Risk of cardiovascular disease in cancer survivors: A cohort study of 446,384 New Zealand primary care patients.

BACKGROUND: Given advances in the management of cancer, it is increasingly important for clinicians to appropriately manage the risk of cardiovascular disease (CVD) among cancer survivors. It is unclear whether CVD risk is increased among cancer survivors overall, and there is inconsistency in evidence to date about CVD incidence and mortality by cancer type. METHODS: Patients aged 30-74 years entered an open cohort study at the time of first CVD risk assessment, between 2004 and 2018, in primary care in New Zealand. Patients with established CVD or cancer within 2 years prior to study entry were excluded. Cancer diagnosis (1995-2016) was determined from a national cancer registry. Cause-specific hazard models were used to examine the association between history of cancer and two outcomes: (1) CVD-related hospitalization and/or death and (2) CVD death. RESULTS: The study included 446,384 patients, of whom 14,263 (3.2%) were cancer survivors. Risk of CVD hospitalization and/or death was increased among cancer survivors compared with patients without cancer at cohort entry (multivariable-adjusted hazard ratio, mHR, 1.11, 95% CI 1.05-1.18), more so for CVD death (1.31, 1.14-1.52). Risk of CVD hospitalization and/or death was increased in patients with myeloma (2.66, 1.60-4.42), lung cancer (2.19, 1.48-3.24) and non-Hodgkin lymphoma (1.90, 1.42-2.54), but not for some cancers (e.g., colorectal, 0.87, 0.71-1.06). Risk of CVD death was increased in several cancer types including melanoma (1.73, 1.25-2.38) and breast cancer (1.56, 1.16-2.11). CONCLUSION: CVD risk management needs to be prioritized among cancer survivors overall, and particularly in those with myeloma, lung cancer and non-Hodgkin lymphoma given consistent evidence of increased risk.

Performance of cardiovascular disease risk prediction equations in more than 14 000 survivors of cancer in New Zealand primary care: a validation study.

BACKGROUND: People with cancer have an increased risk of cardiovascular disease. Risk prediction equations developed in New Zealand accurately predict 5-year cardiovascular disease risk in a general primary care population in the country. We assessed the performance of these equations for survivors of cancer in New Zealand. METHODS: For this validation study, patients aged 30-74 years from the PREDICT open cohort study, which was used to develop the New Zealand cardiovascular disease risk prediction equations, were included in the analysis if they had a primary diagnosis of invasive cancer at least 2 years before the date of the first cardiovascular disease risk assessment. The risk prediction equations are sex-specific and include the following predictors: age, ethnicity, socioeconomic deprivation index, family history of cardiovascular disease, smoking status, history of atrial fibrillation and diabetes, systolic blood pressure, total cholesterol to HDL cholesterol ratio, and preventive pharmacotherapy (blood-pressure-lowering, lipid-lowering, and antithrombotic drugs). Calibration was assessed by comparing the mean predicted 5-year cardiovascular disease risk, estimated using the risk prediction equations, with the observed risk across deciles of risk, for men and women, and according to the three clinical 5-year cardiovascular disease risk groups in New Zealand guidelines (<5%, 5% to <15%, and ≥15%). Discrimination was assessed by Harrell's C statistic. FINDINGS: 14 263 patients were included in the study. The mean age was 61 years (SD 9) for men and 60 years (SD 8) for women, with a median follow-up of 5·8 years for men and 5·7 years for women. The observed cardiovascular disease risk was underpredicted by a maximum of 2·5% in male and 3·2% in female decile groups. When patients were grouped according to clinical risk groups, observed cardiovascular disease risk was underpredicted by less than 2% in the lower risk groups and overpredicted by 2·2% for men and 3·3% for women in the highest risk group. Harrell's C statistics were 0·67 (SE 0·01) for men and 0·73 (0·01) for women. INTERPRETATION: The New Zealand cardiovascular disease risk prediction equations reasonably predicted the observed 5-year cardiovascular disease risk in survivors of cancer in the country, in whom risk prediction was considered clinically appropriate. Prediction could be improved by adding cancer-specific variables and considering competing risks. Our findings suggest that the equations are reasonable clinical tools for use in survivors of cancer in New Zealand. FUNDING: Auckland Medical Research Foundation, Health Research Council of New Zealand.

Development and validation of a new predictive model for breast cancer survival in New Zealand and comparison to the Nottingham prognostic index.

BACKGROUND: The only available predictive models for the outcome of breast cancer patients in New Zealand (NZ) are based on data in other countries. We aimed to develop and validate a predictive model using NZ data for this population, and compare its performance to a widely used overseas model, the Nottingham Prognostic Index (NPI). METHODS: We developed a model to predict 10-year breast cancer-specific survival, using data collected prospectively in the largest population-based regional breast cancer registry in NZ (Auckland, 9182 patients), and assessed its performance in this data set (internal validation) and in an independent NZ population-based series of 2625 patients in Waikato (external validation). The data included all women with primary invasive breast cancer diagnosed from 1 June 2000 to 30 June 2014, with follow up to death or Dec 31, 2014. We used multivariate Cox proportional hazards regression to assess predictors and to calculate predicted 10-year breast cancer mortality, and therefore survival, probability for each patient. We assessed observed survival by the Kaplan Meier method. We assessed discrimination by the C statistic, and calibration by comparing predicted and observed survival rates for patients in 10 groups ordered by predicted 10-year survival. We compared this NZ model with the Nottingham Prognostic Index (NPI) in this validation data set. RESULTS: Discrimination was good: C statistics were 0.84 for internal validity and 0.83 for an independent external validity. For calibration, for both internal and external validity the predicted 10-year survival probabilities in all groups of patients, ordered by predicted survival, were within the 95% confidence intervals (CI) of the observed Kaplan-Meier survival probabilities. The NZ model showed good discrimination even within the prognostic groups defined by the NPI. CONCLUSIONS: These results for the New Zealand model show good internal and external validity, transportability, and potential clinical value of the model, and its clear superiority over the NPI. Further research is needed to assess other potential predictors, to assess the model's performance in specific subgroups of patients, and to compare it to other models, which have been developed in other countries and have not yet been tested in NZ.