The impact of comorbidity on outcomes.

Patients often have other diseases, illnesses, or conditions in addition to the disease under study. These other medical conditions are referred to as comorbidity. Comorbidity can impact on diagnosis, prognosis, and selection of therapy. There are a variety of instruments available to measure the type and severity of comorbid ailments. Comorbidity information can be obtained from direct discussions with the patient, a review of the medical record, or from electronic databases that contain billing information. The method of comorbidity assessment can impact on the interpretation of results. Accurate comorbid information will improve the conduct of and generalizability of clinical trials, evaluation of outcomes from observational research, population-based epidemiological studies, and patient-physician communication.

Differential prognostic impact of comorbidity.

PURPOSE: Cancer patients with concurrent comorbid conditions have worse outcomes than patients with no comorbidities. We hypothesized that the prognostic impact of comorbidities would be greatest for patients with cancers associated with a long natural history and least in patients with aggressive cancers. PATIENTS AND METHODS: Using the Barnes-Jewish Hospital Oncology Data Services cancer registry, we grouped 11,558 patients with breast, lung, colon, or prostate cancer by morphologic stage at diagnosis and then determined the 1-year overall survival rate for each group. Overall, severity of comorbidity was assessed from chart review and classified into one of four groups: none, mild, moderate, or severe. The relative prognostic impact of comorbidity was measured by the hazard ratio and adjusted for the prognostic impact of age, race, and sex. RESULTS: One-year overall survival rate ranged from 20% for 1,005 patients with distant spread of lung cancer to 98% for 3,325 patients with localized prostate cancer. Adjusted hazard ratio of moderate/severe comorbidity (relative to none/mild) ranged from 1.04 to 4.48. The correlation between overall survival rate and severity of comorbidity was statistically significant (r2 = 0.56; P < .001). The proportion of variance in outcome explained by comorbidity ranged from less than 1% to almost 9%, depending on tumor site and stage. CONCLUSION: Concurrent comorbidities had the greatest prognostic impact among groups with the highest survival rate and the least impact in groups with the lowest survival rate. These findings can be used to help determine the role comorbidity information should play in studies of cancer outcomes.

Prognostic importance of comorbidity in a hospital-based cancer registry.

CONTEXT: Patients with cancer often have other medical ailments, referred to as comorbidity. Comorbidity may impact treatment decision-making, prognosis, and quality of care assessment. OBJECTIVE: To assess whether comorbidity information can provide important prognostic information in a hospital-based cancer registry. DESIGN, SETTING, AND PARTICIPANTS: An observational prospective cohort study using comorbidity data collected by trained hospital-based cancer registrars. Comorbidity was obtained through medical record review using the Adult Comorbidity Evaluation 27, a validated chart-based comorbidity instrument. A total of 17,712 patients receiving care between January 1, 1995, and January 31, 2001, for the primary diagnosis of new cancer of the prostate, lung (nonsmall cell), breast, digestive system, gynecological, urinary system, or head and neck were included. MAIN OUTCOME MEASURE: Duration in months of overall survival. RESULTS: A total of 19,268 patients were included in the study; median duration of follow-up was 31 months. Of these patients, 1556 (8.0%) were excluded due to missing or unknown data. Severity of comorbidity strongly influenced survival in a dose-dependent fashion and the impact of comorbidity was independent of cancer stage. Compared with patients without comorbidity, the adjusted hazard ratio associated with mild comorbidity was 1.21 (95% confidence interval [CI], 1.13-1.30), moderate comorbidity was 1.86 (95% CI, 1.73-2.00), and severe comorbidity was 2.56 (95% CI, 2.35-2.81). Adjusted Kaplan-Meier survival curves revealed that at any point in time the patients with more severe levels of comorbidity had worse survival (partial chi2(3) due to comorbidity, 523.54; P<.001). Model discrimination ranged from 0.71 for head and neck to 0.86 for prostate cancers. CONCLUSIONS: Comorbidity is an important independent prognostic factor for patients with cancer. The inclusion of comorbidity in hospital-based cancer registries will increase the value and use of observational research.

Comparison of comorbidity indices for patients with head and neck cancer.

BACKGROUND: Comorbidity is an important prognostic factor for elderly patients with head and neck cancer. Investigators are faced with the dilemma of selecting the appropriate comorbidity instrument for outcomes research in cancer. The goal of this study was to compare 2 general comorbidity indices with 2 disease-specific indices. METHODS: The Surveillance, Epidemiology, and End Results (SEER)-Medicare-linked database was used to identify 15,493 patients with incident squamous cell carcinomas of the oral cavity, pharynx, and larynx first diagnosed between December 1983 and December 1994. Comorbid ailments were identified through the use of the International Classification of Diseases, 9th edition codes in the Medicare inpatient and outpatient claims for 7131 patients. The overall severity of comorbidity was classified according to 2 general comorbidity indices: the Charlson Comorbidity Index and the Klabunde Index, and 2 disease-specific indices: the Washington University Head and Neck Index and the Head and Neck Cancer Index. Overall survival was the primary end point. Cox proportional hazards analysis was used to assess the performance and discrimination of the comorbidity indices. RESULTS: For each of the 4 comorbidity indices, there was a weak trend of worse survival with higher levels of comorbidity. The 2 general indices performed as well as the 2 disease-specific indices and no instrument clearly performed better than the others. CONCLUSION: Both the general and disease-specific comorbidity indices provided important prognostic information. The disease-specific indices did not perform better than the general indices. In this claims-based analysis, there was no apparent advantage to using a disease-specific index when attempting to predict overall survival.