tumor localization: Right colon Left colon Rectum 44 (17.5%) 102 (40.5%) 106 (42.1%) 74 (23.9%) 98 (31.6%) 138 (44.5%) 10 (30.3%) 5 (15.2%) 18 (54.5%) 35 (67.3%) 13 (25%) 4 (7.7%) < 0.001* Neoadjuvant chemotherapy: Yes No Unknown 73 (29%) 173 (68.7%) 6 (2.4%) 82 (26.5%) 216 (69.7%) 12 (3.9%) 8 (24.2%) 24 (72.7%) 1 (3%) 3 (5.8%) 45 (86.6%) 4 (7.7%) 0.009* Disease relapse/progress: Yes No Unknown 61 (24.2%) 141 (56%) 50 (19.8%) 99 (31.9%) 138 (44.5%) 73 (23.5%) 5 (15.2%) 18 (54.6%) 10 (30.3%) 9 (17.3%) 30 (57.7%) 13 (25%) 0.01* Stage I-II III-IV 62 (24.6%) 190 (75.4%) 69 (22.3%) 241 (77.7%) 10 (30.3%) 23 (69.7%) 21 (40.4%) 31 (59.6%) 0.04* Synchronous cancer Metachronous cancer 12 (4.8%) 14 (5.6%) 15 (4.8%) 22 (7.1%) 2 (6.1%) 3 (9.1%) 1 (1.9%) 4 (7.7%) 0.8 0.7 Characteristic of patients after surgery Surgical treatment: Yes No 226 (89.3%) 26 (10.7%) 255 (82.3%) 55 (17.7%) 31 (93.9%) 2 (6.1%) 46 (88.5%) 6 (11.5%) 0.04* Adjuvant chemotherapy Yes No Unknown 187 (82.7%) 35 (15.5%) 4 (1.8%) 225 (88.2%) 27 (10.6%) 3 (1.2%) 25 (80.6%) 6 (19.4%) - 33 (71.7%) 10 (21.7%) 3 (6.5%) 0.09 Cytoreduction: Incomplete Complete 17 (7.5%) 209 (92.5%) 30 (11.8%) 225 (88.2%) 3 (9.7%) 28 (90.3%) 8 (17.4%) 38 (82.6%) 0.2 Residual tumor: R0 R1 Unknown 202 (89.4%) 18 (8%) 6 (2.6%) 233 (91.4%) 13 (5.1%) 9 (3.5%) 28 (90.3%) 3 (9.1%) 44 (95.7%) 2 (4.3%) 0.5 * p-value< 0.05, the difference is significant The frequency of RAS/ BRAF genes mutations was 395/647 (61.1%). The distribution of the mutation frequencies is presented in the Supplementary materials (Table 4). The median follow–up for patients with wild–type genes was 24 months (IQR 10-37 months), with KRAS gene mutations – 21 months (IQR 9-34 months), with NRAS gene mutations - 14 months (IQR 4-31 months), with BRAF gene mutations - 21.5 months (IQR 4.8-29.3 months). Survival analysis The median overall survival (OS) was 82 months, 95% CI 73 – +∞ months. The median survival of KRAS gene mutation patients was 82 months, 95% CI 73 – +∞ months. The medians for the other subgroups could not be calculated due to the insufficient number of target events (deaths) (Fig. 1). According to the results of the log-rank test, significant differences were observed only between patients with NRAS gene mutations and with wild-type gene (p-value=0.04). The overall 1-year survival rate was 95%, for patients with wild type genes - 96%, with KRAS gene mutations - 95%, with NRAS gene mutations - 86%, and with BRAF gene mutations - 94%. The overall 3-year survival rate was 79% and 86%, 74%, 67%, and 78% for patients with wild-type genes, KRAS , NRAS and BRAF gene mutations, respectively. The disease-free survival (DFS) analysis included 490 patients with a known disease relapse/progress status. The median DFS was 60 months, 95% CI 51-72 months. The median DFS for patients with KRAS gene mutations was 48 months, 95% CI 32-74 months. For patients with wild-type genes, the median DFS was 60 months, 95% CI 57 - +∞ months. The medians for the other subgroups could not be calculated due to the insufficient number of target events (relapse or disease progress) (Fig. 2) Significant differences in DFS were found only between patients with the wild-type genes and with KRAS gene mutations. The disease-free period in KRAS gene mutation patients was significantly shorter than in patients with the wild-type genes (p-value = 0.02). The overall 1-year disease-free survival rate was 79%, for patients with the wild-type genes - 81%, for patients with KRAS gene mutations - 75%, for NRAS gene mutations - 94%, and for BRAF gene mutations - 83%. The overall 3-year DFS rate was 42% and 50%, 34%, 50%, and 46% for patients with wild-type genes, KRAS , NRAS and BRAF gene mutations, respectively. The results of univariate and multivariate regression analysis (Cox regression model) to identify risk factors of death (N=611) are presented in Table 2. Table 2. Univariate and multivariate regression analysis of risk factors of death. Risk factor Univariate analysis (Hazard ratio, 95% CI) p-value multivariate analysis (Hazard ratio, 95% CI) p-value Sex (female) 0.77 [0.43-1.38] 0.4 - - Age 1.06 [1.03-1.09] <0.001* 1.02 [0.98-1.06] 0.3 The presence of any mutation 1.85 [0.97-3.52] 0.06 - - Wild-type gene - reference KRAS gene mutation NRAS gene mutation BRAF gene mutation 1.85 [0.95-3.58] 3.08 [1.00-9.50] 1.04 [0.23-4.63] 0.07 0.05 0.9 1.92 [0.74-4.97] 0.0 [0.0-inf] 0.53 [0.06-5.18] 0.2 1.0 0.6 Primary tumor localization: Right colon - reference Left colon Rectum 0.70 [0.31-1.56] 1.36 [0.67-2.75] 0.4 0.4 - - - - Surgical treatment 0.23 [0.11-0.47] <0.001* 0.56 [0.06-5.19] 0.6 Complete cytoreduction 0.10 [0.05-0.19] <0.001* 0.20 [0.07-0.61] <0.005* Neoadjuvant chemotherapy 2.81 [1.53-5.17] 0.001* - - Adjuvant chemotherapy 1.27 [0.45-3.60] 0.7 - - Disease relapse/progress 4.16 [1.60-10.81] 0.003* - - Stage: (IV – reference) I II III 0.00 [0.00-inf] 0.06 [0.01-0.25] 0.12 [0.06-0.27] 1.0 <0.001* <0.001* 0 [0.00-inf] 0.07 [0.01-0.60] 0.33 [0.11-1.04] 1.0 0.01* 0.06 Stage T: (Т1 – reference) 2 3 4 0.22 [0.01-3.50] 1.34 [0.18-9.99] 1.66 [0.22-12.37] 0.3 0.8 0.6 - - - - - - Stage N: (N0 – reference) 1 2 2.82 [1.01-7.83] 4.66 [1.79-12.12] 0.05* 0.002* - - - - Stage M: (М0 - reference) 1a 1b 1c 10.42 [4.94-21.94] 14.91 [5.80-38.31] 7.05 [2.19-22.71] <0.001* <0.001* 0.001* - - - - - - Metastasis localization: Liver Carcinomatosis Lungs Lymphatic nodes Other 6.52 [3.60-11.82] 2.92 [1.14-7.47] 5.33 [2.62-10.86] 1.28 [0.39-4.13] 2.47 [0.34-18.02] <0.001* 0.02* <0.001* 0.7 0.4 - - - - - - - - - - Synchronous cancer Metachronous cancer 1.42 [0.44-4.59] 0.29 [0.04-2.08] 0.6 0.2 - - - - Residual tumor: (R0 – reference) R1 1.67 [0.51-5.48] 0.4 - - LVI 1.73 [0.52-5.70] 0.4 - - *p-value< 0.05, the difference is significant Univariate analysis demonstrated that a younger age, surgical treatment with complete cytoreduction, stage II and III of the disease compared with stage IV were significantly associated with a lower risk of death, while neoadjuvant CT, the regional lymph nodes and distant metastases (N1-2M1 according to the TNM classification), liver, lung and peritoneal metastases, as well as the disease recurrence were significantly associated with a higher risk of death. Multivariate analysis demonstrated that only complete cytoreduction and stage II of the disease were significantly associated with a lower risk of death. The results of univariate and multivariate regression analysis (Cox regression model) to identify risk factors for disease recurrence or progress (N=490) are presented in Table 3. Table 3. Univariate and multivariate regression analysis of risk factors for disease recurrence or progress. Risk factor Univariate analysis (Hazard ratio, 95% CI) p-value Multivariate analysis (Hazard ratio, 95% CI) p-value Sex (female) 0.85 [0.62-1.15] 0.3 - - Age 1.00 [0.99-1.02] 0.6 - - The presence of any mutation 1.34 [0.97-1.84] 0.07 - - Wild-type gene - reference KRAS gene mutation NRAS gene mutation BRAF gene mutation 1.47 [1.06-2.04] 0.77 [0.31-1.92] 0.86 [0.41-1.80] 0.02* 0.6 0.7 1.61 [1.11-2.31] 1.22 [0.48-3.11] 1.23 [0.57-2.67] 0.01* 0.7 0.6 Primary tumor localization: Right colon - reference Left colon Rectum 1.07 [0.70-1.63] 1.31 [0.88-1.95] 0.7 0.2 - - - - Surgical treatment 0.38 [0.21-0.67] 0.001* - Complete cytoreduction 0.42 [0.24-0.74] 0.002* 1.18 [0.63-2.21] 0.6 Neoadjuvant chemotherapy 2.47 [1.77-3.43] <0.001* 1.52 [1.02-2.28] 0.04* Adjuvant chemotherapy 1.60 [0.95-2.72] 0.08 - - Stage: (IV – reference) I II III 0.27 [0.13-0.57] 0.18 [0.11-0.30] 0.26 [0.19-0.37] 0.001* <0.001* <0.001* 0.32 [0.14-0.72] 0.22 [0.13-0.38] 0.26 [0.17-0.40] 0.01* <0.005* <0.005* Stage T: (Т1 – reference) 2 3 4 0.78 [0.28-2.14] 0.84 [0.34-2.09] 1.54 [0.62-3.80] 0.6 0.7 0.4 - - - - - - Stage N: (N0 – reference) 1 2 1.25 [0.81-1.92] 2.06 [1.41-3.02] 0.3 <0.001* - - - - Stage M: (М0 - reference) 1a 1b 1c 3.85 [2.74-5.43] 6.32 [3.42-11.69 4.57 [2.43-8.59] <0.001* <0.001* <0.001* - - - - - - Metastasis localization: Liver Carcinomatosis Lungs Lymphatic nodes Other 5.10 [3.67-7.07] 2.56 [1.35-4.86] 1.70 [0.92-3.15] 1.94 [1.12-3.36] 2.87 [1.06-7.76] <0.001* 0.004* 0.09 0.02* 0.04* - - - - - - - - - - Synchronous cancer Metachronous cancer 1.11 [0.54-2.26] 0.99 [0.57-1.72] 0.8 0.9 - - - - Residual tumor: (R0 – reference) R1 3.58 [2.17-5.90] <0.001* 1.83 [1.07-3.13] 0.03* LVI 1.10 [0.65-1.85] 0.7 - - *p-value< 0.05, the difference is significant Univariate analysis demonstrated that a KRAS gene mutations, neoadjuvant chemotherapy, stage N2M1 (according to the TNM classification), liver, lymph nodes and other organs metastases, carcinomatosis and incomplete resection (R1) were associated with a higher risk of disease recurrence, while stages I-III compared with stage IV, surgical treatment and complete cytoreduction were associated with a lower risk of disease recurrence. Multivariate analysis demonstrated that only a KRAS gene mutations, neoadjuvant chemotherapy, and incomplete resection (R1) were significant risk factors for disease recurrence or progression, while stages I-III compared with stage IV were associated with a lower risk of disease recurrence. Discussion This cohort study demonstrates the results of the overall and disease-free survival