Abstract
Background
The impact of chemotherapy on cardiocerebrovascular disease (CCVD) outcomes in patients with colorectal cancer (CRC) remains insufficiently explored. This research aimed to clarify the association between chemotherapy and CCVD-related mortality in middle-aged and elderly CRC patients.
Methods
CRC patients aged ≥ 50 years at diagnosis were identified from the Surveillance, Epidemiology, and End Results (SEER) database for the period 2010–2015. The primary outcome was CCVD-related mortality. Survival analyses included Kaplan-Meier (KM) curves to characterize CCVD-related survival patterns and multivariate competing risks regression analysis to evaluate the independent association between chemotherapy and CCVD-related mortality. Subgroup analyses and Fine-Gray competing risks models were additionally performed to enhance the robustness of study findings.
Results
A total of 136 095 CRC patients were included. KM analysis showed a significantly lower cumulative risk of CCVD-related mortality in chemotherapy treatment group than in non-chemotherapy treatment group. After adjusting for age, race, gender, primary tumor site, and tumor stage, multivariate competing risks regression analysis confirmed that chemotherapy was an independent protective factor against CCVD-related mortality (sHR = 0.75, 95% CI 0.71–0.79, P < 0.001). Subgroup analyses and Fine-Gray competing risks models further validated the robustness of chemotherapy’s beneficial effect on CCVD outcomes.
Conclusion
Chemotherapy may serve as an independent protective factor against CCVD-related mortality in CRC patients. These findings can help alleviate concerns regarding chemotherapy-associated CCVD risk in CRC management and provide novel insights for clinical decision-making and future research.
Keywords: Colorectal cancer, Chemotherapy, Cardiocerebrovascular disease-related mortality, Survival analysis, Middle-aged and elderly patients
Introduction
Colorectal cancer (CRC) represents the third most prevalent malignancy globally, ranking as the second most common cancer in women and the third in men. According to 2012 global cancer statistics, 614 000 female cases (9.2% of total new cancer diagnoses) and 746 000 male cases (10.0% of total new cancer diagnoses) were reported [1]. Analysis of survival data from 2003 to 2009 (with follow-up through 2010) demonstrated a 5-year relative survival rate of 64.9%, with localized stage CRC patients exhibiting a 90.3% 5-year survival rate [2, 3]. Recent advancements in therapeutic strategies, particularly the integration of multiple cytotoxic agents and targeted therapies, have substantially improved overall survival from approximately 12 months to over 30 months in contemporary clinical trials [4, 5]. Epidemiological evidence indicates that CRC patients exhibit a fourfold increased risk of developing cardiovascular diseases compared to the general population [6, 7], with cancer-associated cardiocerebrovascular disease (CCVD)-related mortality being a significant concern [8]. While cytotoxic and biological agents constitute the primary systemic treatment modalities [9, 10], conflicting evidence exists regarding the association between anticancer therapies and cardiovascular-related hospitalizations [11]. Most prior cardio-oncology research has centered on chemotherapy-related cardiovascular toxicities, with scarce data on its long-term impact on CCVD-related mortality in CRC patients. The net clinical effect of chemotherapy on CCVD outcomes beyond toxic effects remains poorly characterized. We therefore investigated the association between chemotherapy and CCVD-related mortality in a large real-world cohort of middle-aged and elderly CRC patients, using competing risk regression to adjust for competing events.
In this study, we conducted a comprehensive evaluation of CCVD-related mortality risk in the US population aged ≥ 50 years and were diagnosed with CRC between 2010 and 2015, utilizing data from the Surveillance, Epidemiology, and End Results (SEER) program. This large-scale retrospective analysis, encompassing 136 095 CRC patients with 10 100 documented CCVD-related mortality, provides evidence regarding CCVD-related mortality patterns among middle-aged and elderly CRC survivors. The findings offer valuable insights for optimizing chemotherapy strategies in the context of CCVD health management.
