Seasonal variations in the diagnosis of the top 10 cancers in Korea: A nationwide population-based study using a common data model

Association between colonoscopy and colorectal cancer occurrence and mortality in the older population: a population-based cohort study

We aimed to evaluate the association between colonoscopy and colorectal cancer (CRC) occurrence and related mortality in an older population.This retrospective, nationwide, population-based cohort study used data of adults aged ≥40 years from the Health Insurance Review and Assessment Service database. After excluding colonoscopy within 6 months of CRC diagnosis during enrollment, CRC occurrence and related mortality were compared between colonoscopy and non-colonoscopy groups using a time-dependent Cox proportional hazard model. Subgroup analysis was conducted among four age groups: young, middle-aged, old, and very old.Among 748986 individuals followed for 9.64 (SD 0.99) years, the colonoscopy group had a 65% lower CRC occurrence (adjusted hazard ratio [HRa] 0.35, 95%CI 0.32-0.38) and 76% lower CRC-related mortality (HRa 0.24, 95%CI 0.18-0.31) after 5 years compared with the non-colonoscopy group. Colonoscopy was associated with the most significant reduction in CRC occurrence in the middle-aged group (HRa 0.32, 95%CI 0.29-0.35) and in CRC-related mortality in the young group (HRa 0.04, 95%CI 0.01-0.33); the very old group had the least reduction in both CRC occurrence and CRC-related mortality (HRa 0.44, 95%CI 0.33-0.59 and HRa 0.28, 95%CI 0.15-0.53, respectively).We found a significant association between colonoscopy and reduction in CRC occurrence and CRC-related mortality in adults aged ≥40 years after 5 years of follow-up; however, these associations were weaker in the very old group. More research is needed on the association between colonoscopy and older age.

A scoping review of OMOP CDM adoption for cancer research using real world data

The Observational Medical Outcomes Partnership (OMOP) common data model (CDM) supports large-scale research by enabling distributed network analyses. However, the breadth of its adoption in cancer research is not well understood. We conducted a scoping review to describe the adoption of the OMOP CDM in cancer research. A total of 49 unique articles were included in the review, with 30 on the data analysis theme, and 20 on the infrastructure theme. This review highlighted that while the OMOP CDM ecosystem has enabled successful data support for cancer research, particularly for collaborative studies, ongoing model development and iterative improvement remain needed to fulfill additional research data needs. Expanding disease sites, specifically for rare cancers, integrating more diverse types of data sources, improving data quality, adopting advanced analytics methodology, and increasing multisite evaluations serve as important opportunities to facilitate secondary usage of observational data in future cancer research.

Common Data Model-based Analysis of Selective Leukoreduction Protocol Compliance at Three Hospitals

Background

The selective leukoreduction protocol (SLP) is limited in that patients who require it can be overlooked. We estimated SLP compliance (SLPC) using the Observational Medical Outcomes Partnership common data model (CDM).

Methods

Patients were classified into eight groups: pre- and post-hematology disease (A and B), pre- and post-solid organ transplantation (C and D), solid cancer (E), immunodeficiency (F), anticancer therapy (G), and cardiovascular surgery (H). We examined the red blood cell (RBC) transfusion history from three hospital datasets comprising approximately three million patients over 20 years using CDM-based analysis. SLPC was calculated as the percentage of patients who received only leukoreduced RBCs in total patients transfused RBCs.

Results

In total, 166,641 patients from three hospitals were enrolled in this study. From 2001 to 2021, SLPC in all groups, except H, tended to increase, although there were differences among the hospitals. Based on the most recent values (2017-2021), the SLPC in groups A, B, D, and G was maintained at ≥75% until 1,095 days before or after diagnosis or treatment. Groups E, F, and H had < 50% SLPC one day after diagnosis and treatment.

Conclusions

CDM analysis supports the review of large datasets for SLPC evaluation. Although SLPC tended to improve in most patient groups, additional education and monitoring are needed for groups that continue to show low SLPC.