analysis of colorectal cancer patients with RAS/ BRAF gene mutations. The Cox proportional hazards model allowed to identify predictors of death and relapse of colorectal cancer. The survival analysis revealed that patients with mutations in the KRAS , NRAS and BRAF genes have lower rates of 1- and 3-year overall and disease-free survival. In our study, the 3-year overall survival rate in patients with BRAF gene mutations was higher than in patients with the KRAS and NRAS genes mutations. We believe that this may be due to the fact that these patients have microsatellite instability (MSI) in their tumors more frequently, which gives them an advantage in survival [9]. Patients with NRAS gene mutations had significantly worse overall survival compared to the wild-type gene (p–value=0.04), and patients with a KRAS gene mutations had worse disease-free survival compared to the wild-type gene (p-value=0.02). Among the most common types of mutations in the KRAS and NRAS genes exons, survival rates were calculated for the KRAS Gly12Asp mutation: the median OS was 73 months (95% CI 73.0 – 73.0 months), the median DFS was 38 months (95% CI 17.0 – 62.0 months). In the retrospective study by Hirose T. et al [15] median progression-free survival was 9.2 months (95%CI: 7.8-12.2) and median OS was 25.8 months (95%CI: 18.8-39.8). Patients with wild-type genes, KRAS , NRAS and BRAF gene mutations differed significantly in age (p-value< 0.001), tumor localization (p-value< 0.001), neoadjuvant chemotherapy (p-value = 0.009), surgical treatment (p-value = 0.04), the disease recurrence/progress rate (p-value = 0.01), and the stage of the disease (p-value = 0.04). According to the results of numerous studies all of these features are recognized as risk factors of death: the age over 75 years (HR 2.54, 95% CI 2.04-3.16) [16–18] or younger (<=40 years, HR 1.87, 95% CI 1.09-3.47 [16], stage III-IV of the disease (HRadj, 3.04; 95% CI 1.79-5.18) [16,17,19], lack of surgical treatment (HR 1.36, 95% CI 1.007-1.83) [16] and perioperative chemotherapy (multivariate analysis: HR 1.65, 95% CI 1.17-2.33) [16,20], stage pT-pT4 (HR 2.59 95% CI 1.37-4.89) and pN2 (HR 2.12 95% CI 1.69-2.66) according to the TNM classification [21], the presence of distant (HRadj = 4.69, 95 CI 3.46-6.36) and regional (HRadj = 2.34, 95% CI 1.69-3.25) metastases [22], as well as left-sided localization of the primary tumors (in the transverse colon and splenic flexure (HRadj = 2.44, 95% CI 1.25-4.76), in the descending colon and sigmoid colon (HRadj = 2.01, 95% CI 1.26-3.20), in the rectosigmoid and rectum (HR = 2.00, 95% CI 1.24-3.24)) compared with the right-sided localization [22]. Thus, differences between the groups in these parameters could also affect the survival rates. In this regard, we conducted a regression analysis of the Cox proportional risks, which allowed us to assess the relationship between the presence or absence of mutations and the risk of death or disease recurrence/progress. Univariate and multivariate analysis did not confirm that mutations increased the risk of death. However, according to studies, the KRAS gene mutations were associated with worse overall survival (HR = 1.27, 95% CI (1.03-1.55), p-value = 0,03) [8–10,16,20,21,23], as well as the BRAF V600E mutation (HR = 1.49, 95% CI (1.31-1.70), p-value < 0.001) and NRAS gene mutations (HR=1.36.95% CI (1,15–1,61)) [8–10,24,25]. The KRAS gene mutations were a risk factor for disease progression or recurrence in univariate and multivariate analysis (HR=1.47 95% CI (1.06-2.04), p-value=0.02 and HR=1.61 95% CI (1.11-2.31), p-value=0.01, respectively). Mutations in KRAS and BRAF were associated with shorter disease-free period and survival after relapse [10]. These mutations were also associated with lower disease-free survival rates (for patients with the KRAS mutation: HR = 1.36, 95% CI (1.15-1.61); with the BRAF mutation: HR = 1.33, 95% CI (1,00-1,78)) [7–9,21,25]. The study showed that the independent risk factors of death were only stage IV of the disease (compared with stage II (p-value=0.01)) and incomplete cytoreduction (p-value<0.005), while disease recurrence predictors were KRAS gene mutations (p–value=0.01), neoadjuvant therapy (p-value=0.04), stage IV of the disease (compared with stage I (p-value=0.01), stage II (p-value<0.005), stage III (p-value<0.005), ) and incomplete resection (R1) (p-value=0.03). Regarding neoadjuvant chemotherapy it was demonstrated to increase the risk of death (HR= 2.81 95% CI (1.53-5.17), p-value=0.001) and relapse of the disease (HR=2.47 95% CI (1.77-3.43), p-value<0.001, HR adj. = 1.52 95% CI (1.02-2.28), p-value=0.04). In subgroup analysis for patients with stage IV colorectal cancer the neoadjuvant chemotherapy was also a death (HR = 2.15 95% CI (1.15-4.00), p-value=0.02) and recurrence predictor (HR=2.19 95% CI (1.54-3.13), p-value<0.001). Jiang Yu-Juan [26] also showed that the neoadjuvant chemotherapy was a risk factor of death for stage IV colorectal cancer patients however the results were statistically insignificant (HR =1.10 95% CI (0.70 -1.72), p-value=0.685). The neoadjuvant chemotherapy improved 5-year OS (p-value = 0.048) and DFS (p-value= 0.040) only for patients with more than three liver metastases, while patients with fewer than three liver metastases showed no survival benefit. [26]. Several studies showed no impact of neoadjuvant chemotherapy on survival outcomes for patients with advanced CRC [27,28]. However the meta-analysis demonstrated significant improvement in OS and DFS for patients with advanced CRC and neoadjuvant chemotherapy [29] In our practice neoadjuvant chemotherapy is usually prescribed for patients with advanced stages and for primary non-surgical patients to reduce the stage. As a result, variable clinical characteristics may result in selection bias and lead to incorrect results. Thus, the overall and disease-free survival of patients with colorectal cancer largely depends on time of diagnosis and radical and complete surgical interventions. Limitations and advantages This study had some limitations. Despite the fact that the Ryzhikh National Medical Research Center of Coloproctology is a large specialized federal center in Russia for the treatment of colorectal cancer, a single-center study design could lead to the selection bias. Due to the short follow-up period and the small number of target events for assessing long-term outcomes, it was not possible to fully calculate the median and confidence intervals for overall and disease-free survival for most subgroups. For this reason it was not possible to calculate survival rates for patients at different stages separately: no deaths were recorded during follow-up at stage I, the number of deaths at stage II was 2, at stage III – 8, at stage IV – 36. When comparing the groups with wild-type and RAS/ BRAF gene mutations significant differences were obtained in several demographic and clinical features, which could also affect the survival rates in the groups. Thus, the results of this study demonstrate the need for further research in this area. Conclusion The independent risk factors of death from CRC were stage IV compared with stage II and incomplete cytoreduction, while disease recurrence independent predictors were KRAS gene mutations, neoadjuvant therapy, stage IV compared with stage I, II and III, and incomplete resection (R1). Thus, early colorectal cancer diagnostic and radical and complete tumor resection allow to improve overall and disease-free survival for all patients. Declarations The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. The authors have no relevant financial or non-financial interests to disclose. The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request. This study was performed in line with the principles of the Declaration of Helsinki. The study was approved by the Local Ethical Committee of the Ryzhikh National Medical Research Center of Coloproctology. Informed consent was obtained from all individual participants included in the study. All authors work in civil hospitals or in educational organizations and none of them are currently involved in any other kind of activity (including military, political or economical) and never were. Authors contribution Conceptualization: Tsukanov A.S., Khomyakov E.A. Data curation: Khomyakov E.A. Formal analysis: Kazachenko E.A. Investigation: Shubin V.P., Methodology: Otstanov S.S., Khomyakov E.A., Project administration: Otstanov S.S., Tsukanov A.S. Resources: Shubin V.P. Software: Kazachenko E.A. Supervision: Tsukanov A.S., Rybakov E.G. Validation: Khomyakov E.A., Visualization: Kazachenko E.A. Writing – original draft: Khomyakov E.A., Tsukanov A.S. Writing – review & editing: Rybakov E.G., Shelygin Yu.A. References Bray F, Laversanne M, Sung H, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2024;74:229–63. https://doi.org/10.3322/caac.21834 . Seshacharyulu P, Ponnusamy MP, Haridas D, et al. Targeting the EGFR signaling pathway in cancer therapy. Expert Opin Ther Targets. 2012;16. https://doi.org/10.1517/14728222.2011.648617 . Kazachenko EA, Shubin VP, Otstanov SS, et al. The RAS/BRAF genes status in patients with colorectal cancer (review). Koloproktologia. 