Ruofei Du’s research while affiliated with Southern University of Science and Technology and other places

Background and objectives The prevalence and fatality rates of cutaneous malignant melanoma (CMM) have been rising, particularly among the elderly. This study analyzes CMM incidence trends in the United States elderly population from 1987 to 2016 to inform prevention and management strategies. Methods Using incidence data from the Surveillance, Epidemiology, and End Results database spanning 1989 to 2008, we calculated the age-adjusted standardized population incidence rates for CMM in elderly individuals. The Joinpoint software was employed to estimate annual percent change and analyze trends in CMM incidence among elderly individuals from 1987 to 2016. Results The study included 56,997 elderly CMM patients from eight Surveillance, Epidemiology, and End Results registries, of whom 36,726 were male (64.4%). The age-adjusted CMM incidence rate from 2012 to 2016 was 0.99 per 1,000, a 2.8-fold increase from 1987–1991 (95% confidence interval: 2.7–2.9). Incidence rates increased with age and birth cohort, peaking at 1.53 per 1,000 males and 0.59 per 1,000 females aged 85+ during 2012–2016. Birth cohort effects also showed a continuous increase. Conclusions This study reveals a substantial increase in CMM incidence rates among the elderly from 1987 to 2016, particularly between 2012 and 2016. Incidence rates escalated with age and birth cohort, with the highest rates observed in individuals aged 85 and older.

Background The purpose of this study is to employ a competing risk model based on the Surveillance, Epidemiology, and End Results (SEER) database to identify prognostic factors for elderly individuals with sigmoid colon adenocarcinoma (SCA) and compare them with the classic Cox proportional hazards model. Methods We extracted data from elderly patients diagnosed with SCA registered in the SEER database between 2010 and 2015. Univariate analysis was conducted using cumulative incidence functions and Gray’s test, while multivariate analysis was performed using both the Fine-Gray and Cox proportional hazards models. Results Among the 10,712 eligible elderly patients diagnosed with SCA, 5595 individuals passed away: 2987 due to sigmoid colon adenocarcinoma and 2608 from other causes. The results of one-way Gray’s test showed that age, race, marital status, AJCC stage, differentiation grade, tumor size, surgical status, liver metastasis status, lung metastasis status, brain metastasis status, radiotherapy status, and chemotherapy status all affected the prognosis of SCA (P < .05). Multivariate analysis showed that sex, age, race, marital status, and surgical status affected the prognosis of SCA (P < .05). Multifactorial Fine-Gray analysis revealed that key factors influencing the prognosis of SCA patients include age, race, marital status, AJCC stage, grade classification, surgical status, tumor size, liver metastasis, lung metastasis, and chemotherapy status (P < .05). Conclusion Data from the SEER database were used to more accurately estimate CIFs for sigmoid colon adenocarcinoma-specific mortality and prognostic factors using competing risk models.