ESTIMATING THE BURDEN OF MALIGNANT HAEMATOPOIETIC CANCERS IN NORDIC COUNTRIES- A PREDICTIVE ANALYSIS USING TIME SERIES ANALYSIS METHODS

Author(s)

Sharma A1, Pandey S2, Siddiqui MK1, Vanderpuye-Orgle J3, Singla D4
1PAREXEL International, Mohali, India, 2PAREXEL International, Lucknow, UP, India, 3PAREXEL, Glendale, CA, USA, 4Parexel International, Benglore, India

OBJECTIVES: Overall prevalence of Malignant Haematopoietic Cancers(MHC) have increased exponentially over the years i.e. 104.88/100,000 in 1980 to 448.72/100,000 in 2016 and the number of cases diagnosed each year has also been trending upwards. While these trends may have implications for health system costs, the burden of MHC is yet to be fully assessed. Nordic registry data were examined to estimate the incidence of MHC and to predict the trends in these new cases of MHC in order to assess the future burden of the disease in the Nordic region.

METHODS: MHC incidence data from 1960 to 2016 were obtained from NORDCAN. Assumptions of stationarity and auto-correlation were checked using Augmented Dickey-Fuller (ADF) test and auto-correlation function (ACF), respectively. MHC incidence were forecast through to 2025 using ARIMA models. Data were segmented between 1960-2005 for estimation segment and 2006-2016 for validation. The model selection was based on the Akaike information criteria (AIC), and the verification was based on examining the residual plots. Data analysis were conducted using R(v3.6.0).

RESULTS: The incidence of MHC in Nordic countries is expected to rise from 11165 in 2015 to 16157 in 2025. Between 2015 and 2025, it is expected that the incidence rate in males will increase by 3.2% (60.29/100,000 to 62.83/100,000) and in females by 9.43%(47.2/100,000 to 51.66/100,000). ). The number of new cases in males is expected to increase from 6289 in 2015 to 8887 in 2025 (41.3% increase) and similarly, in females from 4877 in 2015 to 7270 in 2025 (49.1% increase).

CONCLUSIONS: This study predicts an increase in the incidence of MHC in both males and females in the Nordic region by 2025. The application of this analysis could be an important resource for planning and evaluating cancer-control programs.

Conference/Value in Health Info

2019-11, ISPOR Europe 2019, Copenhagen, Denmark

Code

PCN268

Topic

Clinical Outcomes, Economic Evaluation, Epidemiology & Public Health, Methodological & Statistical Research

Topic Subcategory

Artificial Intelligence, Machine Learning, Predictive Analytics, Comparative Effectiveness or Efficacy

Disease

Oncology

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