Materials and methods
Study population and data source
This population-based retrospective cohort study was conducted in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines [12]. The study utilized data from the Surveillance, Epidemiology, and End Results (SEER) registry, a comprehensive database documenting incident cancer cases in the United States. The study population comprised individuals aged ≥ 50 years who were firstly diagnosed with primary malignant colorectal neoplasms between 2010 and 2015 with sufficient demographic, clinical stage, treatment and follow-up information were included, and the follow-up endpoint was November 2023. These variables included year of diagnosis, age at diagnosis, sex, race, diagnostic confirmation, sequence number, AJCC clinical stage, survival months, COD to site recode, vital status, chemotherapy recode and treatment sequence with surgery. Age at diagnosis was stratified into eight categories: 50–54, 55–59, 60–64, 65–69, 70–74, 75–80, 80–85, and 85 + years. Based on whether they received chemotherapy, patients were allocated into the chemotherapy treatment group and non-chemotherapy treatment group. As the study employed de-identified data, institutional review board approval was not required.
Case identification and classification
CRC identified and classified based on codes from the International Classification of Diseases for Oncology (ICD-O): colon cancer (ICD-O codes: C18.0–C18.9, C26.0) and rectal cancer (ICD-O codes: C19.9, C20.9). The study included all anatomical subsites of CRC, namely the ascending colon, hepatic flexure of colon, transverse colon, splenic flexure of colon, descending colon, sigmoid colon, overlapping lesion of colon, colon, not otherwise specified (NOS), rectosigmoid junction, rectum, NOS.
Chemotherapy record identification and classification
Patients who received chemotherapy were defined as those undergoing systemic chemotherapy (including adjuvant, neoadjuvant, or palliative chemotherapy) before, during, or after other CRC treatments (e.g., surgery, radiotherapy). Conversely, patients without chemotherapy were defined as those with no documented systemic chemotherapy throughout the entire CRC treatment course, regardless of other received treatments (e.g., surgery, radiotherapy, supportive care).
Mortality assessment
The primary outcome of this study was CCVD-related mortality. Cause-specific mortality was ascertained using International Classification of Diseases, 10th Revision (ICD-10) codes extracted from the SEER database. Specifically, CCVD-related mortality was defined as deaths attributed to the following conditions: aortic aneurysm and dissection, atherosclerosis, cerebrovascular disease, heart disease, hypertension without heart disease, and other diseases of arteries, arterioles, and capillaries, which corresponding ICD-10 codes were G45, I10, I20–I25, I30–I50, I60–I67, I70–I73, I78, and M30–M31. The cancer-specific mortality was defined as deaths due to CRC.
Statistical methods
Continuous variables demonstrating normal distribution were analyzed utilizing the student’s t-test, while those exhibiting non-normal distribution were evaluated through the non-parametric Wilcoxon rank-sum test. To address confounding from baseline imbalances inherent to retrospective research, we adjusted for all imbalanced covariates in multivariable models and performed stratified analyses to confirm the robustness of our results. Multivariate competing risks regression analysis were developed to identify independent prognostic factors, incorporating variables that demonstrated P < 0.05 in the preliminary univariate competing risks regression analysis, and then visualized by forest plots to compare these risk factors. Kaplan-Meier (KM) curves were performed to characterize CCVD-related survival patterns. Subgroup analyses were additionally performed to enhance the robustness of study findings. All statistical analyses were conducted using SEER*Stat (version 8.4.3) and R software (version 4.0.5).
Results
Cohort characteristics
As shown in Fig. 1, patients with a diagnosis of CRC between 2010 and 2015 were selected for the study from the SEER database. The study cohort comprised 136 095 colorectal cancer patients, including 84 220 who did not receive chemotherapy and 51 875 who underwent chemotherapy, all meeting the predefined inclusion criteria. This population accounted for 10 100 CCVD-related mortality events. The mean overall survival duration was 61.92 months in the chemotherapy group and 64.98 months in the non-chemotherapy group. Detailed demographic and clinical characteristics are presented in Table 1. Baseline characteristic comparisons revealed statistically significant differences in age distribution, AJCC disease stage, primary tumor site, and radiation therapy between the chemotherapy and non-chemotherapy groups (Table 1).
Fig. 1.
Flowchart of the study population
Table 1.
