{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T05:18:43Z","timestamp":1787635123481,"version":"build-2736575974"},"reference-count":39,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T00:00:00Z","timestamp":1787616000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Oncol."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Cancer imposes a growing economic burden on health systems globally, yet longitudinal, population-level data on cancer care costs within private insurance remain scarce in low- and middle-income countries. Lebanon\u2019s private insurance sector, administered through third-party administrators (TPAs), covers a substantial share of the economically active population, yet no published study has characterized its cancer-related economic burden, including during the country\u2019s economic contraction since 2019.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A retrospective cohort analysis used event-level insurance claims from a leading Lebanese TPA for 2018\u20132024. Claims carrying an ICD-10 cancer diagnosis code (C or D series, excluding benign neoplasms D10\u2013D36) were processed through a standardized pipeline from event to patient level. Analyses covered demographics, cancer type distribution, treatment and service utilization, cost trends, per-member-per-year (PMPY) expenditure, and a high-cost cohort (HCC) defined as USD 100,000 or more in cumulative costs within any rolling 365-day window.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The cohort comprised 16,617 unique cancer patients generating 157,550 claims and USD 239.9 million in total expenditure over seven years. Females accounted for 53.7% of patients; breast cancer was the most prevalent diagnosis (19.7%), in the predominant 40\u201364-year age group (50.2%). Surgery was the most common treatment modality (29.3%), followed by cancer medicines (24.2%) and radiotherapy (14.9%), yet cancer medicines were the largest cost category (37.8% of spend). Annual expenditure rose from USD 35.7 million (2018) to USD 48.9 million (2024), with a transient compression in 2022.\u00a0A high-cost cohort of 285 patients (1.7%) accounted for USD 55.1 million (23.0% of spend), led by lung cancer (19.7%). Cancer patient rates rose 24.5% (1,015 to 1,263 per 100,000), and per-member cost rose steeply with age, reaching USD 606 PMPY among patients aged 65+ in 2024 versus USD 15\u2013169 in younger groups; overall PMPY reached USD 111.50, recovering from the 2022 trough.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This study provides the first longitudinal, claims-based characterization of cancer care\u2019s economic burden in Lebanon\u2019s privately insured population. Costs are concentrated in a small, identifiable high-cost subgroup, cancer medicines dominate expenditure despite surgery leading by patient volume, and the per-member burden is rising \u2014 an actuarial foundation for designing sustainable, oncology-specific benefit structures.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fonc.2026.1924237","type":"journal-article","created":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T04:23:25Z","timestamp":1787631805000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Economic burden of cancer care in Lebanon\u2019s privately insured population: a seven-year retrospective cohort analysis (2018\u20132024)"],"prefix":"10.3389","volume":"16","author":[{"given":"Shadi","family":"Saleh","sequence":"first","affiliation":[{"name":"Department of Health Management and Policy, Faculty of Health Sciences, American University of Beirut","place":["Beirut, 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