Mitigating the Paucity-of-Data Problem for Target Population Sizing: Exploring a Model-Based Approach for Advanced Gastroenteropancreatic Neuroendocrine TumoursAurore Bergamasco1, Gabrielle Nayroles2, Anne-Marie Castilloux3, Jérôme Dinet2, Anthony Berthon2, Sylvie Gabriel2 and Yola Moride1,3,4*
- *Corresponding Author:
- Yola Moride
Faculty of Pharmacy
Université de Montréal
CP 6128, Succ. Centre-ville Montreal, QC, H3T 2E3, Canada
Tel: +1 5143433011
E-mail: [email protected]
Received Date: February 09, 2017; Accepted Date: March 23, 2017; Published Date: March 30, 2017
Citation: Bergamasco A, Nayroles G , Castilloux AM, Dinet J, Berthon A, et al. (2017) Mitigating the Paucity-of-Data Problem for Target Population Sizing: Exploring a Model-Based Approach for Advanced Gastroenteropancreatic Neuroendocrine Tumours. Med Saf Glob Health 6: 131.
Copyright: © 2017 Bergamasco A, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Background: Gastroenteropancreatic Neuroendocrine Tumors (GEP-NETs) are rare neoplasms. For innovative treatments, payer recommendations frequently involve sub-populations more restricted than approved indications. Paucity of epidemiologic data specific to sub-populations is a challenge for reimbursement strategies. Objectives: To estimate the population size by site and type of GEP-NETs in the US, EU, and Australia, over a five-year period. Methods: Two GEP-NET sub-populations, respectively approved and restricted indication for reimbursement, were considered: i) Stable/slow progressing well-differentiated, functioning and non-functioning GEP-NETs and unresectable locally advanced/metastatic disease; and ii) Stable/slow progressing well-differentiated, nonfunctioning GEP-NETs and unresectable locally advanced/metastatic disease. For both, tumours originating from the hindgut were excluded. Following identification in the literature of crude prevalence and incidence rates for a broader GEP-NET, estimates were obtained for each sub-population using proportions of GEP-NETs by site and type derived from clinical studies. Then, these figures were further refined using clinical expert opinions. A 5-year target population growth model was developed. Results: Over 5 years, respectively for the first and second sub-population, number of patients is expected to increase from 7,473 to 9,393 and 5,231 to 6,575 in selected European countries; from 8,051 to 10,119 and 5,636 to 7,083 in the US; and from 593 to 746 and 415 to 522 in Australia. Because the second sub-population is a subgroup of the first, lower estimates were obtained. Conclusion: In the absence of epidemiologic data on specific sub-populations, the development of a population growth model can be used to estimate trends in population size under varying labelling hypotheses.