The characteristic of the population
| n | No/Unknown | Yes | p | |
|---|---|---|---|---|
| 84,220 | 51,875 | |||
| age (%) | 50–54 | 8615 (10.23) | 8569 (16.52) | < 0.0001 |
| 55–59 | 8862 (10.52) | 9245 (17.82) | ||
| 60–64 | 10,516 (12.49) | 9664 (18.63) | ||
| 65–69 | 11,575 (13.74) | 8779 (16.92) | ||
| 70–74 | 11,030 (13.10) | 6566 (12.66) | ||
| 75–79 | 10,559 (12.54) | 4758 (9.17) | ||
| 80–84 | 10,610 (12.60) | 2905 (5.60) | ||
| 85+ | 12,453 (14.79) | 1389 (2.68) | ||
| Primary Site - labeled (%) | Cecum | 15,308 (18.18) | 7324 (14.12) | < 0.0001 |
| Ascending colon | 14,361 (17.05) | 5595 (10.79) | ||
| Hepatic flexure of colon | 3184 (3.78) | 1351 (2.60) | ||
| Transverse colon | 6327 (7.51) | 2616 (5.04) | ||
| Splenic flexure of colon | 1891 (2.25) | 1050 (2.02) | ||
| Descending colon | 3856 (4.58) | 1830 (3.53) | ||
| Sigmoid colon | 18,004 (21.38) | 9178 (17.69) | ||
| Overlapping lesion of colon | 865 (1.03) | 442 (0.85) | ||
| Colon, NOS | 2093 (2.49) | 961 (1.85) | ||
| Rectosigmoid junction | 5627 (6.68) | 4775 (9.20) | ||
| Rectum, NOS | 12,704 (15.08) | 16,753 (32.29) | ||
| Survival months (mean (SD)) | 64.981 (45.989) | 61.915 (42.661) | < 0.0001 | |
| status (%) | alive | 39,393 (46.77) | 21,186 (40.84) | < 0.0001 |
| CCVD | 8153 (9.68) | 1947 (3.75) | ||
| Death of other reason | 36,674 (43.55) | 28,742 (55.41) | ||
| Race recode (%) | American Indian/Alaska Native | 666 (0.79) | 486 (0.94) | < 0.0001 |
| Asian or Pacific Islander | 7814 (9.28) | 4693 (9.05) | ||
| Black | 9517 (11.30) | 5977 (11.52) | ||
| Unknown | 637 (0.76) | 109 (0.21) | ||
| White | 65,586 (77.87) | 40,610 (78.28) | ||
| gender (%) | Female | 41,789 (49.62) | 22,719 (43.80) | < 0.0001 |
| Male | 42,431 (50.38) | 29,156 (56.20) | ||
| stage (%) | 0 | 4600 (5.46) | 114 (0.22) | < 0.0001 |
| I | 31,346 (37.22) | 2321 (4.47) | ||
| II | 24,352 (28.91) | 9123 (17.59) | ||
| III | 12,182 (14.46) | 23,306 (44.93) | ||
| IV | 11,740 (13.94) | 17,011 (32.79) | ||
| Reason no cancer-directed surgery (%) | Not performed, patient died prior to recommended surgery | 144 (0.17) | 82 (0.16) | < 0.0001 |
| Not recommended | 8296 (9.85) | 9138 (17.62) | ||
| Not recommended, contraindicated due to other cond; autopsy only (1973–2002) | 812 (0.96) | 541 (1.04) | ||
| Recommended but not performed, patient refused | 999 (1.19) | 384 (0.74) | ||
| Recommended but not performed, unknown reason | 462 (0.55) | 211 (0.41) | ||
| Recommended, unknown if performed | 192 (0.23) | 543 (1.05) | ||
| Surgery performed | 73,167 (86.88) | 40,950 (78.94) | ||
| Unknown; death certificate; or autopsy only (2003+) | 148 (0.18) | 26 (0.05) | ||
| Radiation recode (%) | Beam radiation | 1485 (1.76) | 16,658 (32.11) | < 0.0001 |
| Combination of beam with implants or isotopes | 1 (0.00) | 17 (0.03) | ||
| None/Unknown | 81,878 (97.22) | 34,467 (66.44) | ||
| Radiation, NOS method or source not specified | 30 (0.04) | 270 (0.52) | ||
| Radioactive implants (includes brachytherapy) (1988+) | 6 (0.01) | 65 (0.13) | ||
| Radioisotopes (1988+) | 9 (0.01) | 46 (0.09) | ||
| Recommended, unknown if administered | 242 (0.29) | 278 (0.54) | ||
| Refused (1988+) | 569 (0.68) | 74 (0.14) |
Chemotherapy and cardiocerebrovascular survival
The impact of chemotherapy on survival outcomes was evaluated across the study population. Patients in the non‑chemotherapy group showed significantly better long‑term overall survival than those receiving chemotherapy (P < 0.001) (Fig. 1A). In contrast, the chemotherapy group exhibited significantly higher CCVD‑free survival (P < 0.001) (Fig. 1B).
