Projected Incidence of Hepatobiliary Cancers and Trends Based on Age, Race, and Gender in the United States.

BACKGROUND: Identifying the projected incidence of hepatobiliary cancers and recognizing patient cohorts at increased risk can help develop targeted interventions and resource allocation. The expected incidence of subtypes of hepatobiliary cancers in different age groups, races, and genders remains unknown. METHODS: Historical epidemiological data from the Surveillance, Epidemiology, and End Results (SEER) database was used to project future incidence of hepatobiliary malignancies in the United States and identify trends by age, race, and gender. Patients ≥18 years of age diagnosed with a hepatobiliary malignancy between 2001 and 2017 were included. US Census Bureau 2017 National Population projects provided the projected population from 2017 to 2029. Age-Period-Cohort forecasting model was used to estimate future births cohort-specific incidence. All analyses were completed using R Statistical Software. RESULTS: We included 110381 historical patients diagnosed with a hepatobiliary malignancy between 2001 and 2017 with the following subtypes: hepatocellular cancer (HCC) (68%), intrahepatic cholangiocarcinoma (iCCA) (11.5%), gallbladder cancer (GC) (8%), extrahepatic cholangiocarcinoma (eCCA) (7.6%), and ampullary cancer (AC) (4%). Our models predict the incidence of HCC to double (2001 to 2029) from 4.5 to 9.03 per 100,000, with the most significant increase anticipated in patients 70-79 years of age. In contrast, incidence is expected to continue to decline among the Asian population. Incidence of iCCA is projected to increase, especially in the white population, with rates in 2029 double those in 2001 (2.13 vs. 0.88 per 100,000, respectively; p < 0.001). The incidence of GC among the black population is expected to increase. The incidence of eCCA is expected to significantly increase, especially among the Hispanic population, while that of AC will remain stable. DISCUSSION: The overall incidence of hepatobiliary malignancies is expected to increase in the coming years, with certain groups at increased risk. These findings may help with resource allocation when considering screening, treatment, and research in the coming years.

Global epidemiologic patterns of oropharyngeal cancer incidence trends.

BACKGROUND: The emergence of human papillomavirus (HPV)-positive oropharyngeal cancer and evolving tobacco use patterns have changed the landscape of head and neck cancer epidemiology internationally. We investigated updated trends in oropharyngeal cancer incidence worldwide. METHODS: We analyzed cancer incidence data between 1993 and 2012 from 42 countries using the Cancer Incidence in Five Continents database volumes V through XI. Trends in oropharyngeal cancer incidence were compared with oral cavity cancers and lung squamous cell carcinomas using log-linear regression and age period-cohort modeling. RESULTS: In total, 156 567 oropharyngeal cancer, 146 693 oral cavity cancer, and 621 947 lung squamous cell carcinoma patients were included. Oropharyngeal cancer incidence increased (P < .05) in 19 and 23 countries in men and women, respectively. In countries with increasing male oropharyngeal cancer incidence, all but 1 had statistically significant decreases in lung squamous cell carcinoma incidence, and all but 2 had decreasing or nonsignificant net drifts for oral cavity cancer. Increased oropharyngeal cancer incidence was observed both in middle-aged (40-59 years) and older (≥60 years) male cohorts, with strong nonlinear birth cohort effects. In 20 countries where oropharyngeal cancer incidence increased for women and age period-cohort analysis was possible, 13 had negative or nonsignificant lung squamous cell carcinoma net drifts, including 4 countries with higher oropharyngeal cancer net drifts vs both lung squamous cell carcinoma and oral cavity cancer (P < .05 for all comparisons). CONCLUSIONS: Increasing oropharyngeal cancer incidence is seen among an expanding array of countries worldwide. In men, increased oropharyngeal cancer is extending to older age groups, likely driven by human papillomavirus-related birth cohort effects. In women, more diverse patterns were observed, suggesting a complex interplay of risks factors varying by country, including several countries where female oropharyngeal cancer increases may be driven by HPV.

Reverse engineering the FRAX algorithm: Clinical insights and systematic analysis of fracture risk.

The Fracture Risk Assessment Tool (FRAX) is a computational tool developed to predict the 10-year probability of hip fracture and major osteoporotic fracture based on inputs of patient characteristics, bone mineral density (BMD), and a set of seven clinical risk factors. While the FRAX tool is widely available and clinically validated, its underlying algorithm is not public. The relative contribution and necessity of each input parameter to the final FRAX score is unknown. We systematically collected hip fracture risk scores from the online FRAX calculator for osteopenic Caucasian women across 473,088 unique inputs. This dataset was used to dissect the FRAX algorithm and construct a reverse-engineered fracture risk model to assess the relative contribution of each input variable. Within the reverse-engineered model, age and T-Score were the strongest contributors to hip fracture risk, while BMI had marginal contribution. Of the clinical risk factors, parent history of fracture and ongoing glucocorticoid treatment had the largest additive effect on risk score. A generalized linear model largely recapitulated the FRAX tool with an R2 of 0.91. Observed effect sizes were then compared to a true patient population by creating a logistic regression model of the Study of Osteoporotic Fractures (SOF) cohort, which closely paralleled the effect sizes seen in the reverse-engineered fracture risk model. Analysis identified several clinically relevant observations of interest to FRAX users. The role of major osteoporotic fracture risk prediction in contributing to an indication of treatment need is very narrow, as the hip fracture risk prediction accounted for 98% of treatment indications for the SOF cohort. Removing any risk factor from the model substantially decreased its accuracy and confirmed that more parsimonious models are not ideal for fracture prediction. For women 65 years and older with a previous fracture, 98% of FRAX combinations exceeded the treatment threshold, regardless of T-score or other factors. For women age 70+ with a parent history of fracture, 99% of FRAX combinations exceed the treatment threshold. Based on these analyses, we re-affirm the efficacy of the FRAX as the best tool for fracture risk assessment and provide deep insight into the interplay between risk factors.