2024;23:112–25. https://doi.org/10.33878/2073-7556-2024-23-3-112-125 . Bou Antoun N, Chioni AM. Dysregulated Signalling Pathways Driving Anticancer Drug Resistance. Int J Mol Sci. 2023;24. https://doi.org/10.3390/ijms241512222 . Levin-Sparenberg E, Bylsma LC, Lowe K, et al. A Systematic Literature Review and Meta-Analysis Describing the Prevalence of KRAS, NRAS, and BRAF Gene Mutations in Metastatic Colorectal Cancer. Gastroenterol Res. 2020;13. https://doi.org/10.14740/gr1167 . Zeng J, Fan W, Li J, et al. KRAS/NRAS Mutations Associated with Distant Metastasis and BRAF/PIK3CA Mutations Associated with Poor Tumor Differentiation in Colorectal Cancer. Int J Gen Med. 2023;16. https://doi.org/10.2147/ijgm.s428580 . Taieb J, Sinicrope FA, Pederson L, et al. Different prognostic values of KRAS exon 2 submutations and BRAF V600E mutation in microsatellite stable (MSS) and unstable (MSI) stage III colon cancer: an ACCENT/IDEA pooled analysis of seven trials. Ann Oncol. 2023;34. https://doi.org/10.1016/j.annonc.2023.08.006 . Margonis GA, Buettner S, Andreatos N et al. Association of BRAF mutations with survival and recurrence in surgically treated patients with metastatic colorectal liver cancer. JAMA Surg 2018;153. https://doi.org/10.1001/jamasurg.2018.0996 Orlandi E, Giuffrida M, Trubini S, et al. Unraveling the Interplay of KRAS, NRAS, BRAF, and Micro-Satellite Instability in Non-Metastatic Colon Cancer: A Systematic Review. Diagnostics. 2024;14:1001. https://doi.org/10.3390/diagnostics14101001 . Kadowaki S, Kakuta M, Takahashi S, et al. Prognostic value of KRAS and BRAF mutations in curatively resected colorectal cancer. World J Gastroenterol. 2015;21. https://doi.org/10.3748/wjg.v21.i4.1275 . Afrǎsânie VA, Marinca MV, Alexa-Stratulat T, et al. KRAS, NRAS, BRAF, HER2 and microsatellite instability in metastatic colorectal cancer-practical implications for the clinician. Radiol Oncol. 2019;53. https://doi.org/10.2478/raon-2019-0033 . Tonello M, Baratti D, Sammartino P, et al. Prognostic value of specific KRAS mutations in patients with colorectal peritoneal metastases. ESMO Open. 2024;9:102976. https://doi.org/10.1016/j.esmoop.2024.102976 . Shubin VP, Shelygin Yu A, Achkasov SI. Influence of somatic mutations of KRAS, NRAS, BRAF and microsatellite instability status on survival of colorectal cancer patients with peritonal carcinomatosis. Siberian J Oncol. 2020;19(5):61–7. https://doi.org/10.21294/1814-4861-2020-19-5-61-67 . (In Russ.). Kaganov O, Toropova N, Shvets D et al. Research of the mutational status of KRAS gene and indicators of survival after cytoreductive operations at patients with colorectal cancer metastasises in liver. News of the Samara Scientific Center of the Russian Academy of Sciences 2015; V. 17, № 2(3): 534–537 (In Russ.). Hirose T, Matsuguma K, Hirano H, et al. A retrospective analysis of the prognostic impact of KRAS G12D mutation in patients with RAS -mutated metastatic colorectal cancer. J Clin Oncol. 2024;42. https://doi.org/10.1200/jco.2024.42.3_suppl.105 . Alyabsi M, Sabatin F, Ramadan M, et al. Colorectal cancer survival among Ministry of National Guard-Health Affairs (MNG-HA) population 2009–2017: retrospective study. BMC Cancer. 2021;21. https://doi.org/10.1186/s12885-021-08705-8 . Le DD, Vo T, Van SP. Overall Survival Rate Of Vietnamese Patients With Colorectal Cancer: A Hospital-Based Cohort Study In The Central Region Of Vietnam. Asian Pac J Cancer Prev. 2021;22. https://doi.org/10.31557/APJCP.2021.22.11.3569 . Aguiar Junior S, de OLIVEIRA MM E, Silva DRM, et al. Survival of patients with colorectal cancer in a cancer center. Arq Gastroenterol. 2020;57. https://doi.org/10.1590/s0004-2803.202000000-32 . Maajani K, Khodadost M, Fattahi A, et al. Survival rate of colorectal cancer in Iran: A systematic review and meta-analysis. Asian Pac J Cancer Prev. 2019;20. https://doi.org/10.31557/APJCP.2019.20.1.13 . Tran CG, Goffredo P, Mott SL, et al. Conditional Overall Survival After Diagnosis of Non-Metastatic Colon Cancer: Impact of Laterality, MSI, and KRAS Status. Ann Surg Oncol. 2024;31. https://doi.org/10.1245/s10434-023-14443-x . Taieb J, Kourie HR, Emile J-F, et al. Association of Prognostic Value of Primary Tumor Location in Stage III Colon Cancer With RAS and BRAF Mutational Status. JAMA Oncol. 2018;4:e173695. https://doi.org/10.1001/jamaoncol.2017.3695 . Lee SHF, Abdul Rahman H, Abidin N, et al. Survival of colorectal cancer patients in Brunei Darussalam: comparison between 2002–09 and 2010–17. BMC Cancer. 2021;21. https://doi.org/10.1186/s12885-021-08224-6 . Asawa P, Bakalov V, Kancharla P, et al. The prognostic value of KRAS mutation in locally advanced rectal cancer. Int J Colorectal Dis. 2022;37. https://doi.org/10.1007/s00384-022-04167-x . Hu Y, Tao SY, Deng JM, et al. Prognostic value of NRAS gene for survival of colorectal cancer patients: A systematic review and meta-analysis. Asian Pac J Cancer Prev. 2018;19. https://doi.org/10.31557/APJCP.2018.19.11.3001 . Formica V, Sera F, Cremolini C, et al. KRAS and BRAF Mutations in Stage II and III Colon Cancer: A Systematic Review and Meta-Analysis. J Natl Cancer Inst. 2022;114. https://doi.org/10.1093/jnci/djab190 . Jiang YJ, Zhou SC, Chen JH, et al. Oncological outcomes of neoadjuvant chemotherapy in patients with resectable synchronous colorectal liver metastasis: A result from a propensity score matching study. Front Oncol. 2022;12. https://doi.org/10.3389/fonc.2022.951540 . Park SH, Shin JK, Lee WY, et al. Clinical outcomes of neoadjuvant chemotherapy in colorectal cancer patients with synchronous resectable liver metastasis: A propensity score matching analysis. Ann Coloproctol. 2021;37. https://doi.org/10.3393/AC.2020.00710.0101 . Milito P, Sorrentino L, Pietrantonio F, et al. No benefit after neoadjuvant chemoradiation in stage IV rectal cancer: A propensity score-matched analysis on a real-world population. Dig Liver Dis. 2021;53. https://doi.org/10.1016/j.dld.2021.01.013 . Aliseda D, Arredondo J, Sánchez-Justicia C, et al. Survival and safety after neoadjuvant chemotherapy or upfront surgery for locally advanced colon cancer: meta-analysis. Br J Surg. 2024;111. https://doi.org/10.1093/bjs/znae021 . Additional Declarations No competing interests reported. Supplementary Files SupportingInformation.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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1","display":"","copyAsset":false,"role":"figure","size":67551,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7657018/v1/fa7dd79ad21082c29b5319e4.png"},{"id":93008973,"identity":"21320f62-4b11-4c86-806f-b1d7c188123c","added_by":"auto","created_at":"2025-10-08 07:05:54","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":83336,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7657018/v1/14eff177c25e2444c085650c.png"},{"id":97673253,"identity":"6953481e-f23f-4d51-9c36-5a72983442d4","added_by":"auto","created_at":"2025-12-08 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commonly diagnosed cancer and the second leading cause of oncologic death worldwide [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The RAS/RAF/MAPK/ERK signaling pathway plays an important role in the development of CRC as in most epithelial neoplasms and serves as a target for anti-EGFR therapy [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. However, in 50\u0026ndash;60% of cases CRC does not respond to anti-EGFR therapy [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. This is due to the somatic activation of the RAS/RAF/MAPK/ERK pathway by \u003cem\u003eKRAS\u003c/em\u003e, \u003cem\u003eNRAS\u003c/em\u003e and \u003cem\u003eBRAF\u003c/em\u003e genes mutations [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Patients with such mutations have lower rates of overall and disease-free survival, shorter time to relapse, and survival after relapse [\u003cspan additionalcitationids=\"CR6 CR7 CR8 CR9 CR10\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. In recent studies more attention has been paid to the type of mutations, since the survival rates do not seem to differ between patients with RAS/\u003cem\u003eBRAF\u003c/em\u003e gene mutations and wild-type genes [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The study by Tonello M. et al. [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] showed that the median survival of patients with G12R, G13A, G13C, G13V, Q61H, K117N, A146V \u003cem\u003eKRAS\u003c/em\u003e mutations with peritoneal carcinomatosis after cytoreductive surgery was more than 120 months while the median survival of patients with G12A, G12C, G12D, G12S, G12V, G13D, A59E, A59V, A146T \u003cem\u003eKRAS\u003c/em\u003e mutations was 31.2 months.\u003c/p\u003e\u003cp\u003eIn Russian studies, long-term oncological outcomes in patients with the RAS/\u003cem\u003eBRAF\u003c/em\u003e gene mutations were assessed in two contradictory studies with grade IV colorectal cancer patients [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In one study, the presence of mutations did not affect overall and disease\u0026ndash;free survival, while in the other mutations were poor prognosis predictors.\u003c/p\u003e\u003cp\u003eThus, the survival of patients with CRC with a RAS/\u003cem\u003eBRAF\u003c/em\u003e mutations in the Russian cohort remains unclear.