Univariate and multivariate analysis
We applied the Fine-Gray competing risk regression model to assess the independent association between chemotherapy and CCVD-related mortality. Unlike traditional Cox models, the Fine-Gray model accounts for this competing event to generate accurate, unbiased effect estimates. Univariate competing risk regression analysis identified several covariates associated with CCVD-related mortality (P < 0.001), encompassing age, race, gender, primary site, AJCC stage, and surgery history (Fig. 3). Multivariate competing risk regression analysis adjusting for age, race, gender, primary tumor site, AJCC stages, surgery condition (Fig. 4) demonstrated that chemotherapy remained an independent prognostic factor. Patients who received chemotherapy exhibited a significantly reduced risk of CCVD-related mortality compared to those who did not [sHR = 0.75; 95% confidence interval (CI) 0.71–0.79; P < 0.001].
Fig. 3.
Univariate competing risk regression analysis of the risk of cardiocerebrovascular disease-related mortality in patients with colorectal cancer
Fig. 4.
Multivariate competing risk regression analysis of the risk of cardiocerebrovascular disease-related mortality in patients with colorectal cancer
Subgroup analysis for confounding adjustment.
Then subgroup analysis was done to assess the risk of CCVD-related mortality in chemotherapy and no-chemotherapy CRC patients across various patient characteristics. Among the total cohort (n = 51 875 in chemotherapy group vs. n = 84 220 in non-chemotherapy group), chemotherapy was associated with a significantly lower subdistribution hazard ratio (sHR = 0.41; 95% CI 0.39–0.43; P < 0.001). Stratification by sex, race, tumor stage (AJCC), age, and anatomical site demonstrated largely consistent patterns: chemotherapy was associated with HRs < 1 and P < 0.05 in the majority of subgroups. (Fig. 5). The protective effect of chemotherapy against CCVD-related mortality increased with age, with a 40%–50% risk reduction in CRC patients aged ≥ 70 years and a 77% reduction in those with stage IV disease.
Fig. 5.
Subgroup analysis of the cardiocerebrovascular disease associated mortality between chemotherapy and non-chemotherapy in colorectal cancer patients
To adjust for potential confounding by gender and age, we conducted stratified analysis with gender and age. In male patients, the 3-year and 5-year CCVD survival rates were 97.8% and 96.3%, respectively, in the chemotherapy group, compared with 94.6% and 91.9% in the non-chemotherapy group. Similarly, in female patients, the 3-year and 5-year CCVD survival rates were 98.6% and 97.6% in the chemotherapy group, versus 95.0% and 92.0% in the non-chemotherapy group (Fig. 6).
Fig. 6.
The Kaplan - Meier survival analysis of cardiocerebrovascular disease in colorectal cancer patients was conducted according to different genders. Both male (A) and female (B) could benefit from chemotherapy
The Kaplan-Meier survival analysis for CCVD-related mortality stratified by chemotherapy status across different age groups is presented in Fig. 7. The risk of CCVD-related mortality was reduced in all age groups except for the 50–54 years cohort.
Fig. 7.
