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People with physical diseases are reported to be at elevated risk of subsequent mental disorders. However, previous studies have considered only a few pairs of conditions, or have reported only relative risks. This study aimed to systematically explore the associations between physical diseases and subsequent mental disorders. It examined a population-based cohort of 7,673,978 people living in Denmark between 2000 and 2021, and followed them for a total of 119.3 million person-years. The study assessed nine broad categories of physical diseases (cardiovascular, endocrine, respiratory, gastrointestinal, urogenital, musculoskeletal, hematological and neurological diseases, and cancers), encompassing 31 specific diseases, and the subsequent risk of mental disorder diagnoses, encompassing the ten ICD-10 groupings (organic, including symptomatic, mental disorders; mental disorders due to psychoactive substance use; schizophrenia and related disorders; mood disorders; neurotic, stress-related and somatoform disorders; eating disorders; personality disorders; intellectual disabilities; pervasive developmental disorders; and behavioral and emotional disorders with onset usually occurring in childhood and adolescence). Using Poisson regression, the overall and time-dependent incidence rate ratios (IRRs) for pairs of physical diseases and mental disorders were calculated, adjusting for age, sex and calendar time. Absolute risks were estimated with the Aalen-Johansen estimator. In total, 646,171 people (8.4%) were identified as having any mental disorder during follow-up. All physical diseases except cancers were associated with an elevated risk of any mental disorder. For the nine broad pairs of physical diseases and mental disorders, the median point estimate of IRR was 1.51 (range: 0.99-1.84; interquartile range: 1.29-1.59). The IRRs ranged from 0.99 (95% CI: 0.98-1.01) after cancers to 1.84 (95% CI: 1.83-1.85) after musculoskeletal diseases. Risks varied over time after the diagnosis of physical diseases. The cumulative mental disorder incidence within 15 years after diagnosis of a physical disease varied from 3.73% (95% CI: 3.67-3.80) for cancers to 10.19% (95% CI: 10.13-10.25) for respiratory diseases. These data document that most physical diseases are associated with an elevated risk of subsequent mental disorders. Clinicians treating physical diseases should constantly be alert to the possible development of secondary mental disorders., (© 2024 World Psychiatric Association.)

Background: Predicting cause-specific mortality among people with HIV (PWH) could facilitate targeted care to improve survival. We assessed discrimination of the Veterans Aging Cohort Study (VACS) Index 2.0 in predicting cause-specific mortality among PWH on antiretroviral therapy (ART)., Methods: Using Antiretroviral Therapy Cohort Collaboration data for PWH who initiated ART between 2000 and 2018, VACS Index 2.0 scores (higher scores indicate worse prognosis) were calculated around a randomly selected visit date at least 1 year after ART initiation. Missingness in VACS Index 2.0 variables was addressed through multiple imputation. Cox models estimated associations between VACS Index 2.0 and causes of death, with discrimination evaluated using Harrell's C-statistic. Absolute mortality risk was modelled using flexible parametric survival models., Results: Of 59 741 PWH (mean age: 43 years; 80% male), the mean VACS Index 2.0 at baseline was 41 (range: 0-129). For 2425 deaths over 168 162 person-years follow-up (median: 2.6 years/person), AIDS (n = 455) and non-AIDS-defining cancers (n = 452) were the most common causes. Predicted 5-year mortality for PWH with a mean VACS Index 2.0 score of 38 at baseline was 1% and approximately doubled for every 10-unit increase. The 5-year all-cause mortality C-statistic was .83. Discrimination with the VACS Index 2.0 was highest for deaths resulting from AIDS (0.91), liver-related (0.91), respiratory-related (0.89), non-AIDS infections (0.87), and non-AIDS-defining cancers (0.83), and lowest for suicides/accidental deaths (0.65)., Conclusions: For deaths among PWH, discrimination with the VACS Index 2.0 was highest for deaths with measurable physiological causes and was lowest for suicide/accidental deaths., Competing Interests: Potential conflicts of interest. A.v.S. has received grants unrelated to this study and paid to his institution from ECDC. H.C. has received research grant funding from ViiV, NIH, and AHRQ paid to their institution, and has sat on the NIH Office of AIDS Research Advisory Council. N.P. has received grants unrelated to this study and paid to his institution from Gilead Sciences Hellas and ECDC. M.C.'s institution received research grants and expert opinion fees from Gilead, MSD, and Viiv. P.D. reports consulting fees from Gilead, Merck, Janssen and Cilag, ViiV Healthcare, Roche, and Theratechnologies; and payment or honoraria for lectures from Gilead, Merck, Janssen, ViiV Healthcare, and Roche. I.J. has received teaching fees from ViiV, fees for evaluating scientific projects and participating in expert panels from Gilead, and fees for statistical analyses from GESIDA. M.J.G. has received honoraria in the past 3 years from ad hoc membership of national HIV advisory boards, Merck, Gilead, and ViiV. J.B. reports honoraria for advice or public speaking from Gilead, GSK, Janssen, MSD, and ViiV Healthcare; and grants from Gilead, MSD, and ViiV Healthcare. C.W. reports honoraria for advice or public speaking from Abbott, Gilead, Janssen, MSD, Pfizer, and ViiV Healthcare. P.R., through his institution, has received scientific grant support for investigator-initiated studies from Gilead Sciences, Janssen Pharmaceuticals Inc, Merck & Co, and ViiV Healthcare, and has served on scientific advisory boards for Gilead Sciences, ViiV Healthcare, and Merck & Co honoraria for which were all paid to his institution. All other authors report no potential conflicts., (© The Author(s) 2024. Published by Oxford University Press on behalf of Infectious Diseases Society of America.)