\u003c/p\u003e\n\u003ch3\u003eAim\u003c/h3\u003e\n\u003cp\u003eThe aim of the study was to compare long-term outcomes in patients with colorectal cancer with \u003cem\u003eKRAS\u003c/em\u003e, \u003cem\u003eNRAS\u003c/em\u003e, and \u003cem\u003eBRAF\u003c/em\u003e gene mutations and wild-type genes.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003eThis retrospective cohort study was performed on the basis of the database of the Department of Laboratory Genetics of the Ryzhikh National Medical Research Center of Coloproctology of the Ministry of Health of the Russian Federation. The database included 682 patients who underwent molecular genetic testing for mutations in the \u003cem\u003eKRAS\u003c/em\u003e, \u003cem\u003eNRAS\u003c/em\u003e, and \u003cem\u003eBRAF\u003c/em\u003e genes from 01.2020 to 06.2023. The comparative analysis included 647 patients, and the overall survival analysis included 611 patients while disease-free survival analysis included 490 patients. Additional clinical information (demographic and clinical parameters) was collected based on medical records.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eEligibility criteria\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe study included patients over 18 years old with a verified colorectal cancer who underwent molecular genetic testing for mutations in the \u003cem\u003eKRAS\u003c/em\u003e, \u003cem\u003eNRAS\u003c/em\u003e, and \u003cem\u003eBRAF\u003c/em\u003e genes. Patients with incomplete clinical information in their medical records were excluded from the analysis:\u003c/p\u003e\n\u003cp\u003e\u0026bull; Lack of a formulated diagnosis according to the TNM classification;\u003c/p\u003e\n\u003cp\u003e\u0026bull; No information about primary tumor and the tumor histopathology;\u003c/p\u003e\n\u003cp\u003e\u0026bull; Lost contact with the patient and lost records in patients\u0026rsquo; database.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePrimary endpoint\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u0026bull; Overall and disease-free survival in patients with \u003cem\u003eKRAS\u003c/em\u003e, \u003cem\u003eNRAS\u003c/em\u003e and \u003cem\u003eBRAF\u003c/em\u003e gene mutations, and wild-type genes\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSecondary endpoints\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u0026bull; 1-year and 3-year overall and disease-free survival in patients with \u003cem\u003eKRAS\u003c/em\u003e, \u003cem\u003eNRAS\u003c/em\u003e, \u003cem\u003eBRAF\u0026nbsp;\u003c/em\u003egene\u003cem\u003e\u0026nbsp;\u003c/em\u003emutations and wild-type genes\u003c/p\u003e\n\u003cp\u003e\u0026bull; Risk factors for death and disease recurrence in patients with mutations and wild-type genes\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSequencing using the Sanger method\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTo determine mutations in the \u003cem\u003eKRAS\u003c/em\u003e (RefSeq_NM_004985) (2-4 exons), \u003cem\u003eNRAS\u003c/em\u003e (RefSeq_NM_002524) (2-3 exons), and \u003cem\u003eBRAF\u003c/em\u003e (RefSeq_NM_004333) (15 exons) genes, fragments were amplified using polymerase chain reaction on a Veriti programmable thermal cycler (Applied Biosystems, USA) using original oligonucleotide seed primers. Sequencing was performed on an automatic capillary sequencer ABI PRISM 3500 (8 capillaries; Applied Biosystems, USA). The UniPro Ugene v.47 software was used to interpret the sequencing results. The reference sequence was generated in fasta format from an open source https://www.ensembl.org /.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eStatistical analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTo describe quantitative features median, upper and lower quartiles (IQR \u0026ndash; interquartile range), maximum and minimum values were calculated. Absolute and relative frequencies were used to describe categorical features. The difference between the groups was considered significant with a p-value \u0026lt; 0.05.\u003c/p\u003e\n\u003cp\u003eThe comparative analysis was performed using the R language version 4.4.1. For statistical comparison, the Chi-square test was used when an expected frequency of observations \u0026ge;5 in at least 80% of cells for multipole tables or the exact Fisher test (Fisher\u0026apos;s exact test) for categorical features and the Kruskal-Wallis test for quantitative features.\u003c/p\u003e\n\u003cp\u003eThe survival analysis was performed using the high-level programming language Python 3.9.10 (libraries scipy version 1.13. and lifelines version 0.29.0) based on the Visual Studio Code text editor, Microsoft. (2022) version 1.87.2 using the Kaplan-Meier estimator with the calculation of median survival and 95% confidence interval (CI). To compare the survival curves, a Log-rank test was performed. When calculating disease-free survival, only episodes of relapse or disease progress were considered as target events. To identify risk factors for death and relapse/disease progress, univariate and multivariate regression models of Cox proportional hazards (Cox proportional hazards model) were constructed with the calculation of the hazard ratio (HR), 95% confidence interval (CI) and p-value. The multivariate regression analysis included only those features that turned out to be risk factors in the univariate analysis and which were not the cause of multicollinearity when simultaneously present with other features. The assumption of risk proportionality was verified by visually evaluating the distribution of Schoenfeld residues over time and calculating the p-value using a test based on the correlation between Schoenfeld residues and time.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eEthical statements\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe study\u0026rsquo;s protocol was reviewed and approved by the Local Ethical Committee of Ryzhikh National Medical Research Center of Coloproctology (№ 105, 03.02.2025). The study was conducted in accordance with the World Medical Association (WMA) Declaration of Helsinki: Medical Research Involving Human Subjects.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eA comparative analysis of the \u003cem\u003eKRAS\u003c/em\u003e, \u003cem\u003eNRAS\u003c/em\u003e, and \u003cem\u003eBRAF\u003c/em\u003e gene mutations frequency was performed depending on the patients\u0026rsquo; demographic and clinical characteristic (Table 1).\u003c/p\u003e\n\u003cp\u003eTable 1. Comparative characteristics of patients with RAS/\u003cem\u003eBRAF\u003c/em\u003e gene mutations.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"775\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eFeature\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 489px;\"\u003e\n \u003cp\u003eFrequency\u0026nbsp;(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 131px;\"\u003e\n \u003cp\u003eWild-type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cem\u003eKRAS\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003egene mutations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e\u003cem\u003eNRAS\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003egene mutations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u003cem\u003eBRAF\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003egene mutations\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003eTotal patients\u003c/p\u003e\n \u003cp\u003eN=647 (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 131px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e252 (38.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e310 (47.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e33 (5.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e52 (8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003eAge, years\u003c/p\u003e\n \u003cp\u003e(median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 131px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e58 (46, 66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e61 (51, 68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e67 (52 , 71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e67 (60, 73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt; 0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003eSex:\u003c/p\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 131px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e131 (52%)\u003c/p\u003e\n \u003cp\u003e121 (48%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e131 (42.3%)\u003c/p\u003e\n \u003cp\u003e179 (57.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e13 (39,4%)\u003c/p\u003e\n \u003cp\u003e20 (60,6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e19 (36,5%)\u003c/p\u003e\n \u003cp\u003e33 (63,5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.051\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003ePrimary tumor localization:\u003c/p\u003e\n \u003cp\u003eRight colon\u003c/p\u003e\n \u003cp\u003eLeft colon\u003c/p\u003e\n \u003cp\u003eRectum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 131px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e44 (17.5%)\u003c/p\u003e\n \u003cp\u003e102 (40.5%)\u003c/p\u003e\n \u003cp\u003e106 (42.