Physical activity and body mass index (BMI) are well established risk factors of colorectal cancer. Whether physical activity can counteract adverse obesity-induced metabolic profiles, including inflammation, remains unclear. Using data from the ColoCare Study, Himbert and colleagues tested associations of individual and combined physical activity and BMI groups with pro-inflammatory biomarkers in the largest cohort of colorectal cancer patients to date. The authors identified BMI as the key driver of inflammation, yet, biomarker levels were higher among inactive colorectal cancer patients across BMI groups. Results suggest that physical activity may reduce obesity-induced inflammation among colorectal cancer patients.Hodgkin lymphoma (HL) survivors (HLS) treated with infradiaphragmatic radiotherapy (IRT) and/or procarbazine have an increased risk of developing colorectal cancer (CRC). Ykema, Gini, and colleagues investigated the cost-effectiveness of CRC surveillance in Dutch HLS to determine the optimal surveillance strategy for different HL subgroups. The authors adjusted well-established MISCANColon model to reflect the HL survivor population. Subsequently the model was used to evaluate benefits, harms and costs of a range of potential surveillance strategies. CRC surveillance in HL survivors at increased risk for CRC (treated with IRT and/or procarbazine-containing chemotherapy) is cost-effective and should commence earlier than in the general population. For all examined HL subgroups, FIT surveillance was the most cost-effective strategy.Multiple myeloma disproportionately affects individuals of African descent, occurring more often in Black populations compared to White. Cicero and colleagues investigated the prevalence of monoclonal gammopathy of undetermined significance (MGUS), the precursor to myeloma, in 386 Black South African men. They found MGUS in 8.03% of their cohort, nearly 1.6-fold higher than the historic White Olmsted County males. Moreover, they explored the association between MGUS and various clinical factors, notably determining a correlation between MGUS and HIV status, as well as cigarette use. Their study demonstrates that racial disparities in MGUS exist and may be associated with potentially modifiable risk factors.This study by Chien and colleagues proposed methods for adapting risk models, with or without polygenic score, for another population without prospective cohorts to help alleviate the health disparities caused by advances in absolute risk models. The authors adapted the lung cancer risk model PLCOM2012 for Taiwan, by forming an age-matched case-control study of ever-smokers, synthesizing a dataset resembling the population of cancer-free ever-smokers in 2010, and estimating the number of ever-smoking lung cancer patients in 2011–2016. The adapted PLCOT models had high performance in calibration, discrimination, and clinical usefulness, and could be used to counsel individuals and design screening programs in Taiwan. The methods could be applicable to other cancer models.