ArticleBMC medicine2025
Connection between trajectory of primary cancer monitoring indicators and mortality after cancer in South Korea.
Article in BMC medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
backgroundCancer remains a leading global cause of mortality, responsible for nearly 10 million deaths in 2020. Given the country's low birth rate and aging population, the escalating cancer burden poses significant challenges to its healthcare systems. This study aimed to investigate the relationship between lifestyle risk factors and cancer case fatality, emphasizing the collective impact of these factors through a prevention index at the regional level.
methodsThe study focused on ten cancer types, categorizing counties into three levels of cancer incidence rates using group-based trajectory modeling to identify disparities in patterns and levels among groups. Additionally, we segmented the proportions of obesity prevalence, average daily per capita smoking amount, prevalence of smoking, prevalence of high-risk alcohol consumption, prevalence of hypertension diagnosis, prevalence of diabetes diagnosis, and cancer case fatality into three groups through group-based trajectory modeling. Cox proportional hazard models were employed to evaluate the hazard ratios (HR) for cancer case fatality, adjusting for age, sex, income level, and cancer stage.
resultsThe study population comprised 294,070 cancer patients, with thyroid, stomach, colorectal, breast, and lung cancers being the most common. The prevention index (PI) levels, calculated from six primary prevention indicators, were categorized into High, Medium, and Low grades. Counties with higher PI levels (H) exhibited significantly lower cancer case fatality among cancer patients compared to those with lower PI levels (L). Across all cancer types, females had lower cancer case fatality compared to males, higher age was linked to higher cancer case fatality, advanced stage cases had the highest cancer case fatality, and the highest income quintile consistently showed the lowest cancer case fatality.
conclusionsThe study highlights the significant inverse relationship between primary prevention indicator levels and cancer case fatality. Higher scores on primary prevention indicators are associated with lower cancer mortality among cancer patients for various cancer types, underscoring the importance of comprehensive, community-based prevention strategies in mitigating cancer risk and improving public health outcomes in South Korea.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.