Introduction: Cancer treatment details (i.e., radiation site, chemotherapy dose) are required to conduct rigorous health services research but are difficult to obtain from administrative data. We conducted a validation study to ascertain the optimal algorithm for defining cancer treatment details in cancer-specific and general health administrative data using available chart-abstracted data from adolescent and young adult (AYA) cancer patients.
Methods: Health administrative data and cancer treatment data reported by visit in Ontario, Canada were compared separately and in a combined algorithm to a reference-standard chart-abstracted database of AYA cancer patients diagnosed in 2005-2012 (n = 1173). We tested algorithms for three tiers of treatment details: any chemotherapy/radiotherapy provided; type of chemotherapy/site of radiation; dose of chemotherapy/radiation. For each algorithm, we calculated sensitivity, specificity, positive predictive value, negative predictive value with 95 % confidence intervals (95 %CI) and simple kappa statistics, overall and according to cancer type, diagnosis period, and locus of care.
Results: General health administrative data had high sensitivity and specificity (> 80 %) for detection of any chemotherapy (n = 942) or radiation exposure (n = 412) and was not improved by using cancer-specific data. In 475 patients (40.5 %) with chemotherapy treatment records, sensitivity (22.4-59.6 %) and specificity (95.8-99.1 %) varied by chemotherapy type/class. Factors associated with missing records include locus of care (9.5 % in pediatric vs. 81.7 % in adult cancer centres), year of diagnosis, and type of cancer. There was moderate to strong correlation (r = 0.50-0.79) between dosing for the most common anthracyclines, combined alkylators, cisplatin, and bleomycin. For radiation treatment data (n = 406, 98.5 %), sensitivity and specificity for radiation site ranged from 73.4 % to 91.2 % and 96.6 % to 99.7 %, respectively, with strong dosing correlation (r = 0.63-0.95, by site).
Conclusions: Both general and cancer-specific health administrative data have value in determining receipt of chemotherapy and/or radiation and can be used reliably to create cohorts of exposed cancer patients. More granular information regarding dose and type of chemotherapy and dose and site of radiation therapy is highly specific but limited by variable sensitivity. Care should be taken when using the data to estimate prevalence, compare treated/untreated groups or when full capture of an exposed population is otherwise required as underestimations of the true effect may occur.
Background: Malignant mesothelioma is a rare but aggressive cancer primarily caused by occupational asbestos exposure. This study aims to comprehensively assess global mesothelioma incidence and mortality trends, examine their associations with the Human Development Index (HDI), project future burden through 2050, and investigate epidemiological correlations with other malignancies.
Methods: We extracted mesothelioma incidence and mortality data from GBD 2021 and GLOBOCAN 2022, covering 204 and 185 countries from 1980 to 2022, respectively. Temporal trends were analyzed using estimated annual percentage change (EAPC), while age-period-cohort (APC) modeling was applied in six high-HDI countries to assess generational burden shifts. Future projections were generated using age-stratified machine-learning models trained on historical data and validated against multiple forecasting methods. Additionally, mesothelioma's epidemiological associations with 27 other cancers were analyzed using linear and logistic regression.
Results: Between 1990 and 2021, global mesothelioma incidence and mortality showed a modest decline (ASIR EAPC: -0.2 [95 % UI: -0.32 to -0.08]; ASDR EAPC: -0.23 [95 % UI: -0.3 to -0.16]). Males exhibited a significantly higher burden than females, with the UK and Australia reporting the highest incidence and mortality rates. A clear threshold effect of HDI was observed, with mesothelioma rates remaining stable below HDI 0.8 but rising sharply beyond this level. Additionally, mesothelioma demonstrated strong positive correlations with tracheobronchial lung cancer, ovarian cancer, and Hodgkin lymphoma, suggesting potential shared environmental and occupational risk factors.
Conclusions: Our findings provide the most up-to-date epidemiological insights into mesothelioma, highlighting its stable long-term burden, gender disparities, and socioeconomic influences.