Background: Alcohol intake is associated with breast cancer (BC) risk, but estimates of greatest public health relevance have not been quantified in large studies with long duration. Materials and Methods: In this prospective cohort study of 39,811 women (median 25 years follow-up), we examined the association between alcohol consumption and BC incidence and mortality with adjusted hazard ratios (HRs), cubic splines, absolute risks, number needed to harm (NNH), and population-attributable fractions. Results: We documented 2,830 cases of BC, including 237 BC deaths. Each additional alcoholic drink/day was associated with a 10% higher rate (HR = 1.10, 95% confidence intervals [CIs]: 1.04-1.16) of total BC in a linear manner ( p  = 0.0004). The higher rate was apparent for estrogen receptor (ER) + (HR = 1.12, 95% CI: 1.06-1.18) but not ER - tumors (HR = 0.95, 95% CI: 0.82-1.10), with a statistically significant difference between these associations ( p  = 0.03). We constructed models comparing BC incidence among 100,000 women followed for 10 years. Compared to a scenario where all women rarely or never consumed alcohol, we expect 63.79 (95% CI: 58.35-69.24) more cases (NNH = 1,567) had all women consumed alcohol at least monthly and 278.66 (95% CI: 268.70-288.62) more cases (NNH = 358) had all women consumed >1 drink/day. Approximately 4.1% of BC cases were attributable to consumption exceeding one drink/month. Conclusion: Alcohol consumption is associated with a linear dose-response increase in BC incidence even within recommended limits of up to one alcoholic drink/day, at least for ER + tumors. Our estimates of risk differences, attributable fraction, and NNH quantify the burden that alcohol consumption imposes on women in the general population. ClinicalTrials.gov Identifier: NCT00000479.

Background and Aim: People with new-onset diabetes mellitus (diabetes) could be a possible target population for pancreatic cancer surveillance. However, distinguishing diabetes caused by pancreatic cancer from type 2 diabetes remains challenging. We aimed to develop and validate a model to predict pancreatic cancer among women with new-onset diabetes., Methods: We conducted a retrospective cohort study among Australian women newly diagnosed with diabetes, using first prescription of anti-diabetic medications, sourced from administrative data, as a surrogate for the diagnosis of diabetes. The outcome was a diagnosis of pancreatic cancer within 3 years of diabetes diagnosis. We used prescription medications, severity of diabetes (i.e., change/addition of medication within 2 months after first medication), and age at diabetes diagnosis as potential predictors of pancreatic cancer., Results: Among 99 687 women aged ≥ 50 years with new-onset diabetes, 602 (0.6%) were diagnosed with pancreatic cancer within 3 years. The area under the receiver operating curve for the risk prediction model was 0.73. Age and diabetes severity were the two most influential predictors followed by beta-blockers, acid disorder drugs, and lipid-modifying agents. Using a risk threshold of 50%, sensitivity and specificity were 69% and the positive predictive value (PPV) was 1.3%., Conclusions: Our model doubled the PPV of pancreatic cancer in women with new-onset diabetes from 0.6% to 1.3%. Age and rapid progression of diabetes were important risk factors, and pancreatic cancer occurred more commonly in women without typical risk factors for type 2 diabetes. This model could prove valuable as an initial screening tool, especially as new biomarkers emerge., (© 2024 The Authors. Journal of Gastroenterology and Hepatology published by Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.)