Age-stratified Kaplan-Meier survival analysis of cardiocerebrovascular disease related mortality in colorectal cancer patients. Except from 50–54 groups, chemotherapy decreases cardiocerebrovascular disease associated mortality in all age groups
Furthermore, considering variations in chemotherapy regimens across different tumor stages, we performed stratified analyses according to AJCC stage. The CCVD survival curves across all stages demonstrated consistently higher probabilities in the chemotherapy group during follow‑up (all log‑rank P < 0.001) (Fig. 8A–D). For stage I patients (Fig. 9A), the chemotherapy group had superior early survival, but its survival probability was overtaken by the non-chemotherapy group after long-term follow-up (log‑rank P < 0.001). Among patients with stage II–IV disease (Fig. 9B and D), the chemotherapy group exhibited superior overall survival compared with the non‑chemotherapy group.
Fig. 8.
The Kaplan−Meier Curve for cardiocerebrovascular disease related mortality in colorectal cancer patients with stage I – IV disease
Fig. 9.
The Kaplan-Meier survival curves for overall survival (OS) stratified by tumor stage with different chemotherapy status. A The K-M curve intersected at 12.91months. The chemotherapy group in stage I had superior early survival, but its survival probability was overtaken by the non-chemotherapy group after long-term follow-up. Overall survival (OS) analysis of Panels B–D demonstrates a significant protective effect of chemotherapy on overall survival in stages II-Ⅳ disease (all P < 0.001)
Stratified Kaplan-Meier survival analyses by metastasis status and primary tumor site (Figs. 10 and 11) consistently showed that chemotherapy exerted a significant protective effect against CCVD-related mortality, regardless of the presence of distant metastasis or primary tumor location (all log-rank P < 0.05).
Fig. 10.
The Kaplan-Meier survival curves in localized, regional and distant group. All the patients got benefits against CCVD
Fig. 11.
The Kaplan-Meier survival curves in different sites. All the patients got benefits against CCVD (log rank P < 0.001)
Fine-gray competing risks model
To avoid overestimation of CCVD-related mortality in patients who may die from cancer first, we treated cancer-specific death as a competing event. Over 5 years, the cumulative incidence of CCVD-related mortality remained consistently lower in the chemotherapy group than in the non-chemotherapy group (60-month cumulative incidence function [CIF]: 2.23%, 95% CI 2.12–2.38%vs. 6.20%, 95% CI 6.03–6.36%; P < 0.001) (Fig. 12). For cancer-specific mortality, the cumulative-incidence curves crossed at 18.6 months (Fig. 12); beyond this point, the chemotherapy group exhibited a higher cumulative incidence (60-month CIF 46.30%, 95% CI 45.9–46.8% vs. 35.2%, 95% CI 34.8–35.5%; P < 0.001).
Fig. 12.
Cumulative incidence curves for the outcome of CCVD-related mortality and cancer-specific mortality by chemotherapy status. Solid lines represent the CCVD-related mortality; dashed lines represent the cancer-specific mortality. Red lines represent the non-chemotherapy group.; blue lines represent the chemotherapy group. The Fine-Gray competing-risk model showed that the CCVD protective effect of chemotherapy was maintained throughout follow-up
Discussion
Using a population-based cohort of 136 095 middle-aged and elderly patients with primary CRC, this study demonstrates for the first time that chemotherapy is associated with a sustained, 25% reduction in CCVD-related mortality (SHR 0.75, 95% CI 0.71–0.79) after accounting for cancer-specific mortality as a competing event. This protective signal proved robust across virtually all strata of age, gender, race, AJCC stage and surgery condition, challenging the prevailing perception that chemotherapy inevitably increases cardiac risk.
Kenzik et al. initially linked chemotherapy to higher cardiovascular morbidity [13]. However, consistent with our study, a later cohort of 412 CRC patients [14] and subsequent validations [15, 16] documented fewer major adverse cardiocerebrovascular events among chemotherapy-treated individuals. The discrepancy with earlier investigations most likely stems from endpoint definition: we focused exclusively on fatal cardiocerebrovascular events, whereas the early work by Kenzik combined fatal and non-fatal outcomes, thereby diluting the cardioprotective signal.
Given that age and male sex are well-established risk factors for CRC [17], we stratified our analyses by both variables. Across both genders and across nearly all age groups within the middle-aged and elderly population (≥ 50 years), patients who did not receive chemotherapy consistently exhibited a higher risk of CCVD-related mortality than those who did, suggesting that chemotherapy attenuates cardiocerebrovascular death across a broad demographic spectrum of CRC patients.
