Abdominal aortic calcification predicts failure to complete adjuvant chemotherapy for stage III colorectal cancer: A retrospective cohort study

Abdominal aortic calcification predicts failure to complete adjuvant chemotherapy for stage III colorectal cancer: A retrospective cohort study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Abdominal aortic calcification predicts failure to complete adjuvant chemotherapy for stage III colorectal cancer: A retrospective cohort study Kouki Imaoka, Manabu Shimomura, Hiroshi Okuda, Takuya Yano, Shintaro Akabane, and 11 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4356279/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Completion of postoperative adjuvant chemotherapy (AC) contributes to improved prognosis of patients with pathological stage (pStage) III colorectal cancer (CRC). Therefore, identifying patients with AC intolerance is important. Although abdominal aortic calcification (AAC) indicates frailty, its clinical impact on AC completion remains unclear. This study aimed to clarify the association between AAC and AC incompletion. Methods Patients who underwent AC for pStage III CRC between 2010 and 2021 (n = 161) were divided into two groups based on an AAC cutoff of 992 mm 3 , determined using the receiver operating characteristic curves for AC completion. We investigated the perioperative clinicopathological factors and compared the frequency and severity of AC adverse events between the groups. Results The high AAC group had a significantly higher proportion of patients with older age (≥ 70 years), male sex, hypertension, and AC incompletion than the low AAC group. The regimens were not significantly different. No significant difference in the frequency or severity of adverse events was observed in either group. In the multivariate analysis, high AAC and older age were significantly associated with AC incompletion. Furthermore, k-means cluster analysis based on both age and AAC volume also demonstrated an increased risk of AC incompletion in patients with stage III CRC as both age and AAC volume increased. High AAC was associated with diminished improvement in nutritional status or inflammatory markers after the administration of AC. Conclusions High AAC is a potential risk marker for predicting AC incompletion in patients with stage III CRC before introducing AC. calcification colorectal cancer adjuvant chemotherapy incompletion Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Colorectal cancer (CRC) is the third most commonly diagnosed cancer and the second leading cause of cancer-related deaths globally [ 1 ]. Adjuvant chemotherapy (AC) plays a crucial role in mitigating postoperative recurrence and improving patient prognosis [ 2 , 3 ]. Particularly, AC completion has been linked to reduced rates of postoperative recurrence, establishing it as the standard treatment protocol for stage III CRC [ 3 ]. However, the adverse effects (AEs) of chemotherapy can be more pronounced in patients with comorbidities or deteriorating general health [ 4 ]. Consequently, factors such as advanced age and pre-existing health conditions are frequently cited as reasons for non-initiation of AC [ 5 ]. Considering these observations, it is critical to identify the risk factors that impede the completion of AC before its initiation. This process can facilitate the adjustment or moderation of chemotherapy intensity or necessitate more stringent monitoring of patients undergoing AC. Abdominal aortic calcification (AAC) is known to be correlated with increased mortality related to cardiovascular diseases [ 6 ]. AAC is also associated with malnutrition, chronic inflammation, and atherosclerosis syndrome [ 7 , 8 ]. Recent studies have indicated that the severity of vascular calcification exhibits a linear positive relationship with frailty in older adults [ 9 ], with older women at risk for rapid weight loss over a 5-year period [ 10 ]. While AAC can simply be a marker of advanced age and frailty, there are several putative mechanisms by which AAC can potentially influence the risk of AC toxicity. Firstly, AAC has been reported to be associated with postoperative renal dysfunction [ 11 ]. Therefore, AAC could affect the pharmacokinetics of renally metabolized drugs, such as fluoropyrimidine and oxaliplatin. In addition, advanced age is correlated with a decline in bone marrow reserve and an increased risk of complications related to chemotherapy-induced myelosuppression [ 12 ]. Given such associations, we hypothesized that AAC could be an indicative marker of patient-specific vulnerability, thus acting as a reliable predictor of AC incompletion due to AC toxicity in stage III CRC patients. This study explored the efficacy of AAC as an indicator of AC incompletion. Methods Patients Patients with CRC who underwent radical surgery and were diagnosed with pathological stage (pStage) III CRC in our institute between 2010 and 2021 were included. Clinical data at the time of colorectal surgery, including age, sex, American Society of Anesthesiologists Physical Status Classification System (ASA-PS) score [ 13 ], body mass index, hypertension (HT), diabetes mellitus (DM), hyperlipidemia (HL), blood examination data, postoperative complications, and pathological findings, were collected retrospectively from the medical records of the patients. In addition, the availability of AC introduction, details of the regimens, continuation or discontinuation, and severity of AEs were investigated. The decision of AC discontinuation was based on a comprehensive assessment by the physician, considering the degree of AEs, the patient's overall condition and wishes; the patient did not complete the intended course as scheduled at the time of induction; even after the specified dose was reduced by two levels or to a minimal dose level, the physician judged that the protocol treatment was difficult to continue, and the patient requested discontinuation of protocol treatment. This analysis excluded patients who did not undergo AC, patients who relapsed during the AC period, and patients who were not followed up during the AC period. For the postoperative adjuvant therapy, oxaliplatin combination therapy (capecitabine plus oxaliplatin or fluorouracil plus oxaliplatin) or fluoropyrimidine monotherapy was selected according to the guidelines of the Japanese Society for Cancer of the Colon and Rectum [ 14 ], considering the patient's postoperative condition and risk of recurrence. In this cohort study, no patients received capecitabine plus oxaliplatin for a planned 3-month period. Clinical data after AC introduction, including blood examination results or the degree of AEs, were collected retrospectively from the medical records of the patients. The patients were followed up using contrast-enhanced computed tomography (CT) and colonoscopy, combined with an evaluation of serum CEA and CA19-9 levels at 3-month intervals for 5 years and at 6-month intervals for 5 years thereafter. Evaluation of abdominal aortic calcification CT angiography was conducted using a 320-detector row CT scanner (Aquilion ONE ViSION, Toshiba Medical Systems, Japan) with a standardized examination protocol. The AAC score was determined utilizing the AZE VirtualPlace Lexus64 Anatomia software (AZE Inc., Tokyo, Japan). Employing the Agatston method [ 15 ], the software automatically computed the volume of AAC by identifying calcifications within the abdominal aorta, spanning from the origin of the renal artery to the iliac bifurcation. The AAC cutoff (992 mm 3 ) was determined using the receiver operating characteristic curves of AC completion. Statistical analysis Categorical variables are expressed as numbers and percentages. Continuous variables are presented as medians with interquartile ranges. Data from the two groups were compared using the chi-squared test or Fisher’s exact test for dichotomous outcomes. Paired Student's t tests and the nonparametric Mann–Whitney U test were used for continuous outcomes with a skewed distribution. Univariate analyses were performed to assess the association between AC discontinuation and the following variables: age, sex, ASA-PS, AAC, HT, HL, DM, modified Glasgow prognostic score (mGPS) [ 16 ], geriatric nutritional risk index (GNRI) [ 17 ], controlling nutritional status (CONUT) [ 18 ], neutrophil-to-lymphocyte ratio (NLR) [ 19 ], tumor location, postoperative complications, and pStage. All variables were included in a multivariate logistic regression model using a stepwise (forward or backward) procedure. Independent variables were entered into the model at the 0.10 significance level and removed at the 0.20 level; these were used to select the covariates. Overall survival (OS) and recurrence-free survival (RFS) were plotted using the Kaplan–Meier analysis and compared using log-rank statistics. All statistical analyses were performed using JMP statistical software (JMP® 17; SAS Institute Inc., Cary, NC, USA). Statistical significance was set at P < 0.05. Results patient characteristics A consort diagram of the study is shown in Fig. 1 . The baseline characteristics of the high and low AAC groups are shown in Table 1 . Compared with the low AAC group, the high AAC group had a significantly higher proportion of patients with older age, male sex, higher ASA-PS, HT, and DM. No significant differences were found in malnutrition or systemic inflammation status, including mGPS, CONUT, GNRI, and NLR, between the two groups. In addition, there were no significant differences in tumor factors, including pStage and histopathological differentiation. Furthermore, there was no difference in the choice of regimen between the two groups. The rate of AC completion was lower in the high AAC group than the low AAC group (72.9% vs. 90.3%; P < 0.01). Table 1. Patient characteristics High AAC group (N=48) Low AAC group (N=113) P value Age (years) 71 (65-74) 61 (53-69) < 0.01 Gender (Male/Female) 38/10 52/61 < 0.01 ASA-PS < 0.01 1 3 (6.3%) 33 (29.2%) 2 44 (91.7%) 79 (69.9%) 3 1 (2.1%) 1 (0.9%) HT (+) 25 (52.1%) 26 (23.0%) < 0.01 DM (+) 19 (39.6%) 28 (24.8%) 0.059 HL (+) 24 (50.0%) 54 (47.8%) 0.797 CONUT 0.799 normal (0-1) 31 (64.6%) 71 (62.8%) mild (2-4) 17 (35.4%) 41 (36.3%) moderate (5-8) 0 (0.0%) 1 (0.9%) high (9-) 0 (0.0%) 0 (0.0%) GNRI 0.408 normal (> 98) 42 (87.5%) 93 (82.3%) mild (92-98) 2 (4.2%) 12 (10.6%) moderate (< 92) 4 (8.3%) 8 (7.1%) mGPS 0.696 0 43 (89.6%) 99 (87.6%) 1 4 (8.3%) 13 (11.5%) 2 1 (2.1%) 1 (0.9%) NLR 2.51 (1.86-3.47) 2.23 (1.64-3.03) 0.145 Tumor location (Colon/rectum) 28/20 58/55 0.415 pStage 0.582 Ⅲa 13 (27.1%) 38 (33.6%) Ⅲb 31 (64.6%) 63 (55.8%) Ⅲc 4 (8.3%) 12 (10.6%) Por/muc (+) 3 (6.3%) 12 (10.6%) 0.383 CEA 3.9 (2.4-9.1) 2.4 (1.7-6.0) 0.047 Postoperative complication (+) 12 (25.0%) 15 (13.3%) 0.069 regimen 0.820 fluoropyrimidine monotherapy 34 (70.8%) 78 (69.0%) oxaliplatin combination therapy 14 (29.2%) 35 (31.0%) AC completion (+) 35 (72.9%) 102 (90.3%) <0.01 AAC, abdominal aortic calcification; ASA-PS, American Society of Anesthesiologists Physical Status Classification System; BMI, body mass index; HT, hypertension; HL, hyperlipidemia; DM, diabetes mellitus; NLR, neutrophil-to-lymphocyte ratio; CONUT, controlling nutritional status; mGPS; modified Glasgow prognostic score; GNRI, Geriatric Nutritional Risk Index; pStage, pathological stage; Por/muc, poorly/mucinous; AC; adjuvant chemotherapy; CEA, carcinoembryonic antigen Table 2. Risk factors for adjuvant chemotherapy incompletion Factors Univariate Multivariate OR 95% CI p-value OR 95% CI p-value Age (≥ 70 years) 4.68 1.88-11.6 <0.01 4.85 1.68-14.0 <0.01 Gender (Male) 1.12 0.47-2.71 0.795 AAC (≥ 992mm 3 ) 3.44 1.41-8.39 <0.01 3.00 1.05-8.53 0.040 ASA-PS (≥2) 0.84 0.31-2.31 0.737 0.43 0.13-1.42 0.168 CONUT (≥5) 1.44 0.71-2.94 0.312 mGPS (≥1) 1.28 0.53-3.10 0.581 2.71 0.78-9.45 0.119 GNRI (<92) 0.81 0.09-6.87 0.845 NLR (≥4) 1.45 0.49-4.32 