Background: Genetic, lifestyle, reproductive, and anthropometric factors are associated with the risk of developing breast cancer. However, it is not yet known whether polygenic risk score (PRS) and absolute risk based on a combination of risk factors are associated with the risk of progression of breast cancer. This study aims to estimate the distribution of sojourn time (pre-clinical screen-detectable period) and mammographic sensitivity by absolute breast cancer risk derived from polygenic profile and the other risk factors., Methods: The authors used data from a population-based case-control study. Six categories of 10-year absolute risk based on different combinations of risk factors were derived using the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm. Women were classified into low, medium, and high-risk groups. The authors constructed a continuous-time multistate model. To calculate the sojourn time, they simulated the trajectories of subjects through the disease states., Results: There was little difference in sojourn time with a large overlap in the 95% confidence interval (CI) between the risk groups across the six risk categories and PRS studied. However, the age of entry into the screen-detectable state varied by risk category, with the mean age of entry of 53.4 years (95% CI, 52.2-54.1) and 57.0 years (95% CI, 55.1-57.7) in the high-risk and low-risk women, respectively., Conclusion: In risk-stratified breast screening, the age at the start of screening, but not necessarily the frequency of screening, should be tailored to a woman's risk level. The optimal risk-stratified screening strategy that would improve the benefit-to-harm balance and the cost-effectiveness of the screening programs needs to be studied., (© 2024 The Authors. Cancer published by Wiley Periodicals LLC on behalf of American Cancer Society.)

We compared methods to project absolute risk, the probability of experiencing the outcome of interest in a given projection interval accommodating competing risks, for a person from the target population with missing predictors. Without missing data, a perfectly calibrated model gives unbiased absolute risk estimates in a new target population, even if the predictor distribution differs from the training data. However, if predictors are missing in target population members, a reference dataset with complete data is needed to impute them and to estimate absolute risk, conditional only on the observed predictors. If the predictor distributions of the reference data and the target population differ, this approach yields biased estimates. We compared the bias and mean squared error of absolute risk predictions for seven methods that assume predictors are missing at random (MAR). Some methods imputed individual missing predictors, others imputed linear predictor combinations (risk scores). Simulations were based on real breast cancer predictor distributions and outcome data. We also analyzed a real breast cancer dataset. The largest bias for all methods resulted from different predictor distributions of the reference and target populations. No method was unbiased in this situation. Surprisingly, violating the MAR assumption did not induce severe biases. Most multiple imputation methods performed similarly and were less biased (but more variable) than a method that used a single expected risk score. Our work shows the importance of selecting predictor reference datasets similar to the target population to reduce bias of absolute risk predictions with missing risk factors., Competing Interests: Declaration of conflicting interestsThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Background and Aims: Knowledge of quantifiable cardiovascular disease (CVD) risk may improve health outcomes and trigger behavioural change in patients or clinicians. This review aimed to investigate the impact of CVD risk communication on patient-perceived CVD risk and changes in CVD risk factors., Methods: PubMed, Embase, and PsycINFO databases were searched from inception to 6 June 2023, supplemented by citation analysis. Randomized trials that compared any CVD risk communication strategy versus usual care were included. Paired reviewers independently screened the identified records and extracted the data; disagreements were resolved by a third author. The primary outcome was the accuracy of risk perception. Secondary outcomes were clinician-reported changes in CVD risk, psychological responses, intention to modify lifestyle, and self-reported changes in risk factors and clinician prescribing of preventive medicines., Results: Sixty-two trials were included. Accuracy of risk perception was higher among intervention participants (odds ratio = 2.31, 95% confidence interval = 1.63 to 3.27). A statistically significant improvement in overall CVD risk scores was found at 6-12 months (mean difference = -0.27, 95% confidence interval = -0.45 to -0.09). For primary prevention, risk communication significantly increased self-reported dietary modification (odds ratio = 1.50, 95% confidence interval = 1.21 to 1.86) with no increase in intention or actual changes in smoking cessation or physical activity. A significant impact on patients' intention to start preventive medication was found for primary and secondary prevention, with changes at follow-up for the primary prevention group., Conclusions: In this systematic review and meta-analysis, communicating CVD risk information, regardless of the method, reduced the overall risk factors and enhanced patients' self-perceived risk. Communication of CVD risk to patients should be considered in routine consultations., (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Objective: To investigate associations of self-reported walking pace (SRWP) with relative and absolute risks of cause-specific mortality., Patients and Methods: In 391,652 UK Biobank participants recruited in 2006-2010, we estimated sex- and cause-specific (cardiovascular disease [CVD], cancer, other causes) mortality hazard ratios (HRs) and 10-year mortality risks across categories of SRWP (slow, average, brisk), accounting for confounders and competing risk. Censoring occurred in September 30, 2021 (England, Wales) and October 31, 2021 (Scotland)., Results: Over a median follow-up of 12.6 years, 22,413 deaths occurred. In women, the HRs comparing brisk to slow SRWP were 0.74 (95% CI: 0.67, 0.82), 0.40 (0.33, 0.49), and 0.29 (0.26, 0.32) for cancer, CVD, and other causes of death, respectively, and 0.71 (0.64, 0.78), 0.38 (0.33, 0.44), and 0.29 (0.26, 0.32) in men. Compared to CVD, HRs were greater for other causes (women: 39.6% [6.2, 72.9]; men: 31.6% [9.8, 53.5]) and smaller for cancer (-45.8% [-58.3, -33.2] and - 45.9% [-54.8, -36.9], respectively). For all causes in both sexes, the 10-year mortality risk was higher in slow walkers, but varied across sex, age, and cause, resulting in different risk reductions comparing brisk to slow: the largest were for other causes of death at age 75 years [women: -6.8% (-7.7, -5.8); men: -9.5% (-10.6, -8.4)]., Conclusion: Compared to slow walkers, brisk SRWP was associated with reduced cancer (smallest reduction), CVD, and other (largest) causes of death and may therefore be a useful clinical predictive marker. As absolute risk reductions varied across age, cause, and SRWP, certain groups may particularly benefit from interventions to increase SRWP., Competing Interests: Declaration of Competing Interest The authors had financial support from the funders listed above for the submitted work. The authors declare that they have no competing interests., (Copyright © 2023. Published by Elsevier Inc.)

