Projecting cancer prevalence by phase of care: a methodological approach for health service planning - Francisci, Silvia; Tursini, Francesco; Dal Maso, Luigino; Gigli, Anna; Guzzinati, Stefano (Frontiers in Oncology, 2023)
In most developed countries, the number of cancer survivors is expected to increase over the coming decades, because of raising incidence and survival, and population ageing. These people are heterogeneous in terms of health service requirements: from recently diagnosed patients requiring first course therapy, to patients with extensive care needs and having severe disabilities, to long-term survivors who need minimal care only. Therefore, in terms of providing health care planners and policy makers with useful indicators to address policies according to health service demands, it is worth providing updated measures of prevalence for groups of patients based on the level of care they require. The aim of this paper is to illustrate a new method to estimate short-time projections of cancer prevalence by phase-of-care, which applies to areas covered by cancer registration.The proposed method combines linear regression models to project limited duration prevalence derived from Cancer Registry data and a session of the freely available software COMPREV to estimate projected complete prevalence into three distinct clinically relevant phases-of-care: initial, continuing and final. The method is illustrated and validated using data of the Veneto Region in Italy for breast, colorectal and lung cancers.Prevalence is expected to increase in 2015-2026 for all cancer site and sexes considered, with average annual variation spanning from 2.6% for women with lung cancer to 0.5% for men with colorectal cancer. The only exception is lung cancer prevalence among men, showing a 1.9% average annual decrease. Most patients are in the continuing phase-of-care, followed by the initial and final ones, except for lung cancer, where the final phase-of-care prevails over the initial one.The paper proposes a method to estimate (short-term) future cancer health care needs that is based on user friendly and freely available software and linear regression models. Results from validation confirm the applicability of our method to the most frequent cancer types, provided that Cancer Registry data with at least 15 years of registration are available. Evidence from this method is addressed to policy makers for planning future cancer care, thus improving cancer survivorship experience for patients and care-givers.