Major cardiovascular events in long-term multiple myeloma survivors: a Korean case-control study (the CAREMM-2105 study).

PURPOSE: Despite improvements in multiple myeloma (MM) survival rates, data on cardiovascular outcomes in long-term survivors remain lacking. METHODS: This retrospective case-control study utilized the Korean National Health Insurance Service database (2009-2020) to compare the incidence of cardiovascular disease (CVD) between patients with MM and a matched control group, focusing on long-term (> 5 years) survivors. A preliminary case cohort (n = 15,402 patients with MM) and a matched control cohort (n = 123,216 patients without MM) were established based on birth year and sex. Following 1:1 propensity score matching, the final matched cohorts each comprised 15,402 participants. RESULTS: The case and control cohorts were comparable in mean age (66.2 ± 11.5 years vs. 66.1 ± 11.3 years), sex, age distribution, and comorbidities. By the 8-year follow-up, the cumulative incidence of CV events (12.5% vs. 22.1%) and CVD risk were significantly lower in the case cohort. The 5-year landmark analysis revealed significant differences in CVD incidence between the cohorts (7.8% [case cohort] vs. 9.8% [control cohort]), with variations across age groups and sex, highlighting a significantly higher CVD risk among patients aged < 50 years in the case cohort (P < 0.001). CONCLUSIONS: These findings underscore the need for vigilant CVD monitoring in MM long-term survivors, particularly those aged < 50 years at first diagnosis. IMPLICATION FOR CANCER SURVIVORS: This study highlights the importance of integrating cardiovascular monitoring and risk management into long-term care for MM survivors, with a focus on younger patients and personalized interventions.

Do Weight Changes Affect the Association between Smoking Cessation and the Risk of Stroke Subtypes in Korean Males?

(1) Background: We investigated whether weight changes affect the association between smoking cessation and stroke risk; (2) Methods: Overall, 719,040 males were categorized into eight groups according to smoking status (sustained smokers, non-smokers, long-term quitters (quit > 4 years), and recent quitters (quit < 4 years)) and post-cessation weight change (-5 kg, -5.0 to 0.1 kg, maintainers, 0.1-5.0 kg, and >5.0 kg). The hazard ratios (HR) and 95% confidence intervals (CI) for incident total, ischemic, and hemorrhagic strokes, including subarachnoid and intracerebral hemorrhage, were calculated using Cox proportional hazard models; (3) Results: We detected 38,730 strokes (median follow-up, 25.7 years), including 30,609 ischemic and 9055 hemorrhagic strokes. For recent quitters with a >5.0 kg or 0.1-5.0 kg weight increase, maintainers, or those who lost 0.1-5 kg, the multivariable HR for total stroke was 0.73 (95% CI, 0.67-0.79), 0.78 (95% CI, 0.74-0.82), 0.77 (95% CI, 0.69-0.85), 0.84 (95% CI, 0.77-0.90), and 1.06 (95% CI, 0.92-1.23), respectively, compared with that of sustained smokers; (4) Conclusions: Comparable patterns were obtained for stroke subtypes. Thus, we strongly recommend quitting smoking, as weight gain after quitting smoking does not alter the stroke-related benefits.

Prediction of cancer survivors' mortality risk in Korea: a 25-year nationwide prospective cohort study.

OBJECTIVES: This study aimed to investigate the factors affecting cancer survival and develop a mortality prediction model for Korean cancer survivors. Our study identified lifestyle and mortality risk factors and attempted to determine whether health-promoting lifestyles affect mortality. METHODS: Among the 1,637,287 participants in the Korean Cancer Prevention Study (KCPS) cohort, 200,834 cancer survivors who were alive after cancer diagnosis were analyzed. Discrimination and calibration for predicting the 10-year mortality risk were evaluated. A prediction model was derived using the Cox model coefficients, mean risk factor values, and mean mortality from the cancer survivors in the KCPS cohort. RESULTS: During the 21.6-year follow-up, the all-cause mortality rates of cancer survivors were 57.2% and 39.4% in men and women, respectively. Men, older age, current smoking, and a history of diabetes were high-risk factors for mortality, while exercise habits and a family history of cancer were associated with reduced risk. The prediction model discrimination in the validation dataset for both KCPS all-cause mortality and KCPS cancer mortality was shown by C-statistics of 0.69 and 0.68, respectively. Based on the constructed prediction models, when we modified exercise status and smoking status, as modifiable factors, the cancer survivors' risk of mortality decreased linearly. CONCLUSIONS: A mortality prediction model for cancer survivors was developed that may be helpful in supporting a healthy life. Lifestyle modifications in cancer survivors may affect their risk of mortality in the future.