Background: Attitudes towards smoking, lung cancer screening, and perceived risk of lung cancer have not been widely studied in Malaysia. The primary objective of this study was to describe the factors affecting the willingness of high-risk current smokers and ex-smokers to undergo low-dose computed tomography (LDCT) screening for lung cancer., Methods: A prospective, cross-sectional questionnaire study was conducted in current smokers or ex-smokers aged between 55 and 80 years at three hospitals in Kota Kinabalu, Sabah, Malaysia. The questionnaire recorded the following parameters: perceived lung cancer risk; Prostate Lung Colon Ovarian Cancer 2012 risk prediction model excluding race and ethnicity predictor (PLCOm2012norace); demographic characteristics; psychosocial characteristics; and attitudes towards lung cancer and lung cancer screening., Results: A vast majority of the 95 respondents (94.7%) indicated their willingness to undergo screening. Stigma of lung cancer, low levels of knowledge about lung cancer symptoms, concerns about financial constraints, and a preference for traditional medication were still prevalent among the respondents, and they may represent potential barriers to lung cancer screening uptake. A desire to have an early diagnosis (odds ratio [OR], 11.33; 95% confidence interval [CI], 1.53 to 84.05; p=0.02), perceived time constraints (OR, 3.94; 95% CI, 1.32 to 11.73; p=0.01), and proximity of LDCT screening facilities (OR, 14.33; 95% CI, 1.84 to 111.4; p=0.01) had significantly higher odds of willingness to undergo screening., Conclusion: Although high-risk current smokers and ex-smokers are likely to undergo screening for lung cancer, several psychosocial barriers persist. The results of this study may guide the policymakers and clinicians regarding the need to improve lung cancer awareness in our population.

Background: The occurrence and development of chronic obstructive pulmonary disease (COPD) are regulated by environmental and genetic factors. In hypoxia, Erythropoietin ( EPO ) satisfies the body's need for oxygen by promoting the production of red blood cells. Hypoxia was proven to be a common physiological condition in COPD progression and associated with many complications. Some studies have found that EPO is involved in the development of COPD. But the mechanism has not been fully proven., Methods: We conducted a case-control study enrolled 1095 COPD patients and 1144 healthy controls in Guangdong Province to evaluate the association between EPO polymorphisms (rs1617640 A>C, rs507392 A>G, rs564449 G>T) and COPD susceptibility. 872 participants from southern Gansu Province were recruited to verify the effect of EPO polymorphisms on lung function., Results: EPO rs1617640 C allele reduced COPD susceptibility in southern Chinese significantly (AC vs. AA: adjusted Odds ratio (OR) = 0.805, 95% CI = 0.669-0.969; AC+CC vs. AA: adjusted OR = 0.822, 95% CI = 0.689-0.980). However, there was no association between rs507392 A>G and rs564449 G>T polymorphisms and COPD susceptibility ( p > 0.05). We further observed that the rs1617640 C allele was associated with higher FEV1 and FVC in Guangdong and Gansu populations significantly (both p < 0.05). In brief, the level of FEV1 and FVC increased with the C allele number. We modeled the relative risk for men and women, in which the population-attributable risks chances were 0.449 (0.258-0.641) and 0.262 (0.128-0.396) respectively. In this model, smoking status, coal as fuels, education level, and rs1617640 A>C were finally retained for males, while smoking status, biomass as fuels, and1617640 A>C were retained for females. In the end, using the method developed by Gail and Bruzzi, we fitted a 10-year absolute risk model for southern Chinese with different individual relative risks, which was presented as a table., Conclusions: In conclusion, this study found that EPO rs1617640 A>C polymorphism is associated with COPD susceptibility in southern Chinese, and the C allele was associated with better lung function. In addition, it could also be considered a genetic marker associated with environmental factors to predict the absolute 10-year risk of COPD in southern Chinese., Competing Interests: The authors declare no conflict of interest., (© 2023 The Author(s). Published by IMR Press.)

