Estimating Country-Specific Incidence Rates of Rare Cancers: Comparative Performance Analysis of Modeling Approaches Using European Cancer Registry Data

Analyzing Cancer Incidence Trends in Oman From 1996 to 2019: A Comprehensive Study of the National Cancer Annual Reports

PURPOSE

Previous studies have reported that cancer incidence trends in Oman varied by tumor site and sex. No comprehensive analysis of all cancer sites had been reported. The objective of this study is to analyze cancer incidence trends in Oman and calculate the annual percent change (APC) in age-standardized rates (ASRs) for all-cancer and 61 individual cancer sites in Omani men and women from 1996 to 2019.

METHODS

We gathered incidence data from The Omani National Cancer Registry for all cancers combined and individual tumor sites. We estimated the APC using Poisson regression.

RESULTS

The cancer ASR in the Omani population increased by 23% (from 95/100,000 in 1996 to 117.2/100,000 in 2019), with the increase being more pronounced in females (48% v 7% in males). Among the male population, there was significant increase in the ASRs of colon, rectum, thyroid, and prostate cancers, with APCs of 6.92%, 4.24%, 4.19%, and 2.03%, respectively. Among females, all-cancer incidence showed significant increase (APC = 1.39%), and increasing trends were observed in uterine, colon, rectum, thyroid, and breast cancers (APCs = 7.57%, 7.08%, 5.19%, 5.16%, and 4.19%, respectively).

CONCLUSION

The ASR of all-cancer increased significantly in Omani women but not in men. Uterine cancer had the highest APC. Colorectal cancer and thyroid ASR increased in both males and females. Breast and prostate cancers showed increasing trends. Further research is needed to explore factors contributing to increasing cancer incidences.

Ten-Year Probabilities of Death Due to Cancer and Cardiovascular Disease among Breast Cancer Patients Diagnosed in North-Eastern Spain

Mortality from cardiovascular disease (CVD), second tumours, and other causes is of clinical interest in the long-term follow-up of breast cancer (BC) patients. Using a cohort of BC patients (N = 6758) from the cancer registries of Girona and Tarragona (north-eastern Spain), we studied the 10-year probabilities of death due to BC, other cancers, and CVD according to stage at diagnosis and hormone receptor (HR) status. Among the non-BC causes of death (N = 720), CVD (N = 218) surpassed other cancers (N = 196). The BC cohort presented a significantly higher risk of death due to endometrial and ovarian cancers than the general population. In Stage I, HR- patients showed a 1.72-fold higher probability of all-cause death and a 6.11-fold higher probability of breast cancer death than HR+ patients. In Stages II-III, the probability of CVD death (range 3.11% to 3.86%) surpassed that of other cancers (range 0.54% to 3.11%). In Stage IV patients, the probability of death from any cancer drove the mortality risk. Promoting screening and preventive measures in BC patients are warranted, since long-term control should encompass early detection of second neoplasms, ruling out the possibility of late recurrence. In patients diagnosed in Stages II-III at an older age, surveillance for preventing late cardiotoxicity is crucial.

Invited Commentary: Predicting Incidence Rates of Rare Cancers-Adding Epidemiologic and Spatial Contexts

There are unique challenges to identifying causes of and developing strategies for prevention of rare cancers, driven by the difficulty in estimating incidence, prevalence, and survival due to small case numbers. Using a Poisson modeling approach, Salmerón et al. (Am J Epidemiol. 2022;191(3):487-498) built upon their previous work to estimate incidence rates of rare cancers in Europe using a Bayesian framework, establishing a uniform prior for a measure of variability for country-specific incidence rates. They offer a methodology with potential transferability to other settings with similar cancer surveillance infrastructure. However, the approach does not consider the spatiotemporal correlation of rare cancer case counts and other, potentially more appropriate nonnormal probability distributions. In this commentary, we discuss the implications of future work from cancer epidemiology and spatial epidemiology perspectives. We describe the possibility of developing prediction models tailored to each type of rare cancer; incorporating the spatial heterogeneity in at-risk populations, surveillance coverage, and risk factors in these predictions; and considering a modeling framework with which to address the inherent spatiotemporal components of these data. We note that extension of this methodology to estimate subcountry rates at provincial, state, or smaller geographic levels would be useful but would pose additional statistical challenges.