What is new?
Key findings- •
This study provides validated comorbidity indices for cancer populations using administrative hospitalization data. Site-specific indices did not outperform a more general cancer index. The new indices included a more extensive list of conditions, and more up-to-date and site-specific weights. They outperformed the Charlson and National Cancer Institute (NCI) indices for all sites combined and colorectal cancer, and to a lesser extent for upper gastrointestinal cancers. For other sites, the new indices performed similarly to the Charlson index.
What this adds to what was known?- •
The C3 indices provide a valid alterative to the Charlson or NCI indices in cancer populations, although for many purposes any of these three measures of comorbidity will give similar results.
What is the implications and what should change now?- •
Consideration of comorbidity in studies of cancer population is more important than the measure used to describe it.
Patients diagnosed with cancer frequently have other chronic medical conditions. These concomitant conditions, or comorbidity, can affect how or when a patient is diagnosed with cancer, the treatment options available or offered, and a patients' ultimate prognosis [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13]. At an individual level, a clinician can assess the presence and impact of comorbidity in a patient diagnosed with cancer. However, at the population level, assessing comorbidity is much more difficult. The severity of a patient's comorbidity depends on the number, pattern, and severity of conditions present, and the likely impact may vary depending on the specific cancer diagnosed [4], [11], [14], [15], [16], [17]. Despite these difficulties, measuring comorbidity at the population level is important, as it provides researchers, policy makers, and health service planners with the necessary tools to allow them to stratify patients into groups according to risk in the same way they do for demographic and disease factors such as age and tumor stage [16], [18].
There have been many attempts to measure comorbidity in cancer patient populations [4]. The most commonly cited approach is that of Charlson et al. [19]. These investigators identified all comorbid conditions from the medical records of a relatively small cohort of 559 general medical patients admitted to a single hospital. They assessed the impact of each condition on 1-year mortality, and excluded any with a relative risk of less than 1.2. They developed a weighted index, with the weights being equivalent to the (rounded) adjusted relative risks for mortality for each condition, with a maximum weight of six. Subsequently, the Charlson index has been validated on data from administrative records [20], [21], [22], [23], [24], [25], [26], [27]. The Charlson index has been used as the basis for other comorbidity indices, most notably the National Cancer Institute (NCI) comorbidity index, which uses the same conditions, but uses the regression coefficients (ie, the log of the relative risk rather than the relative risk itself) of the association of each condition with 1-year mortality to assign weights [28]. These latter investigators also argued for the importance of site-specific weights in the development of comorbidity indices for use with cancer patients.
Despite this extensive work, there has been little consideration of whether the conditions that Charlson and colleagues identified in their general medical cohort nearly 30 years ago are those that are most important for cancer patients today. The Charlson index includes some conditions that may not have an impact on survival among patients with cancer because of substantial improvements in management (eg, peptic ulcer disease), and it excludes some that do have such an impact (eg, noncerebrovascular neurological conditions and major psychiatric conditions) [19].
Comorbidity is a composite construct defined by the presence or absence of concomitant conditions. As such, theoretically, comorbidity will be best measured when as many relevant items are included as possible, and it is likely that the weighting of individual conditions will be less important than their inclusion [29]. However, a “reduced” comorbidity index involving a smaller number of conditions may be desirable for practical reasons.
We aimed to develop administrative data–based indices, which address some of the issues identified in previous work, to assess whether they performed better than other well-established comorbidity indices, particularly the Charlson and NCI indices. We wanted to ensure that all conditions that may be important in defining comorbidity in cancer patient populations were included. We also wanted to account for the possibility that the importance of these conditions may vary depending on the primary site of cancer, either because of different underlying prevalence rates of specific conditions or because of differential impact of individual conditions on particular cancer sites.
We used data from more than 14,000 patients diagnosed with one of the nine cancers (colon, rectal, breast, ovarian, endometrial, stomach, liver, bladder, or kidney) identified from the New Zealand cancer registry, with data identified from hospitalizations for the 5 years before diagnosis on 50 potentially concomitant conditions. We combined these into site-specific and non-site–specific indices and evaluated the performance of these against the Charlson and NCI (site-specific) indices.