Objective: COPD is the most common chronic respiratory disease with complex environmental and genetic etiologies. It was reported that EPAS1 might participate in the occurrence and development of respiratory diseases. However, the association between EPAS1 and COPD was unclear., Methods: First, a case-control study enrolling 1130 COPD patients and 1115 healthy controls in Guangzhou was conducted to clarify the association between EPAS1 polymorphisms and COPD susceptibility. Secondly, a prevalence study recruited 882 participants in Gansu to verify the effect of positive polymorphisms on lung function. Finally, the 10-year absolute risk considering environmental factors and genetic variations was calculated by the method of Gail and Bruzzi., Results: EPAS1 rs13419896 AA genotype reduced COPD risk in southern Chinese (AA vs. GG: adjusted OR = 0.689, 95% CI = 0.498-0.955; AA vs. GG/GA: adjusted OR = 0.701, 95% CI = 0.511-0.962). Further, the rs13419896 A allele was significantly associated with higher pre-FEV1/pre-FVC in both the Guangzhou and Gansu populations ( P  < 0.05). Smoking status, coal as fuels, education level, and rs13419896 G > A were finally retained to develop a relative risk model for males. Smoking status, biomass as fuels, and rs13419896 G > A were retained in the female model. The population-attributable risk of the male or female model was 0.457 (0.283-0.632) and 0.421 (0.227-0.616), respectively., Conclusions: This study first revealed that EPAS1 rs13419896 G > A decreased COPD susceptibility and could be a genetic marker to predict the 10-year absolute risk for COPD., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors.)

This article reviews the risk equations recommended for use in international cardiovascular disease (CVD) primary prevention guidelines and assesses their suitability for use in Australia against a set of a priori defined selection criteria. The review and assessment were commissioned by the National Heart Foundation of Australia on behalf of the Australian Chronic Disease Prevention Alliance to inform recommendations on CVD risk estimation as part of the 2023 update of the Australian CVD risk assessment and management guidelines. Selected international risk equations were assessed against eight selection criteria: development using contemporary data; inclusion of established cardiovascular risk factors; inclusion of ethnicity and deprivation measures; prediction of a broad selection of fatal and non-fatal CVD outcomes; population representativeness; model performance; external validation in an Australian dataset; and the ability to be recalibrated or modified. Of the ten risk prediction equations reviewed, the New Zealand PREDICT equation met seven of the eight selection criteria, and met additional usability criteria aimed at assessing the ability to apply the risk equation in practice in Australia., (© 2023 The Authors. Medical Journal of Australia published by John Wiley & Sons Australia, Ltd on behalf of AMPCo Pty Ltd.)

Background: Cutaneous squamous cell carcinoma (cSCC) is a common skin cancer, affecting more than 2 million people worldwide yearly and metastasising in 2-5% of patients. However, current clinical staging systems do not provide estimates of absolute metastatic risk, hence missing the opportunity for more personalised treatment advice. We aimed to develop a clinico-pathological model that predicts the probability of metastasis in patients with cSCC., Methods: Nationwide cohorts from (1) all patients with a first primary cSCC in The Netherlands in 2007-2008 and (2) all patients with a cSCC in 2013-2015 in England were used to derive nested case-control cohorts. Pathology records of primary cSCCs that originated a loco-regional or distant metastasis were identified, and these cSCCs were matched to primary cSCCs of controls without metastasis (1:1 ratio). The model was developed on the Dutch cohort (n = 390) using a weighted Cox regression model with backward selection and validated on the English cohort (n = 696). Model performance was assessed using weighted versions of the C-index, calibration metrics, and decision curve analysis; and compared to the Brigham and Women's Hospital (BWH) and the American Joint Committee on Cancer (AJCC) staging systems. Members of the multidisciplinary Skin Cancer Outcomes (SCOUT) consortium were surveyed to interpret metastatic risk cutoffs in a clinical context., Findings: Eight out of eleven clinico-pathological variables were selected. The model showed good discriminative ability, with an optimism-corrected C-index of 0.80 (95% Confidence interval (CI) 0.75-0.85) in the development cohort and a C-index of 0.84 (95% CI 0.81-0.87) in the validation cohort. Model predictions were well-calibrated: the calibration slope was 0.96 (95% CI 0.76-1.16) in the validation cohort. Decision curve analysis showed improved net benefit compared to current staging systems, particularly for thresholds relevant for decisions on follow-up and adjuvant treatment. The model is available as an online web-based calculator (https://emc-dermatology.shinyapps.io/cscc-abs-met-risk/)., Interpretation: This validated model assigns personalised metastatic risk predictions to patients with cSCC, using routinely reported histological and patient-specific risk factors. The model can empower clinicians and healthcare systems in identifying patients with high-risk cSCC and offering personalised care/treatment and follow-up. Use of the model for clinical decision-making in different patient populations must be further investigated., Funding: PPP Allowance made available by Health-Holland, Top Sector Life Sciences & Health, to stimulate public-private partnerships., Competing Interests: MW participated as speaker/advisory board member/consultant for Sanofi Genzyme, Sunpharma and LEO Pharma. DB is employed by SkylineDx. BRP was employed by SkylineDx before beginning the submitted work (December 2019–July 2021). All other authors declare no competing interests., (© 2023 The Author(s).)

