br Discussion br This study was
This study was the first study to analyze the association of comorbid-ities with OS, toxicity and unplanned hospitalizations in older adults with colorectal cancer by using heat maps. Our previous heat map study showed that high TRS was a predictor of poor survival in a general group of older adults with cancer, and that heat maps showed interest-ing insights into the prevalence and associations of comorbidities affect-ing the OS of these patients . In a parallel study in patients with lung adenocarcinoma, the TRS was also associated with OS . In the pres-ent study, TRS ≥2 showed a similar association with OS in patients with rectal cancer but not in patients with colon cancer or the overall cohort. Further studies in individual cancer types will be needed before clear
Univariate (A) and multivariate (B) Cox regression analysis for OS of patients with rectal cancer.
(ref = Well/Moderate)
Prior Operation (ref = No)
Age at Diagnosis, per 5 years old
CIRS-G severity index
HEMATOPOIETIC (ref = 0)
GENITOURINARY (ref = 0)
(ref = Well/Moderate)
Total risk score ≥ 2
conclusions can be reached as to the robustness of the TRS to predict survival.
On further analysis along the lines of CIRS-G categories and summary scores, unlike in our original study, no individual categories of comor-bidities were associated with OS. The number of CIRS-G grade 4 diseases was associated with OS in both the overall cohort and the subgroup of patients with colon cancer in univariate analysis, although in only the latter did it ALLN remain independently associated in the multivariate analy-sis. Therefore, the overall pattern of association of comorbidity with OS is less clear in this study than it was in our two other cohorts [20,21].
Several studies showed an association of comorbidity with mortality or survival in colorectal cancer [7–9].The Danish older adults population-based comorbidity study showed that comorbidity was associated with increased overall mortality, but not cancer-specific mortality. Interest-ingly enough, their scatter plot analysis shows heterogeneous associa-tion of individual diseases with mortality, divergent from their CCI weight . In another Danish population-based cohort study, comorbid-ity was common in the patients with colorectal cancer and carried poorer prognosis in both cancer subtypes . In a Danish single center retro-spective study, comorbidity predicted survival in patients with colon cancer, but not in patients with rectal cancer, a result inverse from ours . One study found that treatment and comorbidity interacted among late-stage or patients with metastatic colorectal cancer, with e.g. cetuximab treated patients with comorbidities faring better than those without ..Some of the variability may be explained by differ-ences in the definition of comorbidity (CCI versus expansion based on
Fig. 4. Comorbidity heat map for overall survival in patients with rectal cancer.
CIRS-G grading), as well as to the accounting for other variables such as ECOG PS, grade of disease, or treatment types. It would be interesting to test the risk factors identified in our studies, such as grade 4 comorbid-ity or the TRS in some of the cohorts mentioned above.
Contrary to our expectations, mapping comorbidity in more detail did not identify subsets of diseases associated with toxicity or unplanned hospitalizations. Our group has been testing the association of CIRS-G rated comorbidities with chemotherapy toxicity in several trials now, and the results have been overall negative: other elements seem more closely associated with the occurrence or recurrence of severe toxicity
[24,27,28]. It is interesting to note that overall comorbidity measured in various ways was not an independent predictive factor in the two studies that formally constructed and validated predictive indexes for the risk of chemotherapy toxicity in older patients [28,29]. There is less literature on the association of comorbidity with unplanned hospitaliza-tions in patients with cancer. Several hypotheses can be made about this lack of independent association of comorbidity with these outcomes. One may be that a lumping effect still blurs the recognition of the impact of specific comorbidities. For example, the CIRS-G classifies together dia-betes and hypothyroidism in the endocrine system (albeit with different r> Fig. 5. Overall survival by TRS risk group in patients with rectal cancer.