CRC is intrinsically associated with an elevated risk of cardiocerebrovascular events [14–16], and population-based data indicate that higher tumor grades confer progressively greater odds of cardiocerebrovascular complications [18]. Although certain regimens, particularly bevacizumab- or regorafenib-based therapies used for stage IV disease have been implicated in cardiovascular toxicity [19–22], these comparisons were largely derived from healthy controls or normal-tissue studies. However, recent evidence supports that the cardiovascular protective effects of systemic anticancer therapy outweigh its treatment-related toxicities [23]. We performed stage-stratified analyses of CCVD-related mortality according to AJCC stage. Even among patients in AJCC Stage IV, who are most exposed to anti-VEGF agents, CCVD-related mortality remained lower in the chemotherapy group than that in the non-chemotherapy group, suggesting that the cardiocerebrovascular protective signal persists despite anti-VEGF exposure.
Our findings demonstrated that chemotherapy improved cardiocerebrovascular survival across all CRC stages and the overall cohort, but its effect on OS was stage‑ and time‑dependent (Figs. 2, 8 and 9). OS curves intersected at 25 months in the overall cohort and 12.9 months in stage I CRC, with chemotherapy providing early benefit but late inferiority. In contrast, stage II–IV patients displayed persistent, highly significant OS benefits (all P < 0.001), consistent with a systematic review from the Cancer Care Ontario Program [24]. These results suggest that chemotherapy’s long‑term toxicities may offset its oncological value in stage I CRC, while its antitumor effects prevail in advanced disease, leading to consistent cardiocerebrovascular and OS improvements. Our findings support the perception that staged risk-benefit assessment plays a critical role in optimizing CRC care [25].
Fig. 2.
Survival outcomes of colorectal cancer patients. Patients with a follow-up time exceeding five years were collected from SEER database. A overall survival curves, cross at 25 months B survival curves for CCVD associated mortality
In this large real-world middle-aged and elderly CRC cohort, chemotherapy was independently linked to reduced CCVD-related mortality (accounting for cancer-specific competing mortality), with robust protection across key subgroups including older and metastatic patients. These findings help alleviate excessive clinical concerns about chemotherapy-related CCVD mortality, highlight the need to move beyond a toxicity-centric view of chemotherapy’s cardiovascular effects, and warrant validation in future prospective multicenter studies to inform personalized cardio-oncology care for CRC patients.
Several complementary mechanisms may underlie the observed reduction in CCVD-related mortality associated with chemotherapy in CRC patients. First, enhanced cardiovascular risk management: Chemotherapy patients receive more frequent cardiovascular risk factor monitoring and optimized supportive care, which may indirectly reduce CCVD-related mortality. Charles Dolladille et al. proposed the hospital-based management of these patients may facilitate timely intervention for acute cardiocerebrovascular events [11]. Additionally, the shared risk factors between CRC and CCVD, particularly smoking and metabolic syndrome may contribute to this observed benefit [26]. Following CRC diagnosis, smoking cessation may reduce CCVD risk, while chemotherapy-induced weight loss may further attenuate atherosclerosis development [27, 28]. Second, tumor burden reduction. Chemotherapy alleviates CRC-driven chronic catabolism, hypoxia, and neurohormonal activation (all established CCVD risk factors), reducing malignancy-related cardiovascular damage. Certain chemotherapeutic agents may mitigate or reverse the vascular complications associated with colorectal cancer progression [29, 30]. Previous studies have demonstrated that among CRC patients with stage Ⅰ–Ⅲ, the cumulative incidence of new-onset cardiovascular disease and congestive heart failure (CHF) reaches as high as 57.4% and 54.5%, respectively, whereas these rates are only 22% and 18% in an age-matched control population [31]. In the context of the present study’s findings, we contend that the bidirectional relationship between CCVD and CRC warrants further investigation. Last, anti-inflammatory and antithrombotic effects: First-line CRC chemotherapies exert off-target anti-inflammatory effects, mitigating the systemic inflammation that drives atherosclerosis and thrombotic CCVD events. We propose that the protective effect of chemotherapy on cardiocerebrovascular health in elderly patients with CRC may be mediated through the following mechanism: Colorectal cancer-associated inflammation (e.g., elevated levels of IL-6 and TNF-α) can trigger vascular endothelial injury and promote atherosclerosis [31,32, 33]; chemotherapy, in turn, may reduce the risk of cardiovascular events by shrinking tumor volume and decreasing the release of proinflammatory cytokines. Emerging evidence suggests that certain chemotherapy agents can provide direct cardiocerebrovascular protection. Specifically, prior studies have shown some special agents preserves arterial integrity, and drugs such as oxazaphosphorines and pyrimidine antagonists are associated with reduced atherosclerosis incidence [11, 15, 34, 35]. Irinotecan’s metabolite SN-38 inhibits TLR4, thereby reducing inflammation linked to coronary artery disease progression [36, 37]. Anti-EGFR therapy improves renal hemodynamics and reduces atherosclerotic risk markers like total cholesterol and LDL [38, 39]. These mechanisms, which suppress inflammation and mitigate atherosclerosis, explain the observed cardiocerebrovascular benefits across all stages. However, due to the lack of relevant data in the SEER database, further validation of these mechanisms was not possible. We aim to address this research gap in future studies by incorporating such critical variables.