Background: Accurate prostate cancer risk assessment will enable identification of men who are at increased risk of the disease. Using the UK Biobank population-based cohort, we developed and validated a simple model comprising age, family history, and a polygenic risk score (PRS) to predict 5-year risk of prostate cancer., Methods: Eligible participants were unaffected Caucasian men aged 40-69 years at their baseline assessment who had genotyping data available and had completed 6 or more weeks of follow-up. Family history was the number of affected first-degree relatives: 0, 1, or 2+. We used 264 single-nucleotide polymorphisms (SNPs) of a previously developed 269-SNP PRS and population standardized the PRS to have a mean of 1. Age was categorized into 10-year groups: 40-49, 50-59, and 60-69. In a 70% training data set, we used Cox regression with age as the time axis to model family history, PRS, and age group. The model estimates were used with prostate cancer incidences to derive 5-year risks of prostate cancer. Using 5 years of follow-up in a 30% testing data set, the model was tested in terms of its association per quintile of risk, discrimination, and calibration., Results: Of the 198 334 eligible participants, 8996 (4.5%) were diagnosed with incident prostate cancer during follow-up and had a mean age of 67.9 (SD = 5.8) years at diagnosis. The best-fitting model included the PRS, family history, 10-year age group, interactions between age and PRS, and age and family history. In the 30% testing data set with follow-up limited to 5 years, the hazard ratio per SD of 5-year risk was 3.058 (95% confidence interval [CI], 2.720-3.438) and the Harrell's C-index was 0.811 (95% CI, 0.800-0.821). Overall, there were 1088 observed and 1159.1 expected prostate cancers, a standardized incidence ratio of 0.939 (95% CI, 0.885-0.996)., Conclusions: Men at increased risk of prostate cancer could benefit from informed discussions around the risks and benefits of available options for screening for prostate cancer. Although the model was developed in Caucasian men, it can be used with ethnicity-specific polygenic risk and incidence rates for other populations., (© 2023 The Authors. The Prostate published by Wiley Periodicals LLC.)

Objective: The current study explores non-linear effects of absolute risk and effects of comparative risk information about skin cancer on individuals' safety ratings, affective responses and behavioral intentions., Method: An experimental survey was conducted among college students (N = 563) to test the effects of absolute and comparative risk information across a range of risk levels from 3.7% to 60%., Results: The non-linear model of absolute risk effect was confirmed by the data. Absolute risk information had detectable effects at low levels of risk, but the effects did not change appreciably at the highest absolute risk levels. Regarding comparative risk, the data did not support its effects on individuals' safety ratings, affective responses and behavioral intentions., Conclusion: The study found the non-linear model fits well to the skin cancer related feelings and behavioral intentions. It suggests future research apply non-linear models to a variety of health communication areas.

The manner in which clinical trial investigators present their findings to healthcare providers and the public can have a substantial influence on their impact. For example, if a heart attack occurs in 2% of those in the placebo group and in 1% of those in the drug-treated group, the benefit to the treated population is only one percentage point better than no treatment. This finding is unlikely to generate much enthusiasm from the study sponsors and in the reporting of the findings to the public. Instead, trial directors can amplify the magnitude of the appearance of the treatment benefit by using the relative risk (RR) value of a 50% reduction of the risk of a heart attack, since one is 50% of two. By using the RR type of data analysis, clinical trial directors can promote the outcome of their trial in their publication and to the media as highly successful while minimizing or disregarding entirely the absolute risk (AR) reduction of only one percentage point. The practice of expressing the RR without the AR has become routinely deployed in the reporting of findings in many different areas of clinical research. We have provided a historical perspective on how this form of data presentation has become commonplace in the reporting of findings from randomized controlled trials (RCTs) on coronary heart disease (CHD) event monitoring and prevention over the past four decades. We assert that the emphasis on RR coupled with insufficient disclosure of AR in the reporting of RCT outcomes has led healthcare providers and the public to overestimate concerns about high cholesterol and to be misled as to the magnitude of the benefits of cholesterol-lowering therapy. The goal of this review is to prompt the scientific community to address this misleading approach to data presentation., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2023, Diamond et al.)

