This study estimated the absolute risk of colorectal cancer (CRC) specific and other-cause mortality using data from the population-based South Australian Cancer Registry. The impact of competing risks on the absolute and relative risks of mortality in cases with and without comorbidity was also investigated. The study included 7115 staged, primary CRC cases diagnosed between 2003 and 2012 with at least one year of follow-up. Comorbidities were classified according to Charlson, Elixhauser and C3 comorbidity indices, using hospital inpatient diagnoses occurring five years before CRC diagnosis. To estimate the differences in measures of association, the subdistribution hazard ratios (sHR) for the effect of comorbidity on mortality from the Fine and Gray model were compared to the cause-specific hazards (HR) from Cox regression model. CRC was most commonly diagnosed in people aged ≧ 70 years. In cases without comorbidity, the 10-year cumulative probability of CRC and other cause mortality were 37.1% and 17.2% respectively. In cases with Charlson comorbidity scores ≥2, the 10-year cumulative probability of CRC-specific and other cause mortality was 45.5% and 32.2%, respectively. Comorbidity was associated with increased CRC-specific and other cause mortality and the effect differed only marginally based on comorbidity index used.
BackgroundComorbidity is known to increase risk of death in cancer patients, both Aboriginal and non-Aboriginal. The means of measuring comorbidity to assess risk of death has not been studied in any depth in Aboriginal patients in Australia. In this study, conventional and customized comorbidity indices were used to investigate effects of comorbidity on cancer survival by Aboriginal status and to determine whether comorbidity explains survival disparities.MethodsA retrospective cohort study was undertaken using linked population-based South Australian Cancer Registry and hospital inpatient data for 777 Aboriginal people diagnosed with primary cancer between 1990 and 2010 and 777 randomly selected non-Aboriginal controls matched by sex, birth year, diagnosis year and tumour type. A customised comorbidity index was developed by examining associations of comorbid conditions with 1-year all-cause mortality within the Aboriginal and non-Aboriginal patient groups separately using Cox proportional hazard model, adjusting for age, stage, sex and primary site. The adjusted hazard ratios for comorbid conditions were used as weights for these conditions in index development. The comorbidity index score for combined analyses was the sum of the weights across the comorbid conditions for each case from the two groups.ResultsThe two most prevalent comorbidities in the Aboriginal cohort were “uncomplicated” hypertension (13.5%) and diabetes without complications (10.8%), yet in non-Aboriginal people, the comorbidities were “uncomplicated” hypertension (7.1%) and chronic obstructive pulmonary disease (4.4%). Higher comorbidity scores were associated with higher all-cause and cancer-specific mortality. The new index showed minor improvements in predictive ability and model fit when compared with three common generic comparison indices. After accounting for the competing risk of other deaths, stage at diagnosis, socioeconomic status, area remoteness and comorbidity, the increased risk of cancer death in Aboriginal people remained.ConclusionsOur new customised index performed at least as well, although not markedly better than the generic indices. We conclude that in broad terms, the generic indices are reasonably effective for adjusting for comorbidity when comparing survival outcomes by Aboriginal status. Irrespective of the index used, comorbidity has a negative impact on cancer-specific survival, but this does not fully explain the lower survival in Aboriginal patients.
Rationale and objectivesIn epidemiological research, it is essential to account for the confounding effects of factors such as age, stage, and comorbidity for accurate prediction of cancer outcomes. There are several internationally developed and commonly used comorbidity indices. However, none are regarded as the gold‐standard method. This study will assess and compare the predictive validity of established indices for use in a South Australian (SA) colorectal cancer (CRC) population against a local index. Furthermore, the prognostic influence of comorbidity on survival is investigated.MethodsA population‐based study of patients diagnosed with CRC from 2003 to 2012 and linked to in‐hospital data to retrieve comorbidity information was conducted. The predictive performance of established indices, Charlson comorbidity index (CCI), National Cancer Institute comorbidity index (NCI), Elixhauser comorbidity index (ECI), and C3 index was evaluated using the Fine and Gray competing risk regression and reported using measures of calibration and discrimination, area under the curve (AUC), and Brier score. Furthermore, to identify the optimal index, a local CRC comorbidity index (CRCCI) was also developed and its performance compared with the established indices.ResultsComorbidity models adjusted for age, sex, and stage showed that all indices were good predictors of mortality as measured by the AUC (CCI: 0.738, NCI: 0.742, ECI: 0.733, C3: 0.739). CRCCI had similar mortality prediction as established indices (CRCCI: 0.747). There was a significant increase in cumulative risk of noncancer and CRC‐specific mortality with increase in comorbidity scores. The two most prevalent comorbidities were hypertension and diabetes.ConclusionsThe existing indices are still valid for adjusting for comorbidity and accurately predicting mortality in an SA CRC population. Internationally developed indices are preferred when policymakers and researchers wish to compare local study results with those of studies (national and international) that have used these indices. Comorbidity is a predictor of mortality and should be considered when assessing CRC survival.
Objective. To explore variations in patterns of care over three decades for a subgroup of rectal cancer patients in South Australia according to sociodemographic characteristics. Methods. This study evaluated three decades of retrospective data from the South Australian Clinical Cancer Registry. A total of 4,131 patients diagnosed with rectal cancer between 1982 and 2015 and treated in South Australian public hospitals were included. Study outcomes were age at diagnosis, area of primary residence, cancer stage, and primary treatment (surgery, chemotherapy, or radiotherapy). Results. There was a significantly lower likelihood of conventional therapy for the elderly. Adjusted odds of receiving surgery or radiotherapy decreased by 70% and those of receiving chemotherapy by 90% in the 80+ age group, compared to the 50–59 age group. No significant variation was detected according to area-level socioeconomic status or remoteness. Conclusion. Socioeconomic factors showed little impact on the receipt of therapies for rectal cancer patients in South Australia. Variation in treatment by age, irrespective of disease stage or period of diagnosis, requires further investigation.
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