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e74 (23.9%)\u003c/p\u003e\n \u003cp\u003e98 (31.6%)\u003c/p\u003e\n \u003cp\u003e138 (44.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e10 (30.3%)\u003c/p\u003e\n \u003cp\u003e5 (15.2%)\u003c/p\u003e\n \u003cp\u003e18 (54.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e35 (67.3%)\u003c/p\u003e\n \u003cp\u003e13 (25%)\u003c/p\u003e\n \u003cp\u003e4 (7.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt; 0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003eNeoadjuvant chemotherapy:\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 131px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e73 (29%)\u003c/p\u003e\n \u003cp\u003e173 (68.7%)\u003c/p\u003e\n \u003cp\u003e6 (2.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e82 (26.5%)\u003c/p\u003e\n \u003cp\u003e216 (69.7%)\u003c/p\u003e\n \u003cp\u003e12 \u0026nbsp; \u0026nbsp; (3.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e8 (24.2%)\u003c/p\u003e\n \u003cp\u003e24 (72.7%)\u003c/p\u003e\n \u003cp\u003e1 (3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3 (5.8%)\u003c/p\u003e\n \u003cp\u003e45 (86.6%)\u003c/p\u003e\n \u003cp\u003e4 (7.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.009*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003eDisease relapse/progress:\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 131px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e61 (24.2%)\u003c/p\u003e\n \u003cp\u003e141 (56%)\u003c/p\u003e\n \u003cp\u003e50 (19.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e99 (31.9%)\u003c/p\u003e\n \u003cp\u003e138 (44.5%)\u003c/p\u003e\n \u003cp\u003e73 (23.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e5 (15.2%)\u003c/p\u003e\n \u003cp\u003e18 (54.6%)\u003c/p\u003e\n \u003cp\u003e10 (30.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e9 (17.3%)\u003c/p\u003e\n \u003cp\u003e30 (57.7%)\u003c/p\u003e\n \u003cp\u003e13 (25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.01*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003eStage\u003c/p\u003e\n \u003cp\u003eI-II\u003c/p\u003e\n \u003cp\u003eIII-IV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 131px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e62 (24.6%)\u003c/p\u003e\n \u003cp\u003e190 (75.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e69 (22.3%)\u003c/p\u003e\n \u003cp\u003e241 (77.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e10 (30.3%)\u003c/p\u003e\n \u003cp\u003e23 (69.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e21 (40.4%)\u003c/p\u003e\n \u003cp\u003e31 (59.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.04*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003eSynchronous cancer\u003c/p\u003e\n \u003cp\u003eMetachronous cancer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 131px;\"\u003e\n \u003cp\u003e12 (4.8%)\u003c/p\u003e\n \u003cp\u003e14 (5.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e15 (4.8%)\u003c/p\u003e\n \u003cp\u003e22 (7.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e2 (6.1%)\u003c/p\u003e\n \u003cp\u003e3 (9.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e1 (1.9%)\u003c/p\u003e\n \u003cp\u003e4 (7.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 775px;\"\u003e\n \u003cp\u003eCharacteristic of patients after surgery\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003eSurgical treatment:\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 131px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e226 (89.3%)\u003c/p\u003e\n \u003cp\u003e26 (10.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e255 (82.3%)\u003c/p\u003e\n \u003cp\u003e55 (17.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e31 (93.9%)\u003c/p\u003e\n \u003cp\u003e2\u0026nbsp;(6.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e46 (88.5%)\u003c/p\u003e\n \u003cp\u003e6 (11.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.04*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003eAdjuvant chemotherapy\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 131px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e187 (82.7%)\u003c/p\u003e\n \u003cp\u003e35 (15.5%)\u003c/p\u003e\n \u003cp\u003e4 (1.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e225 (88.2%)\u003c/p\u003e\n \u003cp\u003e27 (10.6%)\u003c/p\u003e\n \u003cp\u003e3 (1.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e25 (80.6%)\u003c/p\u003e\n \u003cp\u003e6 (19.4%)\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e33 (71.7%)\u003c/p\u003e\n \u003cp\u003e10 (21.7%)\u003c/p\u003e\n \u003cp\u003e3 (6.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003eCytoreduction:\u003c/p\u003e\n \u003cp\u003eIncomplete\u003c/p\u003e\n \u003cp\u003eComplete\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 131px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e17 (7.5%)\u003c/p\u003e\n \u003cp\u003e209 (92.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e30 (11.8%)\u003c/p\u003e\n \u003cp\u003e225 (88.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3 (9.7%)\u003c/p\u003e\n \u003cp\u003e28 (90.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e8 (17.4%)\u003c/p\u003e\n \u003cp\u003e38\u0026nbsp;(82.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003eResidual tumor:\u003c/p\u003e\n \u003cp\u003eR0\u003c/p\u003e\n \u003cp\u003eR1\u003c/p\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 131px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e202 (89.4%)\u003c/p\u003e\n \u003cp\u003e18 (8%)\u003c/p\u003e\n \u003cp\u003e6 (2.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e233 (91.4%)\u003c/p\u003e\n \u003cp\u003e13 (5.1%)\u003c/p\u003e\n \u003cp\u003e9 (3.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e28 (90.3%)\u003c/p\u003e\n \u003cp\u003e3 (9.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e44 (95.7%)\u003c/p\u003e\n \u003cp\u003e2 (4.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e* p-value\u0026lt; 0.05, the difference is significant\u003c/p\u003e\n\u003cp\u003eThe frequency of RAS/\u003cem\u003eBRAF\u003c/em\u003e genes mutations was 395/647 (61.1%). The distribution of the mutation frequencies is presented in the Supplementary materials (Table 4).\u003c/p\u003e\n\u003cp\u003eThe median follow\u0026ndash;up for patients with wild\u0026ndash;type genes was 24 months (IQR 10-37 months), with \u003cem\u003eKRAS\u003c/em\u003e gene mutations \u0026ndash; 21 months (IQR 9-34 months), with \u003cem\u003eNRAS\u003c/em\u003e gene mutations - 14 months (IQR 4-31 months), with \u003cem\u003eBRAF\u003c/em\u003e gene mutations - 21.5 months (IQR 4.8-29.3 months).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSurvival analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe median overall survival (OS) was 82 months, 95% CI 73 \u0026ndash; +\u0026infin; months. The median survival of \u003cem\u003eKRAS\u003c/em\u003e gene mutation patients was 82 months, 95% CI 73 \u0026ndash; +\u0026infin; months. The medians for the other subgroups could not be calculated due to the insufficient number of target events (deaths) (Fig. 1).\u003c/p\u003e\n\u003cp\u003eAccording to the results of the log-rank test, significant differences were observed only between patients with \u003cem\u003eNRAS\u003c/em\u003e gene mutations and with wild-type gene (p-value=0.04).\u003c/p\u003e\n\u003cp\u003eThe overall 1-year survival rate was 95%, for patients with wild type genes - 96%, with \u003cem\u003eKRAS\u003c/em\u003e gene mutations - 95%, with \u003cem\u003eNRAS\u003c/em\u003e gene mutations - 86%, and with \u003cem\u003eBRAF\u003c/em\u003e gene mutations - 94%. The overall 3-year survival rate was 79% and 86%, 74%, 67%, and 78% for patients with wild-type genes, \u003cem\u003eKRAS\u003c/em\u003e, \u003cem\u003eNRAS\u003c/em\u003e and \u003cem\u003eBRAF\u003c/em\u003e gene mutations, respectively.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe disease-free survival (DFS) analysis included 490 patients with a known disease relapse/progress status. The median DFS was 60 months, 95% CI 51-72 months. The median DFS for patients with \u003cem\u003eKRAS\u003c/em\u003e gene mutations was 48 months, 95% CI 32-74 months. For patients with wild-type genes, the median DFS was 60 months, 95% CI 57 - +\u0026infin; months. The medians for the other subgroups could not be calculated due to the insufficient number of target events (relapse or disease progress) (Fig. 2)\u003c/p\u003e\n\u003cp\u003eSignificant differences in DFS were found only between patients with the wild-type genes and with \u003cem\u003eKRAS\u003c/em\u003e gene mutations. The disease-free period in \u003cem\u003eKRAS\u003c/em\u003e gene mutation patients was significantly shorter than in patients with the wild-type genes (p-value = 0.02).\u003c/p\u003e\n\u003cp\u003eThe overall 1-year disease-free survival rate was 79%, for patients with the wild-type genes - 81%, for patients with \u003cem\u003eKRAS\u003c/em\u003e gene mutations - 75%, for \u003cem\u003eNRAS\u003c/em\u003e gene mutations - 94%, and for \u003cem\u003eBRAF\u003c/em\u003e gene mutations - 83%. The overall 3-year DFS rate was 42% and 50%, 34%, 50%, and 46% for patients with wild-type genes, \u003cem\u003eKRAS\u003c/em\u003e, \u003cem\u003eNRAS\u003c/em\u003e and \u003cem\u003eBRAF\u003c/em\u003e gene mutations, respectively.