A Refined Comorbidity Measurement Algorithm for Claims-Based Studies of Breast, Prostate, Colorectal, and Lung Cancer Patients

Purpose

We evaluated (i) how combining comorbid conditions identified from Medicare inpatient or physician claims into a single comorbidity index compared with three other comorbidity indices and (ii) the need for comorbid condition weights that are specific to different cancer sites.

Methods

This observational study used the SEER-Medicare linked database, from which four cohorts of cancer patients were derived: breast (n = 26,377), prostate (n = 53,503), colorectal (n = 26,460), and lung (n = 33,975). We calculated two established (Charlson; NCI) and two new (NCI Combined; Uniform Weights) comorbidity indices, and used Cox proportional hazards models to assess their predictive ability. We also used a pooled dataset to examine the inclusion of cancer site-specific condition weights.

Results

The four comorbidity indices all significantly predicted mortality, but the NCI and new NCI Combined indices showed the greatest contribution to model fit. The new NCI Combined index is simpler to use and statistically more efficient than the NCI index. Modeling further demonstrated the utility of cancer site-specific weights.

Conclusions

Our results support the need for cancer site-specific comorbidity measures that employ empirically-derived condition weights. The new NCI Combined index is a refined, easier to implement comorbidity measurement algorithm appropriate for investigators using administrative claims databases to study four commonly-occurring cancers.

Introduction

The Charlson index (1) is a widely used measure of comorbidity, particularly among investigators conducting epidemiologic and outcomes research studies using administrative claims (2). The measure comprises 19 comorbid conditions, each assigned a weight according to its potential for influencing 1-year mortality. The index is the sum of the weighted comorbidities and accounts for the number and seriousness of the conditions. Originally developed to predict mortality among hospitalized patients, the index has been used to predict other patient outcomes, including treatment and costs. It has been adapted for use with administrative claims by mapping International Classification of Diseases, revision 9 (ICD-9) diagnostic and procedure codes to the conditions identified by Charlson as prognostically important 3, 4.

Since the publication of Charlson's original study, the proportion of medical care provided in the outpatient setting has increased considerably (5). Earlier studies that have used Medicare data generally have relied on codes obtained from inpatient claims to calculate a Charlson index (2). These analyses tend to classify a large proportion of cohort members as having no comorbid conditions simply because only a small proportion of the population is hospitalized in a given year.

An earlier study of comorbidity among Medicare beneficiaries with cancer used Medicare physician (Part B) claims and inpatient data to construct an adaptation of the Charlson index (6). This approach, hereafter referred to as the National Cancer Institute (NCI) index, involved calculation of two separate comorbidity indices from inpatient and physician claims. The analysis demonstrated improved prediction of noncancer mortality and treatment choice with the inclusion of physician claims for breast and prostate cancer patients. The authors obtained comorbid condition weights that differed from Charlson's (1) and showed that condition weights differed by cancer site. Although the NCI index (6) has been used in several claims-based analyses of cancer treatment and outcomes 7, 8, 9, 10, 11, 12, 13, 14, it may be somewhat cumbersome in practice because two separate comorbidity scores must be calculated and interpreted. Moreover, weights were derived only for breast and prostate cancer patients. Other studies 15, 16, 17 have also demonstrated the need for comorbidity indices tailored to the specific population of interest.

In this report, we describe a new analysis to improve the measurement of comorbidity in cancer patients using administrative claims databases. Our objectives are to evaluate (i) how combining comorbid conditions identified from Medicare inpatient or physician claims into a single comorbidity index, unlike the two separate indices used in the NCI index (6), compares with three other comorbidity indices and (ii) the need for comorbid condition weights specific to four different cancer sites. We chose to examine large cohorts of breast, prostate, colorectal, and lung cancer patients in our study because—excluding nonmelanoma skin cancer—these are the four most commonly diagnosed cancers in the United States.