This study acknowledges several methodological limitations. The database constraints precluded precise identification of specific chemotherapy regimens and the timing of chemotherapy initiation, thereby limiting the ability to determine the exact pharmacological agents responsible for the observed effects. Furthermore, while cardiovascular morbidity represents a critical outcome in CRC survivors with improved survival rates, our analysis was restricted to mortality endpoints, excluding patients with non-fatal CCVD. Moreover, the absence of baseline CCVD status (e.g., stroke, coronary artery disease) and risk factor metrics (e.g., blood pressure, glycemic profiles) in the SEER database may introduce residual confounding. At the same time, the heterogeneous population composition limits the direct and wide spread of the research conclusion in the real world. Future investigations should integrate multimodal clinical data (e.g., serial cardiac imaging and dynamic biomarker monitoring) to develop causal inference models that better delineate treatment-associated cardiovascular risks.
Conclusion
In conclusion, our study has revealed that chemotherapy is a protective factor against CCVD- related mortality in middle-aged and elderly CRC patients. This challenges the conventional concern that chemotherapy primarily increases cardiovascular risk, providing crucial new evidence for this specific cancer population. They can potentially alleviate concerns about chemotherapy-induced CCVD risk in the context of CRC management and may offer new perspectives for clinical management and research.
Acknowledgements
The authors gratefully acknowledge the National Cancer Institute for providing open access to SEER program data. This research utilized SEER*Stat analytical tools (version 8.4.3) in full compliance with the SEER Data Use Agreement (https://seer.cancer.gov/datause.html).
Abbreviations
- CCVD
Cardiocerebrovascular disease
- CRC
Colorectal cancer
- SEER
Surveillance, Epidemiology, and End Results
- STROBE
Strengthening the Reporting of Observational Studies in Epidemiology
- ICD-10
International Classification of Diseases, Tenth Revision
- NOS
Not otherwise specified
- IQR
Interquartile range
- HR
Hazard Ratio
- CI
Confidence Interval
- OR
Odds ratio
Author contributions
Y.C., B.Z., G.W. and L.L. conceived and supervised the study. X.Z. and G.W. recruited data information. X.Z., G.W., X.C., Y.L. analyzed the data and visualized the results. Y.C., B.Z., X.C., Y.C. wrote the original draft. L.L. reviewed and edited the manuscript. All authors revised and approved the final manuscript.
Funding
This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.
Data availability
The datasets analyzed during the current study are available from the corresponding author on reasonable request.
Declarations
Ethics approval
This study is based on a public database with de-identified data and does not involve research protocol requiring approval by the relevant institutional review board or ethics committee.
Consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Yingna Chen, Bin Zhou and Guitao Wu have contributed equally to this study.
Contributor Information
Xinxin Cheng, Email: chengxx3@mail3.sysu.edu.cn.
Xiaowei Zhang, Email: zhangxw93@mail.sysu.edu.cn.
Ling Long, Email: longl3@mail.sysu.edu.cn.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets analyzed during the current study are available from the corresponding author on reasonable request.