0.501 Tumor location (colon) 1.28 0.53-3.09 0.580 Histological type (Por/muc) 1.49 0.39-5.72 0.563 3.24 0.70-15.1 0.133 pStage (IIIb/IIIc) 1.47 0.55-3.95 0.448 Postoperative complication (+) 1.84 0.65-5.18 0.247 Fluoropyrimidine monotherapy 0.69 0.28-1.70 0.417 OR, odds ratio; AAC, abdominal aortic calcification; ASA-PS, American Society of Anesthesiologists Physical Status Classification System; CONUT, controlling nutritional status; mGPS, modified Glasgow prognostic score; GNRI, Geriatric Nutritional Risk Index; NLR, neutrophil-to-lymphocyte ratio; pStage, pathological stage; AC, adjuvant chemotherapy. Table 3. Severity and details of adverse events between the high and low AAC groups High AAC group (N=48) Low AAC group (N=113) p-value The severity of adverse event 0.481 Grade 0 9 (18.8%) 12 (10.6%) Grade 1 8 (16.7%) 23 (20.4%) Grade 2 19 (39.6%) 53 (46.9%) Grade 3 12 (25.0%) 25 (22.1%) Grade 4-5 0 (0.0%) 0 (0.0%) Hematological toxicity (≥ Grade2) 12 (25.0%) 30 (26.6%) 0.838 Symptoms of digestive system (≥ Grade2) 10 (20.8%) 21 (18.6%) 0.741 Hand-foot syndrome (≥ Grade2) 12 (25.0%) 32 (28.3%) 0.666 Others (≥ Grade2) 9 (18.8%) 19 (16.8%) 0.767 AAC, abdominal aortic calcification; AC, adjuvant chemotherapy Table 4. Risk ratios for incompletion of adjuvant chemotherapy according to the cluster analysis based on the age and AAC volume N=161 age (years) AAC volume (mm 3 ) OR 95% CI p-value Cluster 1 43 (26.7%) 50 (45-55) 0 (0-30) 1 (reference) Cluster 2 92 (57.1%) 68 (63-72) 208 (14-954) 4.32 0.95-19.7 0.059 Cluster 3 26 (16.1%) 72 (65-76) 3147 (2727-4146) 6.15 1.14-33.2 0.035 OR, odds ratio; AAC, abdominal aortic calcification; CI, confidence interval Identification of risk factors for AC incompletion Univariate analysis revealed that older age (≥ 70 years) and high AAC (≥ 992 mm3) were risk factors for AC incompletion. The independent risk factors identified in the multivariate analysis were high AAC (OR, 3.00; 95% CI, 1.05–8.53; P = 0.040) and older age (OR, 4.85; 95% CI, 1.68–14.0; P < 0.01) (Table 2 ). Risk ratios for AC incompletion according to the cluster analysis based on the age and AAC volume Subsequently, to elucidate the effects of age and AAC volume on AC incompletion, a k-means cluster analysis was performed. This analysis utilized both age and AAC volume for stratification into three distinct clusters (Fig. 2 ): cluster 1 consisting of young age (50 [45–55] years) and low AAC (0 [0–30] mm3) (N = 43), cluster 2 consisting of old age (68 [63–72] years) and low AAC (208 [14–954] mm3) (N = 92), and cluster 3 consisting of old age (72 [65–76] years) and high AAC (3147 [2727–4146] mm3) (N = 26). The odds ratio for AC incompletion increased with age and AAC volume (Table 4 ). The severity and details of AEs between the high and low AAC groups Table 3 shows the association between the severity or details of the AEs and AAC. There were no differences in the severity or details of the AEs between the high and low AAC groups. Nevertheless, the high AAC group significantly failed to complete AC because of AEs. These results suggest that patients with high AAC are more prone to treatment intolerance of AC, independent of AEs. Perioperative changes in nutrition status, inflammatory markers, and renal function between the high and low AAC groups We assessed the correlation between AAC and alterations in nutritional status, inflammatory markers, and renal function at three key time points: at the time of surgery, at the initiation of AC, and completion or discontinuation of AC. Upon initiation of AC, albumin levels declined compared to preoperative levels in both AAC groups. In the low AAC group, albumin levels at the end of AC showed improvement relative to the levels at initiation, eventually returning to preoperative levels (Fig. 3 a). Conversely, in the high AAC group, albumin levels at the end of AC remained stagnant compared to the levels at initiation and failed to recover to preoperative levels (Fig. 3 a). Similarly, NLR levels improved at the initiation of AC compared with preoperative levels in both AAC groups. Subsequent to AC, NLR levels decreased in the low AAC group compared with the initiation levels (Fig. 3 b). However, in the high AAC group, the NLR levels remained unchanged compared to the initiation level. In contrast, the estimated glomerular filtration rate (eGFR) exhibited no significant changes at any assessed time point, including at surgery, initiation of AC, and completion or discontinuation of AC, in both AAC groups (Fig. 3 c). These findings suggest that high AAC was associated with diminished improvement in nutritional status or inflammatory markers following the introduction of AC. Prognosis by completion of AC The 5-year OS and RFS were 93.6% and 78.4%, respectively, and the median follow-up period was 60.7 months (range, 6–108 months). The 5-year OS was 93.2% for patients who had completed AC and 95.8% for patients who did not complete AC, with no significant difference (P = 0.973) (Fig. 4 a). The 5-year RFS was 81.5% for patients who had completed AC and 60.4% for patients who did not complete AC, with a significant difference (P < 0.05) (Fig. 4 b). Discussion This retrospective study aimed to identify potential predictors of AC incompletion in patients with stage III CRC, with a specific focus on the role of AAC as an indicator of AC incompletion. A notable finding was that high AAC volume was a significant predictor of AC incompletion in patients with stage III CRC. This finding underscores the comprehensive reflection of systemic conditions such as advanced age and comorbidities by AAC. Importantly, AAC was robustly associated with the critical outcomes of chemotherapy discontinuation in patients with CRC. This association suggests that AAC could effectively bridge the clinical gap by identifying risk factors that may impede AC completion prior to its initiation. Additionally, an increased risk of AC incompletion in patients with stage III CRC as both age and AAC volume increased. Finally, our results suggested that AC incompletion was associated with poor prognosis in patients with stage III CRC, as previously reported [ 2 , 3 ]. To the best of our knowledge, this is the first study to establish a direct link between AAC and AC incompletion in patients with stage III CRC who commenced AC. These findings present AAC as a straightforward and immediately applicable metric in clinical settings. The identification of clinically effective biomarkers for exploring the sustainability of AC in the older population presents a significant challenge to clinical practice. One study reported that there was no age requirement for postoperative AC, and aggregated analyses of randomized-controlled trials conducted in both the United States and Europe have demonstrated comparable effectiveness in terms of recurrence prevention and survival extension between patients aged ≥ 70 years and those aged < 60 years [ 20 ]. Our previous study also indicated that completion of AC may contribute to improved long-term prognosis, even in patients aged ≥ 80 years with stage III CRC [ 21 ]. However, older age is considered an important factor in the introduction and continuation of AC by many clinicians and patients [ 22 , 23 ]. Increased age may also be associated with increased frailty and decreased tolerance to chemotherapy [ 24 ]. Although the decision on AC introduction or discontinuation should be made carefully, considering not only age, but also major organ functions, general health, and condition, no clinically useful biomarkers have yet been identified. Recently, geriatric assessment (GA) has been shown a useful method for measuring physical function, cognitive function, nutritional status, social factors, and family environment and has been reported to predict the completion of chemotherapy [ 25 , 26 ]. Although GA has proven useful for characterizing health and functional impairments potentially associated with oncological outcomes [ 27 ], it requires considerable time and human resources [ 28 ]. Therefore, it is necessary to establish a simpler biomarker for predicting AC completion than that for predicting GA. AAC is a well-known risk marker of cardiovascular diseases and is associated with hyperphosphatemia, diabetes, chronic inflammation, and chronic kidney disease [ 29 ]. A recent study indicated that AAC severity independently correlated with an increased risk of pre-frailty or frailty in a dose-responsive relationship [ 9 ]. Furthermore, AAC volume can be calculated and quantified accurately, automatically, and rapidly using preoperative CT-based examination [ 30 ]. Our findings indicate that AAC volume is a specific predictor of AC completion as well as chronological age. This distinction is critical, as even among older patients, there is considerable variation in the overall health status and vulnerability, which are influenced by factors such as the extent of comorbidities and tumor progression. However, these variations cannot be accurately gauged using age alone. Consequently, measurement of AAC volume is anticipated to offer a more objective reflection of the systemic condition and tolerance to AC in patients. There may be several complex underlying mechanisms and reasons why patients cannot complete AC. Several reports have described the predictive role of inflammatory markers and nutritional factors in severe complications with chemotherapy [ 31 – 33 ]. In the field of head and neck oncology, nutritional factors such as the prognostic nutritional index, mGPS, and the C-reactive protein to albumin ratio (CAR) are useful markers for predicting severe AEs [ 31 , 33 ]. In CRC, CAR is also a useful tool for AEs (≥ grade 3) of the AC [ 32 ]. Contrary to expectations, high AAC was not associated with the severity of AEs, but the risk of AC incompletion in stage III CRC patients in this study. High AAC can be related to the patients’ adverse condition that cannot be assessed by the Common Terminology Criteria for Adverse Events (CTCAE) after AC introduction. Therefore, we focused on the association of AAC with alterations in nutritional status and inflammatory markers following the introduction of AC. Our findings suggest that higher levels of AAC are linked to a reduced improvement in nutritional status or inflammatory markers after the administration of AC, which can potentially contribute to AC incompletion independent of the AE severity. Thus, AAC could serve as an indicative marker of patient-specific susceptibility to the tolerance of AC. This study had some limitations that should be considered when interpreting our findings. Specifically, the retrospective and non-randomized study design must be mentioned. The small sample size of patients at a single center may also weaken the conclusion. Future prospective studies involving a larger number of patients with high AAC are required to analyze the effects of AC on clinical outcomes. In conclusion, high AAC volume may help us to more closely follow-up patients who have a potential risk of AC incompletion before AC introduction. Declarations Disclosures Funding: The authors declare that they have no competing interests. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Conflict of interest: The authors declare that they have no competing interest. Ethical statements There is no need for consent to participate to be obtained due to retrospective study. Administrative permissions were not required to access and use the medical records described in this study. This study was authorized in advance by the institutional review board of the Hiroshima University Hospital. The registration number of the study: E744-3 Animal studies: N/A Author contribution KI, MS, and TY conceived and designed the study. KI, KO, KM, TM, TB, SI, SS, and AW acquired the data and calculated AAC scores. KI, TY, SM, SA, MO, YI and MH analyzed and interpreted the data, and drafted the manuscript. KI, YT, MS, SA, and HO critically revised the article. KI, YT, and HO approved the final version of the manuscript to be published. A cknowledgments We would like to thank Editage for the English language review. References Morgan E, Arnold M, Gini A, et al. Global burden of colorectal cancer in 2020 and 2040: incidence and mortality estimates from GLOBOCAN. Gut. 2023 Feb;72(2):338-344. Knapen DG, Cherny NI, Zygoura P, et al. Lessons learnt from scoring adjuvant colon cancer trials and meta-analyses using the ESMO-magnitude of clinical benefit scale V.1.1. ESMO Open. 2020;5(5):e000681. Yoshino T, Arnold D, Taniguchi H, et al. Pan-Asian adapted ESMO consensus guidelines for the management of patients with metastatic colorectal cancer: a JSMO-ESMO initiative endorsed by CSCO, KACO, MOS. SSO and TOS Ann Oncol. 2018;29(1):44–70. Shahrokni, A., Kim, S. J., Bosl, G. J. & Korc-Grodzicki, B. How we care for an older patient with cancer. J. Oncol. Pract. 13(2), 95–102. Abdel-Rahman O, Tang PA, Koski S. Hospitalizations among early-stage colon cancer patients receiving adjuvant chemotherapy: a real-world study. Int J Colorectal Dis. 2021;36(9):1905–13: 1905–1913. Criqui MH, Denenberg JO, McClelland RL, et al. Abdominal aortic calcium, coronary artery calcium, and cardiovascular morbidity and mortality in the Multi-Ethnic Study of Atherosclerosis. Arterioscler Thromb Vasc Biol. 2014 Jul;34(7):1574-9. Epub 2014 May 8. Erratum in: Arterioscler Thromb Vasc Biol. 2015 Jan;35(1):e1. Zhang K, Gao J, Chen J, et al. MICS, an easily ignored contributor to arterial calcification in CKD patients. Am J Physiol Renal Physiol. 2016 Oct 1;311(4):F663-F670. Stenvinkel P, Heimbürger O, Lindholm B, et al. Are there two types of malnutrition in chronic renal failure? Evidence for relationships between malnutrition, inflammation and atherosclerosis (MIA syndrome). Nephrol Dial Transplant. 2000 Jul;15(7):953-60. Lee SY, Chao CT, Huang JW, et al. Vascular Calcification as an Underrecognized Risk Factor for Frailty in 1783 Community-Dwelling Elderly Individuals. J Am Heart Assoc. 2020 Sep 15;9(18):e017308. Smith C, Sim M, Dalla Via J, et al. Extent of Abdominal Aortic Calcification Is Associated With Incident Rapid Weight Loss Over 5 Years: The Perth Longitudinal Study of Ageing Women. Arterioscler Thromb Vasc Biol. 2024;44(2):e54-e64. Ide, R., Ohira, M., Imaoka, Y., et al. (2023). Impact of Abdominal Aortic Calcification on Chronic Kidney Disease After Liver Transplantation: A Retrospective Study. Transplantation proceedings, 55(4), 956–960. Dees EC, O'Reilly S, Goodman SN, et al. A prospective pharmacologic evaluation of age-related toxicity of adjuvant chemotherapy in women with breast cancer. Cancer Invest. 2000;18(6):521-9. Hackett NJ, De Oliveira GS, Jain UK, et al. ASA class is a reliable independent predictor of medical complications and mortality following surgery. Int J Surg. 2015;18:184–190. Hashiguchi Y, Muro K, Saito Y et al (2020) Japanese Society for Cancer of the Colon and Rectum (JSCCR) guidelines 2019 for the treatment of colorectal cancer. Int J Clin Oncol 25:1–42. Agatston AS, Janowitz WR, Hildner FJ, , et al. Quantification of coronary artery calcium using ultrafast computed tomography. J Am Coll Cardiol. 1990 Mar 15;15(4):827–32. Hirashima K, Watanabe M, Shigaki H, et al (2014) Prognostic significance of the modified Glasgow prognostic score in elderly patients with gastric cancer. J Gastroenterol. 49:1040–1046. Li L, Wang H, Yang J, et al. Geriatric nutritional risk index predicts prognosis after hepatectomy in elderly patients with hepatitis B virus-related hepatocellular carcinoma. Sci Rep 2018;8:12561. Elghiaty A, Kim J, Jang WS, et al. Preoperative controlling nutritional status (CONUT) score as a novel immune-nutritional predictor of survival in non-metastatic clear cell renal cell carcinoma of ≤7 cm on preoperative imaging. J Cancer Res Clin Oncol. (2019) 145:957–65. Guthrie GJ Charles KA Roxburgh CS et al. The systemic inflammation-based neutrophil-lymphocyte ratio: experience in patients with cancer. Crit Rev Oncol Hematol. 2013;88(1):218–230. Sargent DJ, Goldberg RM, Jacobson SD, et al (2001) A pooled analysis of adjuvant chemotherapy for resected colon cancer in elderly patients. N Engl J Med 345(15):1091–1097. Mochizuki T, Shimomura M, Nakahara M et al (2023) Survival outcomes of patients with stage III colorectal cancer aged ≥ 80 years who underwent curative resection: the HiSCO-04 prospective cohort study. Int J Clin Oncol. doi: 10.1007/s10147-023-02440-9. Epub ahead of print. Kim HH, Ihn MH, Lee YH, et al. Effect of age on laparoscopic surgery and postoperative chemotherapy in elderly patients with colorectal cancer. Ann Coloproctol. 2020;36(4):229–42: 229–242. Badic B, Oguer M, Cariou M, et al. Prognostic factors for stage III colon cancer in patients 80 years of age and older. Int J Colorectal Dis. 2021;36 Dobie SA, Baldwin LM, Dominitz JA, et al. Completion of therapy by Medicare patients with stage III colon cancer. J Natl Cancer Inst. 2006 May 3;98(9):610-9. Aaldriks AA, Maartense E, Nortier HJ, et al: Prognostic factors for the feasibility of chemotherapy and the Geriatric Prognostic Index (GPI) as risk profile for mortality before chemotherapy in the elderly. Acta Oncol 55:15-23, 2016 Von Gruenigen VE, Huang HQ, Beumer JH, et al. Chemotherapy completion in elderly women with ovarian, primary peritoneal or fallopian tube cancer - an NRG oncology/Gynecologic Oncology Group study. Gynecol Oncol 144:459-467, 2017 Wildiers H, Heeren P, Puts M, et al. International Society of Geriatric Oncology consensus on geriatric assessment in older patients with cancer. J Clin Oncol. 2014;32:2595–2603. Caillet P, Laurent M, Bastuji-Garin S, et al. Optimal management of elderly cancer patients: Usefulness of the Comprehensive Geriatric Assessment. Clin Interv Aging. 2014;9:1645–1660. Kiu Weber CI, Duchateau‐Nguyen G, Solier C, et al. Cardiovascular risk markers associated with arterial calcification in patients with chronic kidney disease stages 3 and 4. Clin Kidney J 2014;7:167-173. Yoon YE, Han WK, Lee HH, et al. Abdominal aortic calcification in living kidney donors. Transplant Proc 2016;48:720-724. Kono T, Sakamoto K, Shinden S, et al. Pre-therapeutic nutritional assessment for predicting severe adverse events in patients with head and neck cancer treated by radiotherapy. Clin Nutr 36(6): 1681-1685, 2016. PMID: 27847115. DOI: 10.1016/j.clnu.2016.10.021 Tominaga T, Nonaka T, Sumida Y, et al. The c-reactive protein to albumin ratio as a predictor of severe side-effects of adjuvant chemotherapy in stage iii colorectal cancer patients. PLoS One 11(12): e0167967, 2016. PMID: 27930703. Mikoshiba T, Ozawa H, Saito S, et al. Usefulness of Hematological Inflammatory Markers in Predicting Severe Side-effects from Induction Chemotherapy in Head and Neck Cancer Patients. Anticancer Res. 2019 Jun;39(6):3059-3065. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4356279","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":300369657,"identity":"92914f3f-608b-43f5-b691-70f9958a3e31","order_by":0,"name":"Kouki Imaoka","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2UlEQVRIie3PPQrCMBTA8UDgZXlYxycVz9BS8AMvUxGc0htIF6GjJ/AQTs6FYqaCa0eh0EEcBMFRTHRwazMK5j8kIeQHL4y5XD9YwEGvOXk9xnN9oqE1GWQMYkOwm7A3YZpgYC66yUTAosZySkDyfqnWU2SiOO7byGwDRYQVaZIc5lLpwXC1qloHK0Tm441SQyIJmhCOrYgZrInk04qA8j+DSV4nmR1ZhrtSE2zGPNkSQudfTio8X1VKnljWd/lIR54oVCv51o+BzA52z01ezm/2r10ul+ufegH50kAW2n5BswAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0001-8972-5777","institution":"Hiroshima University Hospital: Hiroshima Daigaku Byoin","correspondingAuthor":true,"prefix":"","firstName":"Kouki","middleName":"","lastName":"Imaoka","suffix":""},{"id":300369658,"identity":"140b45bf-44e0-4aef-ac8f-d3b19d2f35ac","order_by":1,"name":"Manabu Shimomura","email":"","orcid":"","institution":"Hiroshima University Hospital: Hiroshima Daigaku Byoin","correspondingAuthor":false,"prefix":"","firstName":"Manabu","middleName":"","lastName":"Shimomura","suffix":""},{"id":300369659,"identity":"c2f647f5-5c3b-4a5a-b05e-bd6eee92ebbd","order_by":2,"name":"Hiroshi Okuda","email":"","orcid":"","institution":"Hiroshima University Hospital: Hiroshima Daigaku Byoin","correspondingAuthor":false,"prefix":"","firstName":"Hiroshi","middleName":"","lastName":"Okuda","suffix":""},{"id":300369660,"identity":"3d26517a-19e3-4d99-839a-dee44465d4b1","order_by":3,"name":"Takuya Yano","email":"","orcid":"","institution":"Hiroshima University Hospital: Hiroshima Daigaku Byoin","correspondingAuthor":false,"prefix":"","firstName":"Takuya","middleName":"","lastName":"Yano","suffix":""},{"id":300369662,"identity":"19a0783b-ed3a-4908-82f6-0019597ad22d","order_by":4,"name":"Shintaro Akabane","email":"","orcid":"","institution":"Hiroshima University Hospital: Hiroshima Daigaku Byoin","correspondingAuthor":false,"prefix":"","firstName":"Shintaro","middleName":"","lastName":"Akabane","suffix":""},{"id":300369664,"identity":"3b7e8620-e74e-4b46-9d1c-ff2c4a035959","order_by":5,"name":"Masahiro Ohira","email":"","orcid":"","institution":"Hiroshima University Hospital: Hiroshima Daigaku Byoin","correspondingAuthor":false,"prefix":"","firstName":"Masahiro","middleName":"","lastName":"Ohira","suffix":""},{"id":300369666,"identity":"6bcecf09-69c0-4449-a75f-7ae1da926bc8","order_by":6,"name":"Yuki Imaoka","email":"","orcid":"","institution":"Hiroshima University Hospital: Hiroshima Daigaku Byoin","correspondingAuthor":false,"prefix":"","firstName":"Yuki","middleName":"","lastName":"Imaoka","suffix":""},{"id":300369668,"identity":"6498d254-c479-44b7-a50c-f0ac3459f1f9","order_by":7,"name":"Kosuke Ono","email":"","orcid":"","institution":"Hiroshima University Hospital: Hiroshima Daigaku Byoin","correspondingAuthor":false,"prefix":"","firstName":"Kosuke","middleName":"","lastName":"Ono","suffix":""},{"id":300369670,"identity":"fabfc7a5-338b-40a9-a3d1-70d39cc50637","order_by":8,"name":"Tetsuya Mochizuki","email":"","orcid":"","institution":"Hiroshima University Hospital: Hiroshima Daigaku Byoin","correspondingAuthor":false,"prefix":"","firstName":"Tetsuya","middleName":"","lastName":"Mochizuki","suffix":""},{"id":300369672,"identity":"4c8c3df6-7d62-4e40-abd7-2426c724f34b","order_by":9,"name":"Keiso Matsubara","email":"","orcid":"","institution":"Hiroshima University Hospital: Hiroshima Daigaku Byoin","correspondingAuthor":false,"prefix":"","firstName":"Keiso","middleName":"","lastName":"Matsubara","suffix":""},{"id":300369674,"identity":"2f009fcb-88d2-4970-9bcc-4d4663c9e9b4","order_by":10,"name":"Tomoaki Bekki","email":"","orcid":"","institution":"Hiroshima University Hospital: Hiroshima Daigaku Byoin","correspondingAuthor":false,"prefix":"","firstName":"Tomoaki","middleName":"","lastName":"Bekki","suffix":""},{"id":300369675,"identity":"c443afd0-3e23-4723-8361-3c61a8d2d8af","order_by":11,"name":"Sho Ishikawa","email":"","orcid":"","institution":"Hiroshima University Hospital: Hiroshima Daigaku Byoin","correspondingAuthor":false,"prefix":"","firstName":"Sho","middleName":"","lastName":"Ishikawa","suffix":""},{"id":300369676,"identity":"1005f6be-6047-4e8b-8f2d-c8df55f420ba","order_by":12,"name":"Saki Sato","email":"","orcid":"","institution":"Hiroshima University Hospital: Hiroshima Daigaku Byoin","correspondingAuthor":false,"prefix":"","firstName":"Saki","middleName":"","lastName":"Sato","suffix":""},{"id":300369677,"identity":"a55063ae-2f8a-472d-9440-1abc891a018a","order_by":13,"name":"Atsuhiro Watanabe","email":"","orcid":"","institution":"Hiroshima University Hospital: Hiroshima Daigaku Byoin","correspondingAuthor":false,"prefix":"","firstName":"Atsuhiro","middleName":"","lastName":"Watanabe","suffix":""},{"id":300369678,"identity":"e0c12b06-4b6a-4c40-afc7-5f8aa17a6551","order_by":14,"name":"Minoru Hattori","email":"","orcid":"","institution":"Hiroshima University Hospital: Hiroshima Daigaku Byoin","correspondingAuthor":false,"prefix":"","firstName":"Minoru","middleName":"","lastName":"Hattori","suffix":""},{"id":300369679,"identity":"810798bd-dc32-4425-9a49-2b4abf8a0148","order_by":15,"name":"Hideki Ohdan","email":"","orcid":"","institution":"Hiroshima University Hospital: Hiroshima Daigaku Byoin","correspondingAuthor":false,"prefix":"","firstName":"Hideki","middleName":"","lastName":"Ohdan","suffix":""}],"badges":[],"createdAt":"2024-05-02 01:14:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4356279/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4356279/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":56621851,"identity":"20a24d2c-406d-4769-915c-5f414d0be3a7","added_by":"auto","created_at":"2024-05-16 18:10:52","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":147778,"visible":true,"origin":"","legend":"\u003cp\u003eStudy consort diagram\u003c/p\u003e\n\u003cp\u003eOf the 257 patients, 161 were included in the analysis, after excluding 81 who did not undergo adjuvant chemotherapy, 10 who had recurrence during AC, and 5 who could not be followed up during AC.