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Biomedical subjects

Mark A Jenkins

Publications and source records attributed to Mark A Jenkins.

2 recordsLinked to original sources

Early-onset colorectal cancer burden attributable to early-life obesity from 2000 to 2020 with projections to 2040.

PURPOSE: Early-onset colorectal cancer (age <50 years) incidence has increased globally since the 1990s for unknown reasons. Early-life exposure to established risk factors like adiposity is suspected to play a role, but the contribution to the rising disease burden remains unknown. This study quantified the potential impact of rising early-life obesity on early-onset colorectal cancer in Australia. METHODS: Population attributable fractions for early-onset colorectal cancer were derived from meta-analytic relative risks and obesity prevalence estimates in adolescents (10-19-year-olds), using body mass index data for 1990-2022 from the Noncommunicable Diseases Risk Factor Collaboration. Under age-specific carcinogenesis latency assumptions, we linked adolescent obesity prevalence estimates to colorectal cancer incidence across age groups (20-29, 30-39, and 40-49 years) using observed cancer incidence data from Australian cancer registries covering 2000-2019 and age-period-cohort modelling to generate scenario-based estimates of incidence and obesity-attributable cases through 2040. Trends in obesity-attributable colorectal cancer incidence were quantified using joinpoint regression. RESULTS: The proportion of early-onset colorectal cancers attributable to adolescent obesity across 1990-2022 rose from 2% to 6% in men and 1-3% in women (average annual change: 3-4%). Although absolute attributable incidence rates were low, they increased 2-20% per year, varying by period, age-dependent lag, and sex. Under the projection assumptions applied, scenario estimates suggest that adolescent obesity could account for an estimated 1465 early-onset cases by 2040. CONCLUSION: Early-life obesity is estimated to account for a growing yet minor fraction of early-onset colorectal cancers in Australia and is therefore unlikely to be a major driver of the rising disease incidence. These findings suggest that childhood obesity prevention programs may have only a small public health impact on early-onset colorectal cancer prevention. Therefore, it is imperative that other causal risk factors - especially early-life exposures - are identified to inform prevention strategies that stem the rising disease burden.

Obesity

A prediction model for metachronous colorectal cancer: development and validation.

BACKGROUND: Being able to estimate the risk of metachronous disease in a patient with colorectal cancer (CRC) could enable risk-appropriate surveillance. The aim of this study was to develop a risk-prediction model to estimate individual 10-year risk of metachronous disease following a CRC diagnosis. METHODS: A population-based cohort of patients with CRC was recruited soon after diagnosis between 1997 and 2012 from the United States, Canada, and Australia. Cox regression with the least absolute shrinkage and selection operator penalization was used to identify factors that predicted the risk of a new primary CRC diagnosed at least 1 year after the initial CRC diagnosis. Potential predictors included demography, anthropometry, lifestyle factors, comorbidities, personal and family cancer history, medication use, age at diagnosis, and pathological features of the first CRC. Internal validation through bootstrapping was used to evaluate the discrimination and calibration. RESULTS: We included 6085 CRC cases; 138 (2.3%) of these cases were diagnosed with metachronous disease over a median of 12&#x2009;years (IQR&#x2009;=&#x2009;5-17&#x2009;years). Metachronous CRC risk was predicted by body mass index; smoking status; level of physical activity; family history of cancer and synchronous CRC; stage, grade, histological type, and DNA mismatch repair status; and age at diagnosis of the first CRC. The model was valid with a C statistic of 0.65 (95% CI&#x2009;=&#x2009;0.63 to 0.68) and a calibration slope of 0.873 (SD = 0.087). CONCLUSIONS: Metachronous CRC can be predicted with reasonable accuracy using a prediction model that consists of clinical variables collected as part of routine practice.

Humans