Personalized breast cancer risk profiling has the potential to promote shared decision-making and improve compliance with routine screening. We assessed the Gail model's performance in predicting the short-term (2- and 5-year) and the long-term (10- and 15-year) absolute risks in 28,234 asymptomatic Asian women. Absolute risks were calculated using different relative risk estimates and Breast cancer incidence and mortality rates (White, Asian-American, or the Singapore Asian population). Using linear models, we tested the association of absolute risk and age at breast cancer occurrence. Model discrimination was moderate (AUC range: 0.580-0.628). Calibration was better for longer-term prediction horizons (E/O long-term ranges : 0.86-1.71; E/O short-term ranges :1.24-3.36). Subgroup analyses show that the model underestimates risk in women with breast cancer family history, positive recall status, and prior breast biopsy, and overestimates risk in underweight women. The Gail model absolute risk does not predict the age of breast cancer occurrence. Breast cancer risk prediction tools performed better with population-specific parameters. Two-year absolute risk estimation is attractive for breast cancer screening programs, but the models tested are not suitable for identifying Asian women at increased risk within this short interval.

Recurrent events can occur more than once in the same individual; such events may be of different types, known as multitype recurrent events. They are very common in longitudinal studies. Often there is a terminating event, after which no further events can occur. The risk of any event, including terminating events such as death or cure, is typically affected by prior events. We propose a flexible joint multitype recurrent-events model that explicitly provides estimates of the change in risk for each event due to subject characteristics, including number and type of prior events and the absolute risk for every event type (terminating and nonterminating), and predicts event-free survival probability over a desired time period. The model is fully parametric, and therefore a standard likelihood function and robust standard errors can be constructed. We illustrate the model with applications to the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (1994-2002) and provide discussion of the results and model features., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: China has the largest burden of esophageal cancer (EC). Prediction models can be used to identify high-risk individuals for intensive lifestyle interventions and endoscopy screening. However, the current prediction models are limited by small sample size and a lack of external validation, and none of them can be embedded into the booming electronic health records (EHRs) in China., Objective: This study aims to develop and validate absolute risk prediction models for EC in the Chinese population. In particular, we assessed whether models that contain only EHR-available predictors performed well., Methods: A prospective cohort recruiting 510,145 participants free of cancer from both high EC-risk and low EC-risk areas in China was used to develop EC models. Another prospective cohort of 18,441 participants was used for validation. A flexible parametric model was used to develop a 10-year absolute risk model by considering the competing risks (full model). The full model was then abbreviated by keeping only EHR-available predictors. We internally and externally validated the models by using the area under the receiver operating characteristic curve (AUC) and calibration plots and compared them based on classification measures., Results: During a median of 11.1 years of follow-up, we observed 2550 EC incident cases. The models consisted of age, sex, regional EC-risk level (high-risk areas: 2 study regions; low-risk areas: 8 regions), education, family history of cancer (simple model), smoking, alcohol use, BMI (intermediate model), physical activity, hot tea consumption, and fresh fruit consumption (full model). The performance was only slightly compromised after the abbreviation. The simple and intermediate models showed good calibration and excellent discriminating ability with AUCs (95% CIs) of 0.822 (0.783-0.861) and 0.830 (0.792-0.867) in the external validation and 0.871 (0.858-0.884) and 0.879 (0.867-0.892) in the internal validation, respectively., Conclusions: Three nested 10-year EC absolute risk prediction models for Chinese adults aged 30-79 years were developed and validated, which may be particularly useful for populations in low EC-risk areas. Even the simple model with only 5 predictors available from EHRs had excellent discrimination and good calibration, indicating its potential for broader use in tailored EC prevention. The simple and intermediate models have the potential to be widely used for both primary and secondary prevention of EC., (©Yuting Han, Xia Zhu, Yizhen Hu, Canqing Yu, Yu Guo, Dong Hang, Yuanjie Pang, Pei Pei, Hongxia Ma, Dianjianyi Sun, Ling Yang, Yiping Chen, Huaidong Du, Min Yu, Junshi Chen, Zhengming Chen, Dezheng Huo, Guangfu Jin, Jun Lv, Zhibin Hu, Hongbing Shen, Liming Li. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 15.03.2023.)

