26 research outputs found
Cancer-Specific Mortality, Cure Fraction, and Noncancer Causes of Death Among Diffuse Large B-cell Lymphoma Patients in the Immunochemotherapy Era.
BACKGROUND
Survival after the diagnosis of diffuse large B-cell lymphoma (DLBCL) has been increasing since 2002 because of improved therapies; however, long-term outcomes for these patients in the modern treatment era are still unknown. METHODS
Using Surveillance, Epidemiology, and End Results data, this study first assessed factors associated with DLBCL-specific mortality during 2002-2012. An epidemiologic risk profile, based on clinical and demographic characteristics, was used to stratify DLBCL cases into low-, medium-, and high-risk groups. The proportions of DLBCL cases that might be considered cured in these 3 risk groups was estimated. Risks of death due to various noncancer causes among DLBCL cases versus the general population were also calculated with standardized mortality ratios (SMRs). RESULTS
Overall, 8274 deaths were recorded among 18,047 DLBCL cases; 76% of the total deaths were attributed to DLBCL, and 24% were attributed to noncancer causes. The 10-year survival rates for the low-, medium-, and high-risk groups were 80%, 60%, and 36%, respectively. The estimated cure proportions for the low-, medium-, and high-risk groups were 73%, 49%, and 27%, respectively; however, these cure estimates were uncertain because of the need to extrapolate the survival curves beyond the follow-up time. Mortality risks calculated with SMRs were elevated for conditions including vascular diseases (SMR, 1.3), infections (SMR, 3.1), gastrointestinal diseases (SMR, 2.5), and blood diseases (SMR, 4.6). These mortality risks were especially high within the initial 5 years after the diagnosis and declined after 5 years. CONCLUSIONS
Some DLBCL patients may be cured of their cancer, but they continue to experience excess mortality from lymphoma and other noncancer causes. Cancer 2017. © 2017 American Cancer Society
Breast-Cancer-Specific Mortality in Patients Treated Based on the 21-Gene Assay: A SEER Population-Based Study
The 21-gene Recurrence Score assay is validated to predict recurrence risk and chemotherapy benefit in hormone-receptor-positive (HR+) invasive breast cancer. To determine prospective breast-cancer-specific mortality (BCSM) outcomes by baseline Recurrence Score results and clinical covariates, the National Cancer Institute collaborated with Genomic Health and 14 population-based registries in the the Surveillance, Epidemiology, and End Results (SEER) Program to electronically supplement cancer surveillance data with Recurrence Score results. The prespecified primary analysis cohort was 40–84 years of age, and had node-negative, HR+, HER2-negative, nonmetastatic disease diagnosed between January 2004 and December 2011 in the entire SEER population, and Recurrence Score results (N = 38,568). Unadjusted 5-year BCSM were 0.4% (n = 21,023; 95% confidence interval (CI), 0.3–0.6%), 1.4% (n = 14,494; 95% CI, 1.1–1.7%), and 4.4% (n = 3,051; 95% CI, 3.4–5.6%) for Recurrence Score \u3c 18, 18–30, and ≥ 31 groups, respectively (P \u3c 0.001). In multivariable analysis adjusted for age, tumor size, grade, and race, the Recurrence Score result predicted BCSM (P \u3c 0.001). Among patients with node-positive disease (micrometastases and up to three positive nodes; N = 4,691), 5-year BCSM (unadjusted) was 1.0% (n = 2,694; 95% CI, 0.5–2.0%), 2.3% (n = 1,669; 95% CI, 1.3–4.1%), and 14.3% (n = 328; 95% CI, 8.4–23.8%) for Recurrence Score \u3c 18, 18–30, ≥ 31 groups, respectively (P \u3c 0.001). Five-year BCSM by Recurrence Score group are reported for important patient subgroups, including age, race, tumor size, grade, and socioeconomic status. This SEER study represents the largest report of prospective BCSM outcomes based on Recurrence Score results for patients with HR+, HER2-negative, node-negative, or node-positive breast cancer, including subgroups often under-represented in clinical trials
Cost of illness for severe and non-severe diarrhea borne by households in a low-income urban community of Bangladesh: A cross-sectional study
The illness cost borne by households, known as out-of-pocket expenditure, was 74% of the total health expenditure in Bangladesh in 2017. Calculating economic burden of diarrhea of low-income urban community is important to identify potential cost savings strategies and prioritize policy decision to improve the quality of life of this population. This study aimed to estimate cost of illness and monthly percent expenditure borne by households due diarrhea in a low-income urban settlement of Dhaka, Bangladesh. We conducted this study in East Arichpur area of Tongi township in Dhaka, Bangladesh from September 17, 2015 to July 26, 2016. We used the World Health Organization (WHO) definition of three or more loose stool in 24 hours to enroll patients and enrolled 106 severe patients and 158 non-severe patients from Tongi General Hospital, local pharmacy and study community. The team enrolled patients between the first to third day of the illness (≤ 72 hours) and continued daily follow-up by phone until recovery. We considered direct and indirect costs to calculate cost-per-episode. We applied the published incidence rate to estimate the annual cost of diarrhea. The estimated average cost of illness for patient with severe diarrhea was US 6.36 [95% CI: 5.19, 7.55] (499 BDT), 4% of the average monthly income of households. A single diarrheal episode substantially affects financial condition of low-income urban community residents: a severe episode can cost almost equivalent to 4.35 days (17%) and a non-severe episode can cost almost equivalent to 1 day (4%) of household’s income. Preventing diarrhea preserves health and supports financial livelihoods
Modeling the Effect of a Preventive Intervention on the Natural History of Cancer: Application to the Prostate Cancer Prevention Trial
The Prostate Cancer Prevention Trial (PCPT) recently demonstrated a significant reduction in prostate cancer incidence of about 25% among men taking finasteride compared to men taking placebo. However, the effect of finasteride on the natural history of prostate cancer is not well understood. We adapted a convolution model developed by Pinsky (2001) to characterize the natural history of prostate cancer in the presence and absence of finasteride. The model was applied to data from 10,995 men in PCPT who had disease status determined by interim diagnosis of prostate cancer or end-of-study biopsy. Prostate cancer cases were either screen-detected by Prostate-Specific Antigen (PSA), biopsy-detected at the end of the study, or clinically detected, that is, detected by methods other than PSA screening. The hazard ratio (HR) for the incidence of preclinical disease on finasteride versus placebo was 0.42 (95% CI: 0.20-0.58). The progression from preclinical to clinical disease was relatively unaffected by finasteride, with mean sojourn time being 16 years for placebo cases and 18.5 years for finasteride cases (p-value for difference = 0.2). We conclude that finasteride appears to affect prostate cancer primarily by preventing the emergence of new, preclinical tumors with little impact on established, latent disease.