Multimorbidity and short-term overall mortality among colorectal cancer patients in Spain: A population-based cohort...

Numerous studies have analysed the effect of comorbidity on cancer outcomes, but evidence on the association between multimorbidity and short-term mortality among colorectal cancer patients is limited. We aimed to assess this association and the most frequent patterns of multimorbidity associated with a higher short-term mortality risk among colorectal cancer patients in Spain.

Data were obtained from two Spanish population-based cancer registries and electronic health records. We estimated the unadjusted cumulative incidence of death by comorbidity status at 6 months and 1 year. We used a flexible parametric model to derive the excess mortality hazard ratios (HRs) for multimorbidity after adjusting for sex, age at diagnosis, cancer stage and treatment. We estimated the adjusted cumulative incidence of death by comorbidity status and identified multimorbidity patterns.

Among the study participants, 1,048 cases were diagnosed with cancers of the colon and rectum, 2 cases with cancer of the anus with overlapping sites of the rectum and 11 cases with anal adenocarcinomas but treated as colorectal cancer patients. Among 1,061 colorectal cancer patients, 171 (16.2%) died before 6 months, 246 (23.3%) died before the 1-year follow-up, and 324 (30.5%) had multimorbidity. Patients with multimorbidity had two times higher mortality risk than those without comorbidities at 6 months (adjusted HR: 2.04; 95% confidence interval [CI]: 1.30-3.20, p = 0.002). The most frequent multimorbidity pattern was congestive heart failure + diabetes. However, patients with rheumatologic disease + diabetes had two times higher 1-year mortality risk than those without comorbidities (HR: 2.23; 95% CI: 1.23-4.07, p = 0.008).

Multimorbidity was a strong independent predictor of short-term mortality at 6 months and 1 year among the colorectal cancer patients in Spain. The identified multimorbidity pattern was consistent. Our findings might help identify patients at a higher risk for poor cancer and treatment outcomes.