Socioeconomic Status and Overall Survival Among Patients With Hematological Malignant Neoplasms.

Importance: In recent years, there has been a focus on reducing the socioeconomic gap in survival for hematological malignant neoplasms. Understanding recent developments is important to develop further intervention to improve care. Objective: To investigate the temporal trend in associations of socioeconomic status (SES) with survival among 3 aggressive hematological malignant neoplasms: multiple myeloma (MM), acute myeloid leukemia (AML), and diffuse large B-cell lymphoma (DLBCL). Design, Setting, and Participants: This nationwide, population-based cohort study used retrospectively collected data from 3 clinical registries of patients diagnosed in Denmark between January 1, 2005, and December 31, 2020, with follow-up until December 31, 2021. Analyses were stratified by diagnosis year (2005-2009, 2010-2014, and 2015-2020). Participants were patients aged 25 to 65 years with hematological malignant neoplasms. Patients with missing data on education were excluded. Data were analyzed from October 14, 2022, to January 2, 2024. Exposure: Education was used as a proxy for SES and defined low- and high-SES groups based on the completion of tertiary education. Main Outcomes and Measures: The main outcome was overall survival (OS), analyzed using Kaplan-Meier (log rank) method and Cox proportional hazards regression adjusted for age, sex, performance status, comorbidities, and disease-specific prognostic indices. Two-year OS through time and survival difference were estimated using flexible parametric survival models. Results: A total of 5677 patients (median [IQR] age, 58 [51-62] years; 3177 [57.0%] male) were assessed, including 1826 patients with MM, 1236 patients with AML, and 2509 patients with DLBCL. The 2-year OS increased over time for patients with MM (78.8% [95% CI, 75.4%-82.3%] to 91.4% [95% CI, 89.3%-93.5%]), AML (42.2% [95% CI, 37.8%-47.1%] to 52.7% [95% CI, 48.0%-57.9%]), and DLBCL (80.1% [95% CI, 77.4%-82.8%] to 88.1% [95% CI, 86.0%-90.3%]). For MM and DLBCL, no association of SES with survival was observed after adjustment (MM: hazard ratio [HR], 0.99 [95% CI, 0.85-1.15]; DLBCL: HR, 1.08 [95% CI, 0.91-1.29]). For AML, a negative association was observed between low SES and survival (HR, 1.49 [95% CI, 1.25-1.76]), but the association was attenuated in recent years. The difference in hazard for patients with low SES and AML was observed in the first 2 years after diagnosis. Conclusions and Relevance: These findings suggest that survival has improved among patients with these hematological malignant neoplasms. While patients with MM and DLBCL had increased survival in all groups, disparities were observed in AML outcomes, primarily in the first years after diagnosis. These results suggest that differences originate in factors specific to AML.

Extracting Systemic Anticancer Treatment Lines from the Danish National Patient Registry for Solid Tumour Patients Treated in the North Denmark Region Between 2009 and 2019.

Background: Reconstructing patient treatment trajectories is important to generate real-world evidence for epidemiological studies. The Danish National Patient Registry (DNPR) contains information about drug prescriptions and could therefore be used to reconstruct treatment trajectories. We aimed to evaluate and enhance two existing methods to reconstruct systemic anticancer treatment trajectories. Methods: This study was based on data from 8738 consecutive patients with solid tumors treated in the North Denmark Region between 2009 and 2019. Two approaches found in the literature as well as two new approaches were applied to the DNPR data. All methods relied on time intervals between two consecutive drug administrations to determine if they belonged to the same treatment line. MedOnc, a local dataset from the Department of Oncology, Aalborg University Hospital was used as a reference. To evaluate the performance of each method, F1-scores were calculated after matching the lines identified in both datasets. We used three different matching strategies: stringent matching, loose matching, and matching based on line numbers, controlling for overfitting. Results: Overall, the two new approaches outperformed the simpler and best performing of the two existing methods, with F1-scores of 0.47 and 0.45 vs 0.44 for stringent matching and 0.84 and 0.83 vs 0.82 for loose matching. Nevertheless, only one of the new methods outperformed the existing simpler method when matching on the number of lines (0.73 vs 0.72). Large differences were seen by cancer site, especially for the stringent and line number matchings. Performances were relatively stable by calendar year. Conclusion: The high F1-scores for the new methods confirm that they should be generally preferred to reconstruct systemic anticancer treatment trajectories using the DNPR.