\u003c/p\u003e\n\u003cp\u003eAC, adjuvant chemotherapy\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4356279/v1/66b751b5b88723d65c3bdf6d.png"},{"id":56621853,"identity":"bdbcf384-6116-445e-b286-b1ede9f2a519","added_by":"auto","created_at":"2024-05-16 18:10:52","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":285863,"visible":true,"origin":"","legend":"\u003cp\u003eCluster analysis based on the age and AAC volume\u003c/p\u003e\n\u003cp\u003eA k-means cluster analysis is conducted to elucidate the effects of age and AAC volume on AC incompletion. This analysis uses both age and AAC volume for stratification into three distinct clusters.\u003c/p\u003e\n\u003cp\u003eAAC, abdominal aortic calcification; AC, adjuvant chemotherapy\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4356279/v1/325b904b92622a7b3cb83856.png"},{"id":56621854,"identity":"9442534b-8780-41b0-8121-8b1f428a28af","added_by":"auto","created_at":"2024-05-16 18:10:52","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":261317,"visible":true,"origin":"","legend":"\u003cp\u003ePerioperative changes in nutrition status, inflammatory marker, and renal function between the high and low AAC groups; a) albumin level, b) neutrophil-to-lymphocyte ratio, c) estimated glomerular filtration rate (eGFR)\u003c/p\u003e\n\u003cp\u003eIn the high AAC group, the decrease in nutritional status at the initiation of AC did not recover to the level at the time of surgery by the end of AC. Additionally, in the high AAC group, inflammatory markers at the end of AC did not show improvement compared to those at surgery. The eGFR exhibited no significant changes at any of the assessed time point in either group.\u003c/p\u003e\n\u003cp\u003eAAC, abdominal aortic calcification; NLR, neutrophil-to-lymphocyte ratio; eGFR, estimated Glomerular Filtration rate; AC, adjuvant chemotherapy\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4356279/v1/6982b93224870293cbbcbd8d.png"},{"id":56621852,"identity":"c9da8ea9-da05-4ce9-8bdb-710e0b7bf9db","added_by":"auto","created_at":"2024-05-16 18:10:52","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":152271,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan–Meier survival curves of overall survival (OS) and recurrence-free survival (RFS) in stage III colorectal cancer between the AC completion and incompletion groups; a) OS, b) RFS\u003c/p\u003e\n\u003cp\u003eKaplan–Meier survival curve analysis showed worse RFS, but not OS, in the AC incompletion group than in the AC completion group.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4356279/v1/fac51f829cde17aea8da6dd2.png"},{"id":57062034,"identity":"ba52fbdc-9eaa-4e14-9912-d560e9b4bab9","added_by":"auto","created_at":"2024-05-24 06:22:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1208589,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4356279/v1/dd6c0261-615b-44f6-9b28-ce59c4e89657.pdf"}],"financialInterests":"","formattedTitle":"Abdominal aortic calcification predicts failure to complete adjuvant chemotherapy for stage III colorectal cancer: A retrospective cohort study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eColorectal cancer (CRC) is the third most commonly diagnosed cancer and the second leading cause of cancer-related deaths globally [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Adjuvant chemotherapy (AC) plays a crucial role in mitigating postoperative recurrence and improving patient prognosis [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Particularly, AC completion has been linked to reduced rates of postoperative recurrence, establishing it as the standard treatment protocol for stage III CRC [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. However, the adverse effects (AEs) of chemotherapy can be more pronounced in patients with comorbidities or deteriorating general health [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Consequently, factors such as advanced age and pre-existing health conditions are frequently cited as reasons for non-initiation of AC [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Considering these observations, it is critical to identify the risk factors that impede the completion of AC before its initiation. This process can facilitate the adjustment or moderation of chemotherapy intensity or necessitate more stringent monitoring of patients undergoing AC.\u003c/p\u003e \u003cp\u003eAbdominal aortic calcification (AAC) is known to be correlated with increased mortality related to cardiovascular diseases [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. AAC is also associated with malnutrition, chronic inflammation, and atherosclerosis syndrome [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Recent studies have indicated that the severity of vascular calcification exhibits a linear positive relationship with frailty in older adults [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], with older women at risk for rapid weight loss over a 5-year period [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. While AAC can simply be a marker of advanced age and frailty, there are several putative mechanisms by which AAC can potentially influence the risk of AC toxicity. Firstly, AAC has been reported to be associated with postoperative renal dysfunction [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Therefore, AAC could affect the pharmacokinetics of renally metabolized drugs, such as fluoropyrimidine and oxaliplatin. In addition, advanced age is correlated with a decline in bone marrow reserve and an increased risk of complications related to chemotherapy-induced myelosuppression [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Given such associations, we hypothesized that AAC could be an indicative marker of patient-specific vulnerability, thus acting as a reliable predictor of AC incompletion due to AC toxicity in stage III CRC patients. This study explored the efficacy of AAC as an indicator of AC incompletion.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatients\u003c/h2\u003e \u003cp\u003ePatients with CRC who underwent radical surgery and were diagnosed with pathological stage (pStage) III CRC in our institute between 2010 and 2021 were included. Clinical data at the time of colorectal surgery, including age, sex, American Society of Anesthesiologists Physical Status Classification System (ASA-PS) score [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], body mass index, hypertension (HT), diabetes mellitus (DM), hyperlipidemia (HL), blood examination data, postoperative complications, and pathological findings, were collected retrospectively from the medical records of the patients. In addition, the availability of AC introduction, details of the regimens, continuation or discontinuation, and severity of AEs were investigated. The decision of AC discontinuation was based on a comprehensive assessment by the physician, considering the degree of AEs, the patient's overall condition and wishes; the patient did not complete the intended course as scheduled at the time of induction; even after the specified dose was reduced by two levels or to a minimal dose level, the physician judged that the protocol treatment was difficult to continue, and the patient requested discontinuation of protocol treatment. This analysis excluded patients who did not undergo AC, patients who relapsed during the AC period, and patients who were not followed up during the AC period. For the postoperative adjuvant therapy, oxaliplatin combination therapy (capecitabine plus oxaliplatin or fluorouracil plus oxaliplatin) or fluoropyrimidine monotherapy was selected according to the guidelines of the Japanese Society for Cancer of the Colon and Rectum [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], considering the patient's postoperative condition and risk of recurrence. In this cohort study, no patients received capecitabine plus oxaliplatin for a planned 3-month period. Clinical data after AC introduction, including blood examination results or the degree of AEs, were collected retrospectively from the medical records of the patients. The patients were followed up using contrast-enhanced computed tomography (CT) and colonoscopy, combined with an evaluation of serum CEA and CA19-9 levels at 3-month intervals for 5 years and at 6-month intervals for 5 years thereafter.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eEvaluation of abdominal aortic calcification\u003c/h2\u003e \u003cp\u003eCT angiography was conducted using a 320-detector row CT scanner (Aquilion ONE ViSION, Toshiba Medical Systems, Japan) with a standardized examination protocol. The AAC score was determined utilizing the AZE VirtualPlace Lexus64 Anatomia software (AZE Inc., Tokyo, Japan). Employing the Agatston method [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], the software automatically computed the volume of AAC by identifying calcifications within the abdominal aorta, spanning from the origin of the renal artery to the iliac bifurcation. The AAC cutoff (992 mm\u003csup\u003e3\u003c/sup\u003e) was determined using the receiver operating characteristic curves of AC completion.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eCategorical variables are expressed as numbers and percentages. Continuous variables are presented as medians with interquartile ranges. Data from the two groups were compared using the chi-squared test or Fisher\u0026rsquo;s exact test for dichotomous outcomes. Paired Student's t tests and the nonparametric Mann\u0026ndash;Whitney U test were used for continuous outcomes with a skewed distribution. Univariate analyses were performed to assess the association between AC discontinuation and the following variables: age, sex, ASA-PS, AAC, HT, HL, DM, modified Glasgow prognostic score (mGPS) [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], geriatric nutritional risk index (GNRI) [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], controlling nutritional status (CONUT) [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], neutrophil-to-lymphocyte ratio (NLR) [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], tumor location, postoperative complications, and pStage. All variables were included in a multivariate logistic regression model using a stepwise (forward or backward) procedure. Independent variables were entered into the model at the 0.10 significance level and removed at the 0.20 level; these were used to select the covariates. Overall survival (OS) and recurrence-free survival (RFS) were plotted using the Kaplan\u0026ndash;Meier analysis and compared using log-rank statistics. All statistical analyses were performed using JMP statistical software (JMP\u0026reg; 17; SAS Institute Inc., Cary, NC, USA). Statistical significance was set at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\"\u003e\n \u003ch2\u003epatient characteristics\u003c/h2\u003e\n \u003cp\u003eA consort diagram of the study is shown in Fig.