Francesco Piva1, Francesca Tartari2, Matteo Giulietti1, Marco Maria Aiello3, Liang Cheng4, Antonio Lopez-Beltran5, Roberta Mazzucchelli6, Alessia Cimadamore6, Roy Cerqueti7,8, Nicola Battelli9, Rodolfo Montironi6, Matteo Santoni9. 1. Department of Specialistic Clinical & Odontostomatological Sciences, Polytechnic University of Marche, 60126, Ancona, Italy. 2. Department of Economics & Law, University of Macerata, via Crescimbeni, 20, 62100, Macerata, Italy. 3. Oncology Unit, Policlinico Hospital, 95123, Catania, Italy. 4. Department of Pathology & Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA. 5. Department of Surgery, Cordoba University Medical School, 14071, Cordoba, Spain. 6. Section of Pathological Anatomy, Polytechnic University of the Marche Region, School of Medicine, United Hospitals, 60126, Ancona, Italy. 7. Department of Social & Economic Sciences, Sapienza University of Rome, Piazzale Aldo Moro, 5 - I-00185, Rome, Italy. 8. School of Business, London South Bank University, London, SE1 0AA, UK. 9. Oncology Unit, Macerata Hospital, 62012, Macerata, Italy.
Abstract
Aims: To capture the complex relationships between risk factors and cancer incidences in the US and predict future cancer burden. Materials & methods: Two artificial neural network (ANN) algorithms were adopted: a multilayer feed-forward network (MLFFNN) and a nonlinear autoregressive network with eXogenous inputs (NARX). Data on the incidence of the four most common tumors (breast, colorectal, lung and prostate) from 1992 to 2016 (available from National Cancer Institute online datasets) were used for training and validation, and data until 2050 were predicted. Results: The rapid decreasing trend of prostate cancer incidence started in 2010 will continue until 2018-2019; it will then slow down and reach a plateau after 2050, with several differences among ethnicities. The incidence of breast cancer will reach a plateau in 2030, whereas colorectal cancer incidence will reach a minimum value of 35 per 100,000 in 2030. As for lung cancer, the incidence will decrease from 50 per 100,000 (2017) to 31 per 100,000 in 2030 and 26 per 100,000 in 2050. Conclusion: This up-to-date prediction of cancer burden in the US could be a crucial resource for planning and evaluation of cancer-control programs.
Aims: To capture the complex relationships between risk factors and cancer incidences in the US and predict future cancer burden. Materials & methods: Two artificial neural network (ANN) algorithms were adopted: a multilayer feed-forward network (MLFFNN) and a nonlinear autoregressive network with eXogenous inputs (NARX). Data on the incidence of the four most common tumors (breast, colorectal, lung and prostate) from 1992 to 2016 (available from National Cancer Institute online datasets) were used for training and validation, and data until 2050 were predicted. Results: The rapid decreasing trend of prostate cancer incidence started in 2010 will continue until 2018-2019; it will then slow down and reach a plateau after 2050, with several differences among ethnicities. The incidence of breast cancer will reach a plateau in 2030, whereas colorectal cancer incidence will reach a minimum value of 35 per 100,000 in 2030. As for lung cancer, the incidence will decrease from 50 per 100,000 (2017) to 31 per 100,000 in 2030 and 26 per 100,000 in 2050. Conclusion: This up-to-date prediction of cancer burden in the US could be a crucial resource for planning and evaluation of cancer-control programs.
Entities:
Keywords:
artificial neural network; breast cancer; colorectal cancer; future tumor burden; lung cancer; prostate cancer