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe results of univariate and multivariate regression analysis (Cox regression model) to identify risk factors of death (N=611) are presented in Table 2.\u003c/p\u003e\n\u003cp\u003eTable 2. Univariate and multivariate regression analysis of risk factors of death.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"756\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eRisk factor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eUnivariate analysis (Hazard ratio, 95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003emultivariate analysis (Hazard ratio, 95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eSex (female)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e0.77\u0026nbsp;[0.43-1.38]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e1.06 [1.03-1.09]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e1.02 [0.98-1.06]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eThe presence of any mutation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e1.85 [0.97-3.52]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eWild-type gene - reference\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eKRAS\u0026nbsp;\u003c/em\u003egene mutation\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eNRAS\u003c/em\u003e gene mutation\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eBRAF\u003c/em\u003e gene mutation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.85 [0.95-3.58]\u003c/p\u003e\n \u003cp\u003e3.08 [1.00-9.50]\u003c/p\u003e\n \u003cp\u003e1.04 [0.23-4.63]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.92 [0.74-4.97]\u003c/p\u003e\n \u003cp\u003e0.0 [0.0-inf]\u003c/p\u003e\n \u003cp\u003e0.53 [0.06-5.18]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003ePrimary tumor localization:\u003c/p\u003e\n \u003cp\u003eRight colon - reference\u003c/p\u003e\n \u003cp\u003eLeft colon\u003c/p\u003e\n \u003cp\u003eRectum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.70 [0.31-1.56]\u003c/p\u003e\n \u003cp\u003e1.36 [0.67-2.75]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eSurgical treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e0.23 [0.11-0.47]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e0.56 [0.06-5.19]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eComplete cytoreduction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e0.10 [0.05-0.19]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e0.20 [0.07-0.61]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026lt;0.005*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eNeoadjuvant chemotherapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e2.81 [1.53-5.17]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eAdjuvant chemotherapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e1.27 [0.45-3.60]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eDisease relapse/progress\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e4.16 [1.60-10.81]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.003*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eStage: (IV \u0026ndash; reference)\u003c/p\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003cp\u003eII\u003c/p\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.00 [0.00-inf]\u003c/p\u003e\n \u003cp\u003e0.06 [0.01-0.25]\u003c/p\u003e\n \u003cp\u003e0.12 [0.06-0.27]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0 [0.00-inf]\u003c/p\u003e\n \u003cp\u003e0.07 [0.01-0.60]\u003c/p\u003e\n \u003cp\u003e0.33 [0.11-1.04] \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003cp\u003e0.01*\u003c/p\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eStage T: (Т1 \u0026ndash; reference)\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.22 [0.01-3.50]\u003c/p\u003e\n \u003cp\u003e1.34 [0.18-9.99]\u003c/p\u003e\n \u003cp\u003e1.66 [0.22-12.37]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eStage N: (N0 \u0026ndash; reference)\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.82 [1.01-7.83]\u003c/p\u003e\n \u003cp\u003e4.66 [1.79-12.12]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.05*\u003c/p\u003e\n \u003cp\u003e0.002*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eStage M: (М0 - reference)\u003c/p\u003e\n \u003cp\u003e1a\u003c/p\u003e\n \u003cp\u003e1b\u003c/p\u003e\n \u003cp\u003e1c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e10.42 [4.94-21.94]\u003c/p\u003e\n \u003cp\u003e14.91 [5.80-38.31]\u003c/p\u003e\n \u003cp\u003e7.05 [2.19-22.71]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003cp\u003e0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eMetastasis localization:\u003c/p\u003e\n \u003cp\u003eLiver\u003c/p\u003e\n \u003cp\u003eCarcinomatosis\u003c/p\u003e\n \u003cp\u003eLungs\u003c/p\u003e\n \u003cp\u003eLymphatic nodes\u003c/p\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e6.52 [3.60-11.82]\u003c/p\u003e\n \u003cp\u003e2.92 [1.14-7.47]\u003c/p\u003e\n \u003cp\u003e5.33 [2.62-10.86]\u003c/p\u003e\n \u003cp\u003e1.28 [0.39-4.13]\u003c/p\u003e\n \u003cp\u003e2.47 [0.34-18.02]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003cp\u003e0.02*\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eSynchronous cancer\u003c/p\u003e\n \u003cp\u003eMetachronous cancer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e1.42 [0.44-4.59]\u003c/p\u003e\n \u003cp\u003e0.29 [0.04-2.08]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eResidual tumor: (R0 \u0026ndash; reference)\u003c/p\u003e\n \u003cp\u003eR1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.67 [0.51-5.48]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eLVI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e1.73 [0.52-5.70]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*p-value\u0026lt; 0.05, the difference is significant\u003c/p\u003e\n\u003cp\u003eUnivariate analysis demonstrated that a younger age, surgical treatment with complete cytoreduction, stage II and III of the disease compared with stage IV were significantly associated with a lower risk of death, while neoadjuvant CT, the regional lymph nodes and distant metastases (N1-2M1 according to the TNM classification), liver, lung and peritoneal metastases, as well as the disease recurrence were significantly associated with a higher risk of death. Multivariate analysis demonstrated that only complete cytoreduction and stage II of the disease were significantly associated with a lower risk of death.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe results of univariate and multivariate regression analysis (Cox regression model) to identify risk factors for disease recurrence or progress (N=490) are presented in Table 3.\u003c/p\u003e\n\u003cp\u003eTable 3. Univariate and multivariate regression analysis of risk factors for disease recurrence or progress.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"756\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eRisk factor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eUnivariate analysis (Hazard ratio, 95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eMultivariate analysis (Hazard ratio, 95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eSex (female)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e0.85 [0.62-1.15]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e1.00 [0.99-1.02]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eThe presence of any mutation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e1.34 [0.97-1.84]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eWild-type gene - reference\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eKRAS\u0026nbsp;\u003c/em\u003egene mutation\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eNRAS\u003c/em\u003e gene mutation\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eBRAF\u003c/em\u003e gene mutation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.47 [1.06-2.04]\u003c/p\u003e\n \u003cp\u003e0.77 [0.31-1.92]\u003c/p\u003e\n \u003cp\u003e0.86 [0.41-1.80]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.02*\u003c/p\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.61 [1.11-2.31]\u003c/p\u003e\n \u003cp\u003e1.22 [0.48-3.11]\u003c/p\u003e\n \u003cp\u003e1.23 [0.57-2.67]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.01*\u003c/p\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003ePrimary tumor localization:\u003c/p\u003e\n \u003cp\u003eRight colon - reference\u003c/p\u003e\n \u003cp\u003eLeft colon\u003c/p\u003e\n \u003cp\u003eRectum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.07 [0.70-1.63]\u003c/p\u003e\n \u003cp\u003e1.31 [0.88-1.95]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eSurgical treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e0.38 [0.21-0.67]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eComplete cytoreduction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e0.42 [0.24-0.74]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.002*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e1.18 [0.63-2.21]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eNeoadjuvant chemotherapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e2.47 [1.77-3.43]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e1.52\u0026nbsp;[1.02-2.28]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.04*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eAdjuvant chemotherapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e1.60 [0.95-2.72]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eStage: (IV \u0026ndash; reference)\u003c/p\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003cp\u003eII\u003c/p\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.27 [0.13-0.57]\u003c/p\u003e\n \u003cp\u003e0.18 [0.11-0.30]\u003c/p\u003e\n \u003cp\u003e0.26 [0.19-0.37]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.001*\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.32 [0.14-0.72]\u003c/p\u003e\n \u003cp\u003e0.22 [0.13-0.38]\u003c/p\u003e\n \u003cp\u003e0.26 [0.17-0.40]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.01*\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.005*\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.005*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eStage T: (Т1 \u0026ndash; reference)\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.78 [0.28-2.14]\u003c/p\u003e\n \u003cp\u003e0.84 [0.34-2.09]\u003c/p\u003e\n \u003cp\u003e1.54 [0.62-3.80]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eStage N: (N0 \u0026ndash; reference)\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.25 [0.81-1.92]\u003c/p\u003e\n \u003cp\u003e2.06 [1.41-3.02]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eStage M: (М0 - reference)\u003c/p\u003e\n \u003cp\u003e1a\u003c/p\u003e\n \u003cp\u003e1b\u003c/p\u003e\n \u003cp\u003e1c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3.85 [2.74-5.43]\u003c/p\u003e\n \u003cp\u003e6.32 [3.42-11.69\u003c/p\u003e\n \u003cp\u003e4.57 [2.43-8.59]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eMetastasis localization:\u003c/p\u003e\n \u003cp\u003eLiver\u003c/p\u003e\n \u003cp\u003eCarcinomatosis\u003c/p\u003e\n \u003cp\u003eLungs\u003c/p\u003e\n \u003cp\u003eLymphatic nodes\u003c/p\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e5.10 [3.67-7.07]\u003c/p\u003e\n \u003cp\u003e2.56 [1.35-4.86]\u003c/p\u003e\n \u003cp\u003e1.70 [0.92-3.15]\u003c/p\u003e\n \u003cp\u003e1.94 [1.12-3.36]\u003c/p\u003e\n \u003cp\u003e2.87 [1.06-7.76]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003cp\u003e0.004*\u003c/p\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003cp\u003e0.02*\u003c/p\u003e\n \u003cp\u003e0.04*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eSynchronous cancer\u003c/p\u003e\n \u003cp\u003eMetachronous cancer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e1.11 [0.54-2.26]\u003c/p\u003e\n \u003cp\u003e0.99 [0.57-1.72]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eResidual tumor: (R0 \u0026ndash; reference)\u003c/p\u003e\n \u003cp\u003eR1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3.58 [2.17-5.90]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.83 [1.07-3.13]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.03*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eLVI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e1.10 [0.65-1.85]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*p-value\u0026lt; 0.05, the difference is significant\u003c/p\u003e\n\u003cp\u003eUnivariate analysis demonstrated that a \u003cem\u003eKRAS\u003c/em\u003e gene mutations, neoadjuvant chemotherapy, stage N2M1 (according to the TNM classification), liver, lymph nodes and other organs metastases, carcinomatosis and incomplete resection (R1) were associated with a higher risk of disease recurrence, while stages I-III compared with stage IV, surgical treatment and complete cytoreduction were associated with a lower risk of disease recurrence. Multivariate analysis demonstrated that only a \u003cem\u003eKRAS\u003c/em\u003e gene mutations, neoadjuvant chemotherapy, and incomplete resection (R1) were significant risk factors for disease recurrence or progression, while stages I-III compared with stage IV were associated with a lower risk of disease recurrence.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis cohort study demonstrates the results of the overall and disease-free survival analysis of colorectal cancer patients with RAS/\u003cem\u003eBRAF\u003c/em\u003e gene mutations. The Cox proportional hazards model allowed to identify predictors of death and relapse of colorectal cancer.\u003c/p\u003e\n\u003cp\u003eThe survival analysis revealed that patients with mutations in the \u003cem\u003eKRAS\u003c/em\u003e, \u003cem\u003eNRAS\u003c/em\u003e and \u003cem\u003eBRAF\u003c/em\u003e genes have lower rates of 1- and 3-year overall and disease-free survival. In our study, the 3-year overall survival rate in patients with BRAF gene mutations was higher than in patients with the KRAS and NRAS genes mutations. We believe that this may be due to the fact that these patients have microsatellite instability (MSI) in their tumors more frequently, which gives them an advantage in survival [9]. Patients with \u003cem\u003eNRAS\u003c/em\u003e gene mutations had significantly worse overall survival compared to the wild-type gene (p\u0026ndash;value=0.04), and patients with a \u003cem\u003eKRAS\u003c/em\u003e gene mutations had worse disease-free survival compared to the wild-type gene (p-value=0.02). Among the most common types of mutations in the \u003cem\u003eKRAS\u003c/em\u003e and \u003cem\u003eNRAS\u003c/em\u003e genes exons, survival rates were calculated for the \u003cem\u003eKRAS\u003c/em\u003e Gly12Asp mutation: the median OS was 73 months (95% CI 73.0 \u0026ndash; 73.0 months), the median DFS was 38 months (95% CI 17.0 \u0026ndash; 62.0 months). In the retrospective study by Hirose T. et al [15] median progression-free survival was 9.2 months (95%CI: 7.8-12.2) and median OS was 25.8 months (95%CI: 18.8-39.8).\u003c/p\u003e\n\u003cp\u003ePatients with wild-type genes, \u003cem\u003eKRAS\u003c/em\u003e, \u003cem\u003eNRAS\u003c/em\u003e and \u003cem\u003eBRAF\u003c/em\u003e gene mutations differed significantly in age (p-value\u0026lt; 0.001), tumor localization (p-value\u0026lt; 0.001), neoadjuvant chemotherapy (p-value = 0.009), surgical treatment (p-value = 0.04), the disease recurrence/progress rate (p-value = 0.01), and the stage of the disease (p-value = 0.04). According to the results of numerous studies all of these features are recognized as risk factors of death: the age over 75 years (HR 2.54, 95% CI 2.04-3.16) [16\u0026ndash;18] or younger (\u0026lt;=40 years, HR 1.87, 95% CI 1.09-3.47 [16], stage III-IV of the disease (HRadj, 3.04; 95% CI 1.79-5.18) [16,17,19], lack of surgical treatment (HR 1.36, 95% CI 1.007-1.83) [16] and perioperative chemotherapy (multivariate analysis: HR 1.65, 95% CI 1.17-2.33) [16,20], stage pT-pT4 (HR 2.59 95% CI 1.37-4.89) and pN2 (HR 2.12 95% CI 1.69-2.66) according to the TNM classification [21], the presence of distant (HRadj = 4.69, 95 CI 3.46-6.36) and regional (HRadj = 2.34, 95% CI 1.69-3.25) metastases [22], as well as left-sided localization of the primary tumors (in the transverse colon and splenic flexure (HRadj = 2.44, 95% CI 1.25-4.76), in the descending colon and sigmoid colon (HRadj = 2.01, 95% CI 1.26-3.20), in the rectosigmoid and rectum (HR = 2.00, 95% CI 1.24-3.24)) compared with the right-sided localization [22]. Thus, differences between the groups in these parameters could also affect the survival rates. In this regard, we conducted a regression analysis of the Cox proportional risks, which allowed us to assess the relationship between the presence or absence of mutations and the risk of death or disease recurrence/progress.\u003c/p\u003e\n\u003cp\u003eUnivariate and multivariate analysis did not confirm that mutations increased the risk of death. However, according to studies, the \u003cem\u003eKRAS\u003c/em\u003e gene mutations were associated with worse overall survival (HR = 1.27, 95% CI (1.03-1.55), p-value = 0,03) [8\u0026ndash;10,16,20,21,23], as well as the \u003cem\u003eBRAF\u003c/em\u003e V600E mutation (HR = 1.49, 95% CI (1.31-1.70), p-value \u0026lt; 0.001) and \u003cem\u003eNRAS\u003c/em\u003e gene mutations (HR=1.36.95% CI (1,15\u0026ndash;1,61)) [8\u0026ndash;10,24,25]. The \u003cem\u003eKRAS\u003c/em\u003e gene mutations were a risk factor for disease progression or recurrence in univariate and multivariate analysis (HR=1.47 95% CI (1.06-2.04), p-value=0.02 and HR=1.61 95% CI (1.11-2.31), p-value=0.01, respectively). Mutations in \u003cem\u003eKRAS\u003c/em\u003e and \u003cem\u003eBRAF\u003c/em\u003e were associated with shorter disease-free period and survival after relapse [10]. These mutations were also associated with lower disease-free survival rates (for patients with the \u003cem\u003eKRAS\u003c/em\u003e mutation: HR = 1.36, 95% CI (1.15-1.61); with the \u003cem\u003eBRAF\u003c/em\u003e mutation: HR = 1.33, 95% CI (1,00-1,78)) [7\u0026ndash;9,21,25].