\u0026nbsp;\u003cspan\u003e1\u003c/span\u003e. The baseline characteristics of the high and low AAC groups are shown in Table\u0026nbsp;\u003cspan\u003e1\u003c/span\u003e. Compared with the low AAC group, the high AAC group had a significantly higher proportion of patients with older age, male sex, higher ASA-PS, HT, and DM. No significant differences were found in malnutrition or systemic inflammation status, including mGPS, CONUT, GNRI, and NLR, between the two groups. In addition, there were no significant differences in tumor factors, including pStage and histopathological differentiation. Furthermore, there was no difference in the choice of regimen between the two groups. The rate of AC completion was lower in the high AAC group than the low AAC group (72.9% vs. 90.3%; P\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e\n \u003cp\u003eTable 1. Patient characteristics\u0026nbsp;\u003c/p\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"614\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003eHigh AAC group (N=48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003eLow AAC group (N=113)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e71 (65-74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e61 (53-69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003eGender (Male/Female)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e38/10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e52/61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003eASA-PS\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e3 (6.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e33 (29.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e44 (91.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e79 (69.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e1 (2.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e1 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003eHT (+)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e25 (52.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e26 (23.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003eDM (+)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e19 (39.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e28 (24.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.059\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003eHL (+)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e24 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e54 (47.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.797\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003eCONUT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.799\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003enormal (0-1)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e31 (64.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e71 (62.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003emild (2-4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e17 (35.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e41 (36.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003emoderate (5-8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e1 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003ehigh (9-)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003eGNRI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.408\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003enormal (\u0026gt; 98)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e42 (87.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e93 (82.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003emild (92-98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e2 (4.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e12 (10.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003emoderate (\u0026lt; 92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e4 (8.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e8 (7.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003emGPS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.696\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e43 (89.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e99 (87.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e4 (8.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e13 (11.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e1 (2.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e1 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003eNLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e2.51 (1.86-3.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e2.23 (1.64-3.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.145\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003eTumor location (Colon/rectum)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e28/20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e58/55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.415\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003epStage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.582\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003eⅢa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e13 (27.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e38 (33.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003eⅢb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e31 (64.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e63 (55.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003eⅢc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e4 (8.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e12 (10.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003ePor/muc (+)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e3 (6.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e12 (10.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.383\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003eCEA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e3.9 (2.4-9.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e2.4 (1.7-6.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.047\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003ePostoperative complication (+)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e12 (25.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e15 (13.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.069\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003eregimen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.820\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003efluoropyrimidine monotherapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e34 (70.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e78 (69.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003eoxaliplatin combination therapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e14 (29.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e35 (31.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003eAC completion (+)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e35 (72.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e102 (90.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003eAAC, abdominal aortic calcification; ASA-PS, American Society of Anesthesiologists Physical Status Classification System; BMI, body mass index; HT, hypertension; HL, hyperlipidemia; DM, diabetes mellitus; NLR, neutrophil-to-lymphocyte ratio; CONUT, controlling nutritional status; mGPS; modified Glasgow prognostic score; GNRI, Geriatric Nutritional Risk Index; pStage, pathological stage; Por/muc, poorly/mucinous; AC; adjuvant chemotherapy; CEA, carcinoembryonic antigen\u003c/p\u003e\n \u003cdiv\u003e\n \u003cp\u003eTable 2.\u0026nbsp;Risk factors for adjuvant chemotherapy incompletion\u003c/p\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"612\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.66013071895425%\" rowspan=\"2\"\u003e\n \u003cp\u003eFactors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"35.45751633986928%\" colspan=\"3\"\u003e\n \u003cp\u003eUnivariate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.88235294117647%\" colspan=\"3\"\u003e\n \u003cp\u003eMultivariate\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.673218673218674%\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.673218673218674%\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.216216216216218%\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.547911547911548%\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.673218673218674%\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.216216216216218%\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.605220228384994%\" valign=\"top\"\u003e\n \u003cp\u003eAge (\u0026ge;\u0026nbsp;70\u0026nbsp;years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.398042414355627%\" valign=\"top\"\u003e\n \u003cp\u003e4.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.398042414355627%\" valign=\"top\"\u003e\n \u003cp\u003e1.88-11.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.766721044045678%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.66721044045677%\" valign=\"top\"\u003e\n \u003cp\u003e4.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.398042414355627%\" valign=\"top\"\u003e\n \u003cp\u003e1.68-14.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.766721044045678%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.605220228384994%\" valign=\"top\"\u003e\n \u003cp\u003eGender (Male)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.398042414355627%\" valign=\"top\"\u003e\n \u003cp\u003e1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.398042414355627%\" valign=\"top\"\u003e\n \u003cp\u003e0.47-2.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.766721044045678%\" valign=\"top\"\u003e\n \u003cp\u003e0.795\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.66721044045677%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.398042414355627%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.766721044045678%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.605220228384994%\" valign=\"top\"\u003e\n \u003cp\u003eAAC (\u0026ge;\u0026nbsp;992mm\u003csup\u003e3\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.398042414355627%\" valign=\"top\"\u003e\n \u003cp\u003e3.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.398042414355627%\" valign=\"top\"\u003e\n \u003cp\u003e1.41-8.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.766721044045678%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.66721044045677%\" valign=\"top\"\u003e\n \u003cp\u003e3.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.398042414355627%\" valign=\"top\"\u003e\n \u003cp\u003e1.05-8.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.766721044045678%\" valign=\"top\"\u003e\n \u003cp\u003e0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.605220228384994%\"\u003e\n \u003cp\u003eASA-PS (\u0026ge;2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.398042414355627%\" valign=\"top\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.398042414355627%\" valign=\"top\"\u003e\n \u003cp\u003e0.31-2.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.766721044045678%\" valign=\"top\"\u003e\n \u003cp\u003e0.737\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.66721044045677%\" valign=\"top\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.398042414355627%\" valign=\"top\"\u003e\n \u003cp\u003e0.13-1.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.766721044045678%\" valign=\"top\"\u003e\n \u003cp\u003e0.168\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.605220228384994%\"\u003e\n \u003cp\u003eCONUT (\u0026ge;5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.398042414355627%\" valign=\"top\"\u003e\n \u003cp\u003e1.