Predicting Lung Cancer Survival to the Future: Population-Based Cancer Survival Modeling Study.

BACKGROUND: Lung cancer remains the leading cause of cancer-related mortality globally, with late diagnoses often resulting in poor prognosis. In response, the Lung Ambition Alliance aims to double the 5-year survival rate by 2025. OBJECTIVE: Using the Taiwan Cancer Registry, this study uses the survivorship-period-cohort model to assess the feasibility of achieving this goal by predicting future survival rates of patients with lung cancer in Taiwan. METHODS: This retrospective study analyzed data from 205,104 patients with lung cancer registered between 1997 and 2018. Survival rates were calculated using the survivorship-period-cohort model, focusing on 1-year interval survival rates and extrapolating to predict 5-year outcomes for diagnoses up to 2020, as viewed from 2025. Model validation involved comparing predicted rates with actual data using symmetric mean absolute percentage error. RESULTS: The study identified notable improvements in survival rates beginning in 2004, with the predicted 5-year survival rate for 2020 reaching 38.7%, marking a considerable increase from the most recent available data of 23.8% for patients diagnosed in 2013. Subgroup analysis revealed varied survival improvements across different demographics and histological types. Predictions based on current trends indicate that achieving the Lung Ambition Alliance's goal could be within reach. CONCLUSIONS: The analysis demonstrates notable improvements in lung cancer survival rates in Taiwan, driven by the adoption of low-dose computed tomography screening, alongside advances in diagnostic technologies and treatment strategies. While the ambitious target set by the Lung Ambition Alliance appears achievable, ongoing advancements in medical technology and health policies will be crucial. The study underscores the potential impact of continued enhancements in lung cancer management and the importance of strategic health interventions to further improve survival outcomes.

Global Prevalence of Helicobacter pylori Infection and Incidence of Gastric Cancer Between 1980 and 2022.

BACKGROUND & AIMS: We aimed to assess the secular trend of the global prevalence of Helicobacter pylori (H pylori) infection in adults and children/adolescents and to show its relation to that of gastric cancer incidence. METHODS: We performed a systematic review and meta-analysis to calculate overall prevalence, adjusted by multivariate meta-regression analysis. The incidence rates of gastric cancer were derived from the Global Burden of Disease Study and Cancer Incidence in Five Continents. RESULTS: Of the 16,976 articles screened, 1748 articles from 111 countries were eligible for analysis. The crude global prevalence of H pylori has reduced from 52.6% (95% confidence interval [CI], 49.6%-55.6%) before 1990 to 43.9% (95% CI, 42.3%-45.5%) in adults during 2015 through 2022, but was as still as high as 35.1% (95% CI, 30.5%-40.1%) in children and adolescents during 2015 through 2022. Secular trend and multivariate regression analyses showed that the global prevalence of H pylori has declined by 15.9% (95% CI, -20.5% to -11.3%) over the last 3 decades in adults, but not in children and adolescents. Significant reduction of H pylori prevalence was observed in adults in the Western Pacific, Southeast Asian, and African regions. However, H pylori prevalence was not significantly reduced in children and adolescents in any World Health Organization regions. The incidence of gastric cancer has decreased globally and in various countries where the prevalence of H pylori infection has declined. CONCLUSIONS: The global prevalence of H pylori infection has declined during the last 3 decades in adults, but not in children and adolescents. The results raised the hypothesis that the public health drive to reduce the prevalence of H pylori as a strategy to reduce the incidence of gastric cancer in the population should be confirmed in large-scale clinical trials.

A Survivorship-Period-Cohort Model for Cancer Survival: Application to Liver Cancer in Taiwan, 1997-2016.

Monitoring survival in cancer is a common concern for patients, physicians, and public health researchers. The traditional cohort approach for monitoring cancer prognosis has a timeliness problem. In this paper, we propose a survivorship-period-cohort (SPC) model for examining the effects of survivorship, period, and year-of-diagnosis cohort on cancer prognosis and for predicting future trends in cancer survival. We used the developed SPC model to evaluate the relative survival (RS) of patients with liver cancer in Taiwan (diagnosed from 1997 to 2016) and to predict future trends in RS by imputing incomplete follow-up data for recently diagnosed patient cohorts. We used cross-validation to select the extrapolation method and bootstrapping to estimate the 95% confidence interval for RS. We found that 5-year cumulative RS increased for both men and women with liver cancer diagnosed after 2003. For patients diagnosed before 2010, the 5-year cumulative RS rate for men was lower than that for women; thereafter, the rates were better for men than for women. The SPC model can help elucidate the effects of survivorship, period, and year-of-diagnosis cohort effects on cancer prognosis. Moreover, the SPC model can be used to monitor cancer prognosis in real time and predict future trends; thus, we recommend its use.