\u003c/p\u003e\n\u003cp\u003eThe study showed that the independent risk factors of death were only stage IV of the disease (compared with stage II (p-value=0.01)) and incomplete cytoreduction (p-value\u0026lt;0.005), while disease recurrence predictors were \u003cem\u003eKRAS\u003c/em\u003e gene mutations (p\u0026ndash;value=0.01), neoadjuvant therapy (p-value=0.04), stage IV of the disease (compared with stage I (p-value=0.01), stage II (p-value\u0026lt;0.005), stage III (p-value\u0026lt;0.005), \u0026nbsp;) and incomplete resection (R1) (p-value=0.03). Regarding neoadjuvant chemotherapy it was demonstrated to increase the risk of death (HR= 2.81 95% CI (1.53-5.17), p-value=0.001) and relapse of the disease (HR=2.47 95% CI (1.77-3.43), p-value\u0026lt;0.001, HR adj. = 1.52 95% CI (1.02-2.28), p-value=0.04). In subgroup analysis for patients with stage IV colorectal cancer the neoadjuvant chemotherapy was also a death (HR = 2.15 95% CI (1.15-4.00), p-value=0.02) and recurrence predictor (HR=2.19 95% CI (1.54-3.13), p-value\u0026lt;0.001). Jiang Yu-Juan [26] also showed that the neoadjuvant chemotherapy was a risk factor of death for stage IV colorectal cancer patients however the results were statistically insignificant (HR =1.10 95% CI (0.70 -1.72), p-value=0.685). The neoadjuvant chemotherapy improved 5-year OS (p-value = 0.048) and DFS (p-value= 0.040) only for patients with more than three liver metastases, while patients with fewer than three liver metastases showed no survival benefit. [26]. Several studies showed no impact of neoadjuvant chemotherapy on survival outcomes for patients with advanced CRC [27,28]. However the meta-analysis demonstrated significant improvement in OS and DFS for patients with advanced CRC and neoadjuvant chemotherapy [29] In our practice neoadjuvant chemotherapy is usually prescribed for patients with advanced stages and for primary non-surgical patients to reduce the stage. As a result, variable clinical characteristics may result in selection bias and lead to incorrect results.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThus, the overall and disease-free survival of patients with colorectal cancer largely depends on time of diagnosis and radical and complete surgical interventions.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eLimitations and advantages\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis study had some limitations. Despite the fact that the Ryzhikh National Medical Research Center of Coloproctology is a large specialized federal center in Russia for the treatment of colorectal cancer, a single-center study design could lead to the selection bias. Due to the short follow-up period and the small number of target events for assessing long-term outcomes, it was not possible to fully calculate the median and confidence intervals for overall and disease-free survival for most subgroups. For this reason it was not possible to calculate survival rates for patients at different stages separately: no deaths were recorded during follow-up at stage I, the number of deaths at stage II was 2, at stage III \u0026ndash; 8, at stage IV \u0026ndash; 36.\u003c/p\u003e\n\u003cp\u003eWhen comparing the groups with wild-type and RAS/\u003cem\u003eBRAF\u003c/em\u003e gene mutations significant differences were obtained in several demographic and clinical features, which could also affect the survival rates in the groups.\u003c/p\u003e\n\u003cp\u003eThus, the results of this study demonstrate the need for further research in this area.\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe independent risk factors of death from CRC were stage IV compared with stage II and incomplete cytoreduction, while disease recurrence independent predictors were KRAS gene mutations, neoadjuvant therapy, stage IV compared with stage I, II and III, and incomplete resection (R1). Thus, early colorectal cancer diagnostic and radical and complete tumor resection allow to improve overall and disease-free survival for all patients.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eThe authors declare that no funds, grants, or other support were received during the preparation of this manuscript. The authors have no relevant financial or non-financial interests to disclose. The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request. This study was performed in line with the principles of the Declaration of Helsinki. The study was approved by the Local Ethical Committee of the Ryzhikh National Medical Research Center of Coloproctology. Informed consent was obtained from all individual participants included in the study. All authors work in civil hospitals or in educational organizations and none of them are currently involved in any other kind of activity (including military, political or economical) and never were.\u003c/p\u003e\n\u003cp\u003e\u003cb\u003eAuthors contribution\u003c/b\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: Tsukanov A.S., Khomyakov E.A.\u003c/p\u003e\n\u003cp\u003eData curation: Khomyakov E.A.\u003c/p\u003e\n\u003cp\u003eFormal analysis: Kazachenko E.A.\u003c/p\u003e\n\u003cp\u003eInvestigation: Shubin V.P.,\u003c/p\u003e\n\u003cp\u003eMethodology: Otstanov S.S., Khomyakov E.A.,\u003c/p\u003e\n\u003cp\u003eProject administration: Otstanov S.S., Tsukanov A.S.\u003c/p\u003e\n\u003cp\u003eResources: Shubin V.P.\u003c/p\u003e\n\u003cp\u003eSoftware: Kazachenko E.A.\u003c/p\u003e\n\u003cp\u003eSupervision: Tsukanov A.S., Rybakov E.G.\u003c/p\u003e\n\u003cp\u003eValidation: Khomyakov E.A.,\u003c/p\u003e\n\u003cp\u003eVisualization: Kazachenko E.A.\u003c/p\u003e\n\u003cp\u003eWriting \u0026ndash; original draft: Khomyakov E.A., Tsukanov A.S.\u003c/p\u003e\n\u003cp\u003eWriting \u0026ndash; review \u0026amp; editing: Rybakov E.G., Shelygin Yu.A.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBray F, Laversanne M, Sung H, et al. 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Br J Surg. 2024;111. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/bjs/znae021\u003c/span\u003e\u003cspan address=\"10.1093/bjs/znae021\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Colorectal cancer, overall survival, risk factors, KRAS, BRAF, NRAS","lastPublishedDoi":"10.21203/rs.3.rs-7657018/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7657018/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e\u003cp\u003eCompare long-term outcomes in patients with colorectal cancer with \u003cem\u003eKRAS\u003c/em\u003e, \u003cem\u003eNRAS\u003c/em\u003e, and \u003cem\u003eBRAF\u003c/em\u003e gene mutations and wild-type genes.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThe study had cohort retrospective design. The overall survival (OS) for 611 patients and disease-free survival (DFS) for 490 patients were evaluated using the Kaplan-Meier estimator as primary endpoint. Relative OS and DFS of patients with gene mutations and wild-type genes and risk factor analysis were performed as secondary endpoints.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003ePatients with \u003cem\u003eNRAS\u003c/em\u003e gene mutations had worse OS (p-value\u0026thinsp;=\u0026thinsp;0.04) and patients with \u003cem\u003eKRAS\u003c/em\u003e gene mutation had worse DFS (p-value\u0026thinsp;=\u0026thinsp;0.02) both compared to wild-type genes patients. 3-year OS rate was 86%, 74% 67% and 78% and 3-year DFS rate was 50%, 34% 50% and 46% for patients with the wild-type genes, \u003cem\u003eKRAS\u003c/em\u003e, \u003cem\u003eNRAS\u003c/em\u003e and \u003cem\u003eBRAF\u003c/em\u003e gene mutations, respectively. Complete cytoreduction (HR 0.20, p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.005) and stage II (HR 0.07, p-value\u0026thinsp;=\u0026thinsp;0.01) of the disease were associated with a lower risk of death. A \u003cem\u003eKRAS\u003c/em\u003e gene mutations (HR 1.61, p-value\u0026thinsp;=\u0026thinsp;0.01), neoadjuvant chemotherapy (HR 1.52, p-value\u0026thinsp;=\u0026thinsp;0.04), and incomplete resection (HR 1.83, p-value\u0026thinsp;=\u0026thinsp;0.03) were associated with a high risk of recurrence, while stages I-III compared with stage IV (HR 0.32, p-value\u0026thinsp;=\u0026thinsp;0.01; HR 0.22, p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.005; HR 0.26, p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.005) were associated with a lower risk of recurrence.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eRAS/\u003cem\u003eBRAF\u003c/em\u003e mutations associated with worse CRC survival, however, advanced stage, incomplete cytoreduction and resection (R1) are also significant risk factors for death and CRC recurrence. Thus, early colorectal cancer diagnostic and radical and complete tumor resection allow to improve overall and disease-free survival for all patients.\u003c/p\u003e","manuscriptTitle":"Risk factors and survival of colorectal cancer patients with RAS/BRAF gene mutations","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-08 07:05:49","doi":"10.21203/rs.3.rs-7657018/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"743627ab-a35a-4846-bad8-5e32a98242b9","owner":[],"postedDate":"October 8th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-12-07T22:08:30+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-08 07:05:49","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7657018","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7657018","identity":"rs-7657018","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}