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.398042414355627%\" valign=\"top\"\u003e\n \u003cp\u003e0.71-2.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.766721044045678%\" valign=\"top\"\u003e\n \u003cp\u003e0.312\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.66721044045677%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.398042414355627%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.766721044045678%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.605220228384994%\"\u003e\n \u003cp\u003emGPS (\u0026ge;1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.398042414355627%\" valign=\"top\"\u003e\n \u003cp\u003e1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.398042414355627%\" valign=\"top\"\u003e\n \u003cp\u003e0.53-3.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.766721044045678%\" valign=\"top\"\u003e\n \u003cp\u003e0.581\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.66721044045677%\" valign=\"top\"\u003e\n \u003cp\u003e2.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.398042414355627%\" valign=\"top\"\u003e\n \u003cp\u003e0.78-9.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.766721044045678%\" valign=\"top\"\u003e\n \u003cp\u003e0.119\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.605220228384994%\"\u003e\n \u003cp\u003eGNRI (\u0026lt;92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.398042414355627%\" valign=\"top\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.398042414355627%\" valign=\"top\"\u003e\n \u003cp\u003e0.09-6.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.766721044045678%\" valign=\"top\"\u003e\n \u003cp\u003e0.845\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.66721044045677%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.398042414355627%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.766721044045678%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.605220228384994%\"\u003e\n \u003cp\u003eNLR (\u0026ge;4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.398042414355627%\" valign=\"top\"\u003e\n \u003cp\u003e1.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.398042414355627%\" valign=\"top\"\u003e\n \u003cp\u003e0.49-4.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.766721044045678%\" valign=\"top\"\u003e\n \u003cp\u003e0.501\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.66721044045677%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.398042414355627%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.766721044045678%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.605220228384994%\"\u003e\n \u003cp\u003eTumor location (colon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.398042414355627%\" valign=\"top\"\u003e\n \u003cp\u003e1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.398042414355627%\" valign=\"top\"\u003e\n \u003cp\u003e0.53-3.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.766721044045678%\" valign=\"top\"\u003e\n \u003cp\u003e0.580\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.66721044045677%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.398042414355627%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.766721044045678%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.605220228384994%\"\u003e\n \u003cp\u003eHistological type (Por/muc)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.398042414355627%\" valign=\"top\"\u003e\n \u003cp\u003e1.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.398042414355627%\" valign=\"top\"\u003e\n \u003cp\u003e0.39-5.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.766721044045678%\" valign=\"top\"\u003e\n \u003cp\u003e0.563\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.66721044045677%\" valign=\"top\"\u003e\n \u003cp\u003e3.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.398042414355627%\" valign=\"top\"\u003e\n \u003cp\u003e0.70-15.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.766721044045678%\" valign=\"top\"\u003e\n \u003cp\u003e0.133\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.605220228384994%\"\u003e\n \u003cp\u003epStage (IIIb/IIIc)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.398042414355627%\" valign=\"top\"\u003e\n \u003cp\u003e1.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.398042414355627%\" valign=\"top\"\u003e\n \u003cp\u003e0.55-3.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.766721044045678%\" valign=\"top\"\u003e\n \u003cp\u003e0.448\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.66721044045677%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.398042414355627%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.766721044045678%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.605220228384994%\"\u003e\n \u003cp\u003ePostoperative complication (+)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.398042414355627%\" valign=\"top\"\u003e\n \u003cp\u003e1.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.398042414355627%\" valign=\"top\"\u003e\n \u003cp\u003e0.65-5.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.766721044045678%\" valign=\"top\"\u003e\n \u003cp\u003e0.247\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.66721044045677%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.398042414355627%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.766721044045678%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.605220228384994%\"\u003e\n \u003cp\u003eFluoropyrimidine monotherapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.398042414355627%\" valign=\"top\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.398042414355627%\" valign=\"top\"\u003e\n \u003cp\u003e0.28-1.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.766721044045678%\" valign=\"top\"\u003e\n \u003cp\u003e0.417\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.66721044045677%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.398042414355627%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.766721044045678%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003eOR, odds ratio; AAC, abdominal aortic calcification; ASA-PS, American Society of Anesthesiologists Physical Status Classification System; CONUT, controlling nutritional status; mGPS, modified Glasgow prognostic score; GNRI, Geriatric Nutritional Risk Index; NLR, neutrophil-to-lymphocyte ratio; pStage, pathological stage; AC, adjuvant chemotherapy.\u003c/p\u003e\n \u003cp\u003eTable 3. Severity and details of adverse events between the high and low AAC groups\u003c/p\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"614\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003eHigh AAC group (N=48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003eLow AAC group (N=113)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003eThe severity of adverse event\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.481\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003eGrade 0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e9 (18.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e12 (10.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003eGrade 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e8 (16.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e23 (20.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003eGrade 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e19 (39.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e53 (46.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003eGrade 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e12 (25.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e25 (22.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003eGrade 4-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003eHematological toxicity (\u0026ge;\u0026nbsp;Grade2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e12 (25.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e30 (26.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.838\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003eSymptoms of digestive system (\u0026ge;\u0026nbsp;Grade2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e10 (20.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e21 (18.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.741\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003eHand-foot syndrome (\u0026ge;\u0026nbsp;Grade2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e12 (25.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e32 (28.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.666\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003eOthers (\u0026ge;\u0026nbsp;Grade2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e9 (18.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e19 (16.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.767\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003eAAC, abdominal aortic calcification; AC, adjuvant chemotherapy\u003c/p\u003e\n \u003c/div\u003e\n \u003cp\u003eTable 4. Risk ratios for incompletion of adjuvant chemotherapy according to the cluster analysis based on the age and AAC volume\u003c/p\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"612\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.928104575163399%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003eN=161\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003eage (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.202614379084967%\" valign=\"top\"\u003e\n \u003cp\u003eAAC volume (mm\u003csup\u003e3\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.418300653594772%\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.784313725490197%\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.928104575163399%\" valign=\"top\"\u003e\n \u003cp\u003eCluster 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e43\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(26.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e50\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(45-55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.202614379084967%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003cp\u003e(0-30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e1 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.418300653594772%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.784313725490197%\" valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"0%\" valign=\"top\"\u003e\n \u003cp\u003eCluster 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e92\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(57.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003cp\u003e(63-72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" valign=\"top\"\u003e\n \u003cp\u003e208\u003c/p\u003e\n \u003cp\u003e(14-954)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" valign=\"top\"\u003e\n \u003cp\u003e4.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" valign=\"top\"\u003e\n \u003cp\u003e0.95-19.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" valign=\"top\"\u003e\n \u003cp\u003e0.059\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.928104575163399%\" valign=\"top\"\u003e\n \u003cp\u003eCluster 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e26\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(16.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003cp\u003e(65-76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.202614379084967%\" valign=\"top\"\u003e\n \u003cp\u003e3147\u003c/p\u003e\n \u003cp\u003e(2727-4146)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e6.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.418300653594772%\" valign=\"top\"\u003e\n \u003cp\u003e1.14-33.