Long-term ambient hydrocarbon exposure and incidence of urinary bladder cancer

Particulate matter and volatile organic compounds, including total hydrocarbons (THCs), are major ambient air pollutants. Primary nonmethane hydrocarbons (NMHCs) originate from vehicle emissions. The association between air pollution and urinary bladder cancer (UBC) is debatable. We investigated whether long-term exposure to ambient hydrocarbons increases UBC risk among people aged ≥ 20 years in Taiwan. Linkage dataset research with longitudinal design was conducted among 589,135 initially cancer-free individuals during 2000-2013; 12 airborne pollutants were identified. Several Cox models considering potential confounders were employed. The study outcomes were invasive or in situ UBC incidence over time. The targeted pollutant concentration was divided into three tertiles: T1/T2/T3. The mean age of individuals at risk was 42.5 (SD 15.7), and 50.5% of the individuals were men. The mean daily average over 10 years of airborne THC concentration was 2.25 ppm (SD 0.13), and NMHC was 0.29 ppm (SD 0.09). Both pollutants show long-term monotonic downward trend over time using the Mann-Kendall test. There was a dose-dependent increase in UBC at follow-up. UBC incidence per 100,000 enrollees according to T1/T2/T3 exposure to THC was 60.9, 221.2, and 651.8, respectively; it was 170.0/349.5/426.7 per 100,000 enrollees, corresponding to T1/T2/T3 exposure to NMHC, respectively. Without controlling for confounding air pollutants, the adjusted hazard ratio (adj.HR) was 1.83 (95% CI 1.75-1.91) per 0.13-ppm increase in THC; after controlling for PM2.5, adj.HR was even higher at 2.09 (95% CI 1.99-2.19). The adj.HR was 1.37 (95% CI 1.32-1.43) per 0.09-ppm increase in ambient NMHC concentration. After controlling for SO2 and CH4, the adj.HR was 1.10 (95% CI 1.06-1.15). Sensitivity analyses showed that UBC development risk was not sex-specific or influenced by diabetes status. Long-term exposure to THC and NMHC may be a risk factor for UBC development. Acknowledging pollutant sources can inform risk management strategies.

No Impact of Seasonality of Diagnoses on Baseline Tumor Immune Infiltration, Response to Treatment, and Prognosis in BC Patients Treated with NAC

Simple Summary

High tumor-infiltrating lymphocyte (TIL) levels are associated with an increased response to neoadjuvant chemotherapy (NAC) in breast cancer (BC). The seasonal fluctuation of TILs in breast cancer is poorly documented. In this study, we compared pre- and post-treatment immune infiltration, the treatment response as assessed by means of pathological complete response (pCR) rates, and survival according to the seasonality of BC diagnoses in a clinical cohort of patients treated with NAC. We found no association between seasonality and baseline TIL levels or pCR rates. We found that post-NAC stromal lymphocyte infiltration was lower when cancer was diagnosed in the summer, especially in the subgroup of patients with TNBC. Our data do not support the hypothesis that the seasonality of diagnoses has a major impact on the natural history of BC treated with NAC.

Abstract

Breast cancer (BC) is the most common cancer in women worldwide. Neoadjuvant chemotherapy (NAC) makes it possible to monitor in vivo response to treatment. Several studies have investigated the impact of the seasons on the incidence and detection of BC, on tumor composition, and on the prognosis of BC. However, no evidence is available on their association with immune infiltration and the response to treatment. The objective of this study was to analyze pre- and post-NAC immune infiltration as assessed by TIL levels, the response to treatment as assessed by pathological complete response (pCR) rates, and oncological outcomes as assessed by relapse-free survival (RFS) or overall survival (OS) according to the seasonality of BC diagnoses in a clinical cohort of patients treated with neoadjuvant chemotherapy. Out of 1199 patients, the repartition of the season at BC diagnosis showed that 27.2% were diagnosed in fall, 25.4% in winter, 24% in spring, and 23.4% in summer. Baseline patient and tumor characteristics, including notable pre-NAC TIL levels, were not significantly different in terms of the season of BC diagnosis. Similarly, the pCR rates were not different. No association for oncological outcome was identified. Our data do not support the idea that the seasonality of diagnoses has a major impact on the natural history of BC treated with NAC.