Underlying reasons for post-mortem diagnosed lung cancer cases – A robust retrospective comparative study from Hungary (HULC study)

Abstract

ObjectiveThe Hungarian Undiagnosed Lung Cancer (HULC) study aimed to explore the potential reasons for missed LC (lung cancer) diagnosis by comparing healthcare and socio-economic data among patients with post-mortem diagnosed LC with those who were diagnosed with LC during their lives.MethodsThis nationwide, retrospective study used the databases of the Hungarian Central Statistical Office (HCSO) and National Health Insurance Fund (NHIF) to identify patients who died between January 1, 2019 and December 31, 2019 and were diagnosed with lung cancer post-mortem (population A) or during their lifetime (population B). Patient characteristics, socio-economic factors, and healthcare resource utilization (HCRU) data were compared between the diagnosed and undiagnosed patient population.ResultsDuring the study period, 8,435 patients were identified from the HCSO database with LC as the cause of death, of whom 1,203 (14.24%) had no LC-related ICD (International Classification of Diseases) code records in the NHIF database during their lives (post-mortem diagnosed LC population). Post-mortem diagnosed LC patients were significantly older than patients diagnosed while still alive (mean age 71.20 vs. 68.69 years, p<0.001), with a more pronounced age difference among female patients (difference: 4.57 years, p<0.001), and had significantly fewer GP (General Practitioner) and specialist visits, X-ray and CT scans within 7 to 24 months and 6 months before death, although the differences in GP and specialist visits within 7–24 months did not seem clinically relevant. Patients diagnosed with LC while still alive were more likely to be married (47.62% vs. 33.49%), had higher educational attainment, and had more children, than patients diagnosed with LC post-mortem.ConclusionsPost-mortem diagnosed lung cancer accounts for 14.24% of total lung cancer mortality in Hungary. This study provides valuable insights into patient characteristics, socio-economic factors, and HCRU data potentially associated with a high risk of lung cancer misdiagnosis.

Decreasing incidence and mortality of lung cancer in Hungary between 2011 and 2021 revealed by robust estimates reconciling multiple data sources

“…Appreciating that the increasing weight of input from the national cancer registry of the Czech Republic in the reported Hungarian estimate is in agreement with our observations regarding the similarity of healthcare indicators in Hungary to other Eastern European countries [7], we would like to advocate for granting greater importance to local datasets, when developing these models. Since the availability of observational data for Hungary is limited currently, we would like to provide such empirical data, hoping to contribute to closing the gap between lung cancer incidence estimates in the literature.…”

“…By extending the studied period to more than 10 years, the current study provides updates to epidemiological indicators of lung cancer in Hungary with an even more refined approach, but also largely building on our previous reports [ 4 , 7 , 9 ]. This update confirms the inconsistency between lung cancer incidence rates reported previously for Hungary and the rates estimated by our approach.…”

“…Another potential issue identified by researchers at the HNCR, could be the inconsistent reporting of lung metastases from other sites [ 5 ] and this is related to a third source of uncertainty, identified by our research group recently: the considerable number of lung cancer patients diagnosed post mortem only [ 7 ]. As a comparison, ∼10% of lung cancer cases in Germany are recognized only during autopsy [ 11 ].…”

“…Furthermore, the reliability of tumor classification in reports has also been questioned by a recent amendment [ 6 , 7 ] of the Hungarian National Cancer Registry (HNCR). One of the tumor types most frequently misclassified was lung cancer, possibly since lung is also a common site of metastases.…”

“…Previous publications from our research group [ 4 , 8 ] have already demonstrated that epidemiological indicators can be estimated efficiently using this data source. Additionally, patient-level details captured in reimbursement claims have also provided valuable insights on the high number of post mortem diagnosed lung cancer cases as a potential confounder of reported case numbers [ 7 ].…”