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.784313725490197%\" valign=\"top\"\u003e\n \u003cp\u003e0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003eOR, odds ratio; AAC, abdominal aortic calcification; CI, confidence interval\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\"\u003e\n \u003ch2\u003eIdentification of risk factors for AC incompletion\u003c/h2\u003e\n \u003cp\u003eUnivariate analysis revealed that older age (\u0026ge;\u0026thinsp;70 years) and high AAC (\u0026ge;\u0026thinsp;992 mm3) were risk factors for AC incompletion. The independent risk factors identified in the multivariate analysis were high AAC (OR, 3.00; 95% CI, 1.05\u0026ndash;8.53; P\u0026thinsp;=\u0026thinsp;0.040) and older age (OR, 4.85; 95% CI, 1.68\u0026ndash;14.0; P\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Table\u0026nbsp;\u003cspan\u003e2\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cem\u003eRisk ratios for AC incompletion according to the cluster analysis based on the age and AAC volume\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eSubsequently, to elucidate the effects of age and AAC volume on AC incompletion, a k-means cluster analysis was performed. This analysis utilized both age and AAC volume for stratification into three distinct clusters (Fig.\u0026nbsp;\u003cspan\u003e2\u003c/span\u003e): cluster 1 consisting of young age (50 [45\u0026ndash;55] years) and low AAC (0 [0\u0026ndash;30] mm3) (N\u0026thinsp;=\u0026thinsp;43), cluster 2 consisting of old age (68 [63\u0026ndash;72] years) and low AAC (208 [14\u0026ndash;954] mm3) (N\u0026thinsp;=\u0026thinsp;92), and cluster 3 consisting of old age (72 [65\u0026ndash;76] years) and high AAC (3147 [2727\u0026ndash;4146] mm3) (N\u0026thinsp;=\u0026thinsp;26). The odds ratio for AC incompletion increased with age and AAC volume (Table\u0026nbsp;\u003cspan\u003e4\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\"\u003e\n \u003ch2\u003eThe severity and details of AEs between the high and low AAC groups\u003c/h2\u003e\n \u003cp\u003eTable\u0026nbsp;\u003cspan\u003e3\u003c/span\u003e shows the association between the severity or details of the AEs and AAC. There were no differences in the severity or details of the AEs between the high and low AAC groups. Nevertheless, the high AAC group significantly failed to complete AC because of AEs. These results suggest that patients with high AAC are more prone to treatment intolerance of AC, independent of AEs.\u003c/p\u003e\n \u003cdiv\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cem\u003ePerioperative changes in nutrition status, inflammatory markers, and renal function between the high and low AAC groups\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eWe assessed the correlation between AAC and alterations in nutritional status, inflammatory markers, and renal function at three key time points: at the time of surgery, at the initiation of AC, and completion or discontinuation of AC.\u003c/p\u003e\n \u003cp\u003eUpon initiation of AC, albumin levels declined compared to preoperative levels in both AAC groups. In the low AAC group, albumin levels at the end of AC showed improvement relative to the levels at initiation, eventually returning to preoperative levels (Fig.\u0026nbsp;\u003cspan\u003e3\u003c/span\u003ea). Conversely, in the high AAC group, albumin levels at the end of AC remained stagnant compared to the levels at initiation and failed to recover to preoperative levels (Fig.\u0026nbsp;\u003cspan\u003e3\u003c/span\u003ea).\u003c/p\u003e\n \u003cp\u003eSimilarly, NLR levels improved at the initiation of AC compared with preoperative levels in both AAC groups. Subsequent to AC, NLR levels decreased in the low AAC group compared with the initiation levels (Fig.\u0026nbsp;\u003cspan\u003e3\u003c/span\u003eb). However, in the high AAC group, the NLR levels remained unchanged compared to the initiation level.\u003c/p\u003e\n \u003cp\u003eIn contrast, the estimated glomerular filtration rate (eGFR) exhibited no significant changes at any assessed time point, including at surgery, initiation of AC, and completion or discontinuation of AC, in both AAC groups (Fig.\u0026nbsp;\u003cspan\u003e3\u003c/span\u003ec).\u003c/p\u003e\n \u003cp\u003eThese findings suggest that high AAC was associated with diminished improvement in nutritional status or inflammatory markers following the introduction of AC.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\"\u003e\n \u003ch2\u003ePrognosis by completion of AC\u003c/h2\u003e\n \u003cp\u003eThe 5-year OS and RFS were 93.6% and 78.4%, respectively, and the median follow-up period was 60.7 months (range, 6\u0026ndash;108 months). The 5-year OS was 93.2% for patients who had completed AC and 95.8% for patients who did not complete AC, with no significant difference (P\u0026thinsp;=\u0026thinsp;0.973) (Fig.\u0026nbsp;\u003cspan\u003e4\u003c/span\u003ea). The 5-year RFS was 81.5% for patients who had completed AC and 60.4% for patients who did not complete AC, with a significant difference (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan\u003e4\u003c/span\u003eb).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis retrospective study aimed to identify potential predictors of AC incompletion in patients with stage III CRC, with a specific focus on the role of AAC as an indicator of AC incompletion. A notable finding was that high AAC volume was a significant predictor of AC incompletion in patients with stage III CRC. This finding underscores the comprehensive reflection of systemic conditions such as advanced age and comorbidities by AAC. Importantly, AAC was robustly associated with the critical outcomes of chemotherapy discontinuation in patients with CRC. This association suggests that AAC could effectively bridge the clinical gap by identifying risk factors that may impede AC completion prior to its initiation. Additionally, an increased risk of AC incompletion in patients with stage III CRC as both age and AAC volume increased. Finally, our results suggested that AC incompletion was associated with poor prognosis in patients with stage III CRC, as previously reported [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. To the best of our knowledge, this is the first study to establish a direct link between AAC and AC incompletion in patients with stage III CRC who commenced AC. These findings present AAC as a straightforward and immediately applicable metric in clinical settings.\u003c/p\u003e \u003cp\u003eThe identification of clinically effective biomarkers for exploring the sustainability of AC in the older population presents a significant challenge to clinical practice. One study reported that there was no age requirement for postoperative AC, and aggregated analyses of randomized-controlled trials conducted in both the United States and Europe have demonstrated comparable effectiveness in terms of recurrence prevention and survival extension between patients aged\u0026thinsp;\u0026ge;\u0026thinsp;70 years and those aged\u0026thinsp;\u0026lt;\u0026thinsp;60 years [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Our previous study also indicated that completion of AC may contribute to improved long-term prognosis, even in patients aged\u0026thinsp;\u0026ge;\u0026thinsp;80 years with stage III CRC [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. However, older age is considered an important factor in the introduction and continuation of AC by many clinicians and patients [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Increased age may also be associated with increased frailty and decreased tolerance to chemotherapy [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Although the decision on AC introduction or discontinuation should be made carefully, considering not only age, but also major organ functions, general health, and condition, no clinically useful biomarkers have yet been identified. Recently, geriatric assessment (GA) has been shown a useful method for measuring physical function, cognitive function, nutritional status, social factors, and family environment and has been reported to predict the completion of chemotherapy [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Although GA has proven useful for characterizing health and functional impairments potentially associated with oncological outcomes [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], it requires considerable time and human resources [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Therefore, it is necessary to establish a simpler biomarker for predicting AC completion than that for predicting GA. AAC is a well-known risk marker of cardiovascular diseases and is associated with hyperphosphatemia, diabetes, chronic inflammation, and chronic kidney disease [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. A recent study indicated that AAC severity independently correlated with an increased risk of pre-frailty or frailty in a dose-responsive relationship [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Furthermore, AAC volume can be calculated and quantified accurately, automatically, and rapidly using preoperative CT-based examination [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Our findings indicate that AAC volume is a specific predictor of AC completion as well as chronological age. This distinction is critical, as even among older patients, there is considerable variation in the overall health status and vulnerability, which are influenced by factors such as the extent of comorbidities and tumor progression. However, these variations cannot be accurately gauged using age alone. Consequently, measurement of AAC volume is anticipated to offer a more objective reflection of the systemic condition and tolerance to AC in patients.\u003c/p\u003e \u003cp\u003eThere may be several complex underlying mechanisms and reasons why patients cannot complete AC. Several reports have described the predictive role of inflammatory markers and nutritional factors in severe complications with chemotherapy [\u003cspan additionalcitationids=\"CR32\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. In the field of head and neck oncology, nutritional factors such as the prognostic nutritional index, mGPS, and the C-reactive protein to albumin ratio (CAR) are useful markers for predicting severe AEs [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. In CRC, CAR is also a useful tool for AEs (\u0026ge;\u0026thinsp;grade 3) of the AC [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Contrary to expectations, high AAC was not associated with the severity of AEs, but the risk of AC incompletion in stage III CRC patients in this study. High AAC can be related to the patients\u0026rsquo; adverse condition that cannot be assessed by the Common Terminology Criteria for Adverse Events (CTCAE) after AC introduction. Therefore, we focused on the association of AAC with alterations in nutritional status and inflammatory markers following the introduction of AC. Our findings suggest that higher levels of AAC are linked to a reduced improvement in nutritional status or inflammatory markers after the administration of AC, which can potentially contribute to AC incompletion independent of the AE severity. Thus, AAC could serve as an indicative marker of patient-specific susceptibility to the tolerance of AC.\u003c/p\u003e \u003cp\u003eThis study had some limitations that should be considered when interpreting our findings. Specifically, the retrospective and non-randomized study design must be mentioned. The small sample size of patients at a single center may also weaken the conclusion. Future prospective studies involving a larger number of patients with high AAC are required to analyze the effects of AC on clinical outcomes.\u003c/p\u003e \u003cp\u003eIn conclusion, high AAC volume may help us to more closely follow-up patients who have a potential risk of AC incompletion before AC introduction.