Is the incidence of breast cancer increasing? Using the NCDB and autoregressive integrated moving average models (ARIMA) to forecast breast cancer to 2030.

Abstract

e13612 Background: The observed increase in the incidence rate of BC has been described due, in part, to higher, effective public health campaigns for screening, higher sensitivity among diagnostic testing modalities as well as an aging population. While the mortality rate associated with breast cancer has reported to fall by 1.8% every year since 2007, the disease burden itself has continued to grow and increased breast cancer rates will contribute to the strain already experienced within the United States healthcare system infrastructure. Therefore, the authors sought to use a large, national registry to develop a time series model that might help forecast the approximate breast cancer incidence rate, to the year 2030, as captured by the National Cancer Database (NCDB). Methods: In this time series forecast, autoregressive integrated moving average models (ARIMA) were constructed based on 2004-2016 historic breast cancer incidence rates, as reported by the NCDB. Multiple models were generated, using differing autoregressive parameters, and the most predictive model was chosen using the lowest Bayesian Information Criteria (BIC), and mean absolute percentage error (MAPE). Similar methodology has already been published to predict prostate cancer incidence. The best fit model was applied to forecast annual incidence in the NCDB to the year 2030. Statistics were performed using modeling systems in SPSS, version 26. Results: For this model, 12 years of NCDB breast cancer diagnoses were used, which included n = 1,924,425 cases, overall. Using ARIMA modeling, a best fit, stationary average was identified with autoregressive and difference terms of 1 (ARIMA (1,1,0), coefficient = 0.598; P = 0.028). Of the multiple models tested the model with the lowest BIC was chosen, with a MAPE of 4.71%. The best fit model forecasted n = 325,048 new breast cancer diagnoses to be captured annually by the NCDB, by 2030. Conclusions: In this analysis, the annual breast cancer incidence within the NCDB is predicted to increase by 21%, by 2030. This forecast, while slightly lower than previously reported by the National Cancer Institute, utilizes more recent historical data that reflects a period of leveling-off in disease incidence, during 2014-2016, as reported to the NCDB. This innovative model can be utilized to proactively plan public health strategies and allocate appropriate resources focused on reducing the burden of cancer.