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDisclosures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest:\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical statements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere is no need for consent to participate to be obtained due to retrospective study. Administrative permissions were not required to access and use the medical records described in this study. This study was authorized in advance by the institutional review board of the Hiroshima University Hospital.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe registration number of the study: E744-3\u003c/p\u003e\n\u003cp\u003eAnimal studies: N/A\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eKI, MS, and TY conceived and designed the study. KI, KO, KM, TM, TB, SI, SS, and AW acquired the data and calculated AAC scores. KI, TY, SM, SA, MO, YI and MH analyzed and interpreted the data, and drafted the manuscript. KI, YT, MS, SA, and HO critically revised the article. KI, YT, and HO approved the final version of the manuscript to be published.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e\u003cstrong\u003ecknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank Editage for the English language review.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMorgan E, Arnold M, Gini A, et al. Global burden of colorectal cancer in 2020 and 2040: incidence and mortality estimates from GLOBOCAN. Gut. 2023 Feb;72(2):338-344.\u003c/li\u003e\n\u003cli\u003eKnapen DG, Cherny NI, Zygoura P, et al. Lessons learnt from scoring adjuvant colon cancer trials and meta-analyses using the ESMO-magnitude of clinical benefit scale V.1.1. ESMO Open. 2020;5(5):e000681.\u003c/li\u003e\n\u003cli\u003eYoshino T, Arnold D, Taniguchi H, et al. Pan-Asian adapted ESMO consensus guidelines for the management of patients with metastatic colorectal cancer: a JSMO-ESMO initiative endorsed by CSCO, KACO, MOS. SSO and TOS Ann Oncol. 2018;29(1):44\u0026ndash;70.\u003c/li\u003e\n\u003cli\u003eShahrokni, A., Kim, S. J., Bosl, G. J. \u0026amp; Korc-Grodzicki, B. How we care for an older patient with cancer. J. Oncol. Pract. 13(2), 95\u0026ndash;102.\u003c/li\u003e\n\u003cli\u003eAbdel-Rahman O, Tang PA, Koski S. Hospitalizations among early-stage colon cancer patients receiving adjuvant chemotherapy: a real-world study. Int J Colorectal Dis. 2021;36(9):1905\u0026ndash;13: 1905\u0026ndash;1913. \u003c/li\u003e\n\u003cli\u003eCriqui MH, Denenberg JO, McClelland RL, et al. Abdominal aortic calcium, coronary artery calcium, and cardiovascular morbidity and mortality in the Multi-Ethnic Study of Atherosclerosis. Arterioscler Thromb Vasc Biol. 2014 Jul;34(7):1574-9. Epub 2014 May 8. Erratum in: Arterioscler Thromb Vasc Biol. 2015 Jan;35(1):e1.\u003c/li\u003e\n\u003cli\u003eZhang K, Gao J, Chen J, et al. MICS, an easily ignored contributor to arterial calcification in CKD patients. Am J Physiol Renal Physiol. 2016 Oct 1;311(4):F663-F670. \u003c/li\u003e\n\u003cli\u003eStenvinkel P, Heimb\u0026uuml;rger O, Lindholm B, et al. Are there two types of malnutrition in chronic renal failure? Evidence for relationships between malnutrition, inflammation and atherosclerosis (MIA syndrome). Nephrol Dial Transplant. 2000 Jul;15(7):953-60.\u003c/li\u003e\n\u003cli\u003eLee SY, Chao CT, Huang JW, et al. Vascular Calcification as an Underrecognized Risk Factor for Frailty in 1783 Community-Dwelling Elderly Individuals. J Am Heart Assoc. 2020 Sep 15;9(18):e017308.\u003c/li\u003e\n\u003cli\u003eSmith C, Sim M, Dalla Via J, et al. Extent of Abdominal Aortic Calcification Is Associated With Incident Rapid Weight Loss Over 5 Years: The Perth Longitudinal Study of Ageing Women. Arterioscler Thromb Vasc Biol. 2024;44(2):e54-e64.\u003c/li\u003e\n\u003cli\u003eIde, R., Ohira, M., Imaoka, Y., et al. (2023). Impact of Abdominal Aortic Calcification on Chronic Kidney Disease After Liver Transplantation: A Retrospective Study. Transplantation proceedings, 55(4), 956\u0026ndash;960. \u003c/li\u003e\n\u003cli\u003eDees EC, O\u0026apos;Reilly S, Goodman SN, et al. A prospective pharmacologic evaluation of age-related toxicity of adjuvant chemotherapy in women with breast cancer. Cancer Invest. 2000;18(6):521-9.\u003c/li\u003e\n\u003cli\u003eHackett NJ, De Oliveira GS, Jain UK, et al. ASA class is a reliable independent predictor of medical complications and mortality following surgery. Int J Surg. 2015;18:184\u0026ndash;190. \u003c/li\u003e\n\u003cli\u003eHashiguchi Y, Muro K, Saito Y et al (2020) Japanese Society for Cancer of the Colon and Rectum (JSCCR) guidelines 2019 for the treatment of colorectal cancer. Int J Clin Oncol 25:1\u0026ndash;42. \u003c/li\u003e\n\u003cli\u003eAgatston AS, Janowitz WR, Hildner FJ, , et al. Quantification of coronary artery calcium using ultrafast computed tomography. J Am Coll Cardiol. 1990 Mar 15;15(4):827\u0026ndash;32.\u003c/li\u003e\n\u003cli\u003eHirashima K, Watanabe M, Shigaki H, et al (2014) Prognostic significance of the modified Glasgow prognostic score in elderly patients with gastric cancer. J Gastroenterol. 49:1040\u0026ndash;1046.\u003c/li\u003e\n\u003cli\u003eLi L, Wang H, Yang J, et al. Geriatric nutritional risk index predicts prognosis after hepatectomy in elderly patients with hepatitis B virus-related hepatocellular carcinoma. \u003cem\u003eSci Rep\u003c/em\u003e 2018;8:12561.\u003c/li\u003e\n\u003cli\u003eElghiaty A, Kim J, Jang WS, et al. Preoperative controlling nutritional status (CONUT) score as a novel immune-nutritional predictor of survival in non-metastatic clear cell renal cell carcinoma of \u0026le;7 cm on preoperative imaging. J Cancer Res Clin Oncol. (2019) 145:957\u0026ndash;65. \u003c/li\u003e\n\u003cli\u003eGuthrie GJ Charles KA Roxburgh CS et al. The systemic inflammation-based neutrophil-lymphocyte ratio: experience in patients with cancer. Crit Rev Oncol Hematol. 2013;88(1):218\u0026ndash;230.\u003c/li\u003e\n\u003cli\u003eSargent DJ, Goldberg RM, Jacobson SD, et al (2001) A pooled analysis of adjuvant chemotherapy for resected colon cancer in elderly patients. N Engl J Med 345(15):1091\u0026ndash;1097.\u003c/li\u003e\n\u003cli\u003eMochizuki T, Shimomura M, Nakahara M et al (2023) Survival outcomes of patients with stage III colorectal cancer aged\u0026thinsp;\u0026ge;\u0026thinsp;80 years who underwent curative resection: the HiSCO-04 prospective cohort study. Int J Clin Oncol. doi: 10.1007/s10147-023-02440-9. Epub ahead of print.\u003c/li\u003e\n\u003cli\u003eKim HH, Ihn MH, Lee YH, et al. Effect of age on laparoscopic surgery and postoperative chemotherapy in elderly patients with colorectal cancer. Ann Coloproctol. 2020;36(4):229\u0026ndash;42: 229\u0026ndash;242.\u003c/li\u003e\n\u003cli\u003eBadic B, Oguer M, Cariou M, et al. Prognostic factors for stage III colon cancer in patients 80\u0026thinsp;years of age and older. Int J Colorectal Dis. 2021;36\u003c/li\u003e\n\u003cli\u003eDobie SA, Baldwin LM, Dominitz JA, et al. Completion of therapy by Medicare patients with stage III colon cancer. J Natl Cancer Inst. 2006 May 3;98(9):610-9.\u003c/li\u003e\n\u003cli\u003eAaldriks AA, Maartense E, Nortier HJ, et al: Prognostic factors for the feasibility of chemotherapy and the Geriatric Prognostic Index (GPI) as risk profile for mortality before chemotherapy in the elderly. Acta Oncol 55:15-23, 2016\u003c/li\u003e\n\u003cli\u003eVon Gruenigen VE, Huang HQ, Beumer JH, et al. Chemotherapy completion in elderly women with ovarian, primary peritoneal or fallopian tube cancer - an NRG oncology/Gynecologic Oncology Group study. Gynecol Oncol 144:459-467, 2017\u003c/li\u003e\n\u003cli\u003eWildiers H, Heeren P, Puts M, et al. International Society of Geriatric Oncology consensus on geriatric assessment in older patients with cancer. J Clin Oncol. 2014;32:2595\u0026ndash;2603.\u003c/li\u003e\n\u003cli\u003eCaillet P, Laurent M, Bastuji-Garin S, et al. Optimal management of elderly cancer patients: Usefulness of the Comprehensive Geriatric Assessment. Clin Interv Aging. 2014;9:1645\u0026ndash;1660.\u003c/li\u003e\n\u003cli\u003eKiu Weber CI, Duchateau‐Nguyen G, Solier C, et al. Cardiovascular risk markers associated with arterial calcification in patients with chronic kidney disease stages 3 and 4. Clin Kidney J 2014;7:167-173.\u003c/li\u003e\n\u003cli\u003eYoon YE, Han WK, Lee HH, et al. Abdominal aortic calcification in living kidney donors. Transplant Proc 2016;48:720-724.\u003c/li\u003e\n\u003cli\u003eKono T, Sakamoto K, Shinden S, et al. Pre-therapeutic nutritional assessment for predicting severe adverse events in patients with head and neck cancer treated by radiotherapy. Clin Nutr 36(6): 1681-1685, 2016. PMID: 27847115. DOI: 10.1016/j.clnu.2016.10.021\u003c/li\u003e\n\u003cli\u003eTominaga T, Nonaka T, Sumida Y, et al. The c-reactive protein to albumin ratio as a predictor of severe side-effects of adjuvant chemotherapy in stage iii colorectal cancer patients. PLoS One 11(12): e0167967, 2016. PMID: 27930703.\u003c/li\u003e\n\u003cli\u003eMikoshiba T, Ozawa H, Saito S, et al. Usefulness of Hematological Inflammatory Markers in Predicting Severe Side-effects from Induction Chemotherapy in Head and Neck Cancer Patients. Anticancer Res. 2019 Jun;39(6):3059-3065.\u003c/li\u003e\n\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":"calcification, colorectal cancer, adjuvant chemotherapy, incompletion","lastPublishedDoi":"10.21203/rs.3.rs-4356279/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4356279/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eCompletion of postoperative adjuvant chemotherapy (AC) contributes to improved prognosis of patients with pathological stage (pStage) III colorectal cancer (CRC). Therefore, identifying patients with AC intolerance is important. Although abdominal aortic calcification (AAC) indicates frailty, its clinical impact on AC completion remains unclear. This study aimed to clarify the association between AAC and AC incompletion.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003ePatients who underwent AC for pStage III CRC between 2010 and 2021 (n\u0026thinsp;=\u0026thinsp;161) were divided into two groups based on an AAC cutoff of 992 mm\u003csup\u003e3\u003c/sup\u003e, determined using the receiver operating characteristic curves for AC completion. We investigated the perioperative clinicopathological factors and compared the frequency and severity of AC adverse events between the groups.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe high AAC group had a significantly higher proportion of patients with older age (\u0026ge;\u0026thinsp;70 years), male sex, hypertension, and AC incompletion than the low AAC group. The regimens were not significantly different. No significant difference in the frequency or severity of adverse events was observed in either group. In the multivariate analysis, high AAC and older age were significantly associated with AC incompletion. Furthermore, k-means cluster analysis based on both age and AAC volume also demonstrated an increased risk of AC incompletion in patients with stage III CRC as both age and AAC volume increased. High AAC was associated with diminished improvement in nutritional status or inflammatory markers after the administration of AC.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eHigh AAC is a potential risk marker for predicting AC incompletion in patients with stage III CRC before introducing AC.\u003c/p\u003e","manuscriptTitle":"Abdominal aortic calcification predicts failure to complete adjuvant chemotherapy for stage III colorectal cancer: A retrospective cohort study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-16 18:10:42","doi":"10.21203/rs.3.rs-4356279/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":"e99551f3-bb2e-4684-82c6-b22fc098900a","owner":[],"postedDate":"May 16th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-05-24T06:14:08+00:00","versionOfRecord":[],"versionCreatedAt":"2024-05-16 18:10:42","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4356279","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4356279","identity":"rs-4356279","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}