Background: longitudinal evidence concerning frailty phenotype and the risk of cardiovascular disease (CVD) remained insufficient, and whether CVD preventive strategies exert low CVD risk on frail adults is unclear., Objectives: we aimed to prospectively evaluate the association of frailty phenotype, adherence to ideal cardiovascular health (CVH) and their joint associations with the risk of CVD., Methods: a total of 314,093 participants from the UK Biobank were included. Frailty phenotype was assessed according to the five criteria of Fried et al.: weight loss, exhaustion, low physical activity, slow gait speed and low grip strength. CVH included four core health behaviours (smoking, physical activity and diet) and three health factors (weight, cholesterol, blood pressure and glycaemic control). The outcome of interest was incident CVD, including coronary heart disease, heart failure and stroke., Results: compared with the non-frail people whose incident rate of overall CVD was 6.54 per 1,000 person-years, the absolute rate difference per 1,000 person-years was 1.67 (95% confidence interval, CI: 1.33, 2.02) for pre-frail and 5.00 (95% CI: 4.03, 5.97) for frail. The ideal CVH was significantly associated with a lower risk of all CVD outcomes. For the joint association of frailty and CVH level with incident CVD, the highest risk was observed among frailty accompanied by poor CVH with an HR of 2.92 (95% CI: 2.68, 3.18)., Conclusions: our findings indicate that physical frailty is associated with CVD incidence. Improving CVH was significantly associated with a considerable decrease in CVD risk, and such cardiovascular benefits remain for the frailty population., (© The Author(s) 2023. Published by Oxford University Press on behalf of the British Geriatrics Society. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: In this study, we examined the relationship between polygenic liability for depression and number of stressful life events (SLEs) as risk factors for early-onset depression treated in inpatient, outpatient or emergency room settings at psychiatric hospitals in Denmark., Methods: Data were drawn from the iPSYCH2012 case-cohort sample, a population-based sample of individuals born in Denmark between 1981 and 2005. The sample included 18 532 individuals who were diagnosed with depression by a psychiatrist by age 31 years, and a comparison group of 20 184 individuals. Information on SLEs was obtained from nationwide registers and operationalized as a time-varying count variable. Hazard ratios and cumulative incidence rates were estimated using Cox regressions., Results: Risk for depression increased by 35% with each standard deviation increase in polygenic liability ( p < 0.0001), and 36% ( p < 0.0001) with each additional SLE. There was a small interaction between polygenic liability and SLEs ( β = -0.04, p = 0.0009). The probability of being diagnosed with depression in a hospital-based setting between ages 15 and 31 years ranged from 1.5% among males in the lowest quartile of polygenic liability with 0 events by age 15, to 18.8% among females in the highest quartile of polygenic liability with 4+ events by age 15., Conclusions: These findings suggest that although there is minimal interaction between polygenic liability and SLEs as risk factors for hospital-treated depression, combining information on these two important risk factors could potentially be useful for identifying high-risk individuals.

Background and Aims: The SAFEHEART tool has shown good discrimination in predicting cardiovascular events in a bespoke genotyped cohort with familial hypercholesterolaemia (FH). We assessed whether the tool could aid clinical decision making in an English routine care cohort with FH., Methods: A historical (2000-2017) open cohort of 3643 participants aged 18-79 years and ≥6-months since FH diagnosis was derived from the Clinical Practice Research Datalink. Individual 10-year cardiovascular risks were predicted using the SAFEHEART model, with multiple imputation used to manage missing data. Outcomes were the first occurrence of myocardial infarction, coronary revascularisation, ischaemic stroke, carotid revascularisation, peripheral arterial revascularisation, non-traumatic lower limb amputation, or cardiovascular death. Model performance was assessed using standard measures of calibration and discrimination, and decision curve analysis., Results: 147 outcome events were observed over a median 3.73 (IQR 1.59-6.48) years follow-up. While the model had some discriminatory value (Harrell's c-statistic 0.67 (95% CI 0.61-0.72)), observed outcome risks departed substantially from predicted risks. Calibration slopes for men and women by age decile were 10.09 (95% CI 7.40-12.77) and 2.85 (1.25-4.45), respectively. Recalibration-in-the-large led to closer alignment of observed and predicted risks (recalibration slopes 3.48 (2.55-4.41) and 1.14 (0.50-1.79), respectively). Decision curve analysis suggested the recalibrated model had net benefit at predicted risks of 10-30%., Conclusions: The original SAFEHEART model has limited generalisability to the routinely identifiable English primary care FH population. With recalibration it appears to have moderate utility at 10-30% predicted risk. It may have greater validity in more bespoke genetically defined FH populations., Competing Interests: Declaration of interests The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Kausik Ray has acted as a consultant for Amgen, Sanofi, Novartis, Pfizer, AstraZeneca, Boehringer Ingelheim, Novo Nordisk, Kowa, Silence Therapeutics, New Amsterdam, Esperion, Daiichi Sankyo, Bayer, Abbott and Resverlogix; and as a speaker for Novartis, Amgen, Viatris, Pfizer, AstraZeneca, Novo Nordisk, Boehringer Ingelheim, Sanofi. He has received research grants from Amgen, Sanofi, Daiichi Sankyo, Regeneron, and Pfizer through his institution. No conflicts of interest are reported by the other team members., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Aim: To examine sex differences in associations of obesity, type-2 diabetes, hypertension, and atrial fibrillation (AF) with incident cardiovascular disease (CVD), focusing on absolute risk measures., Methods and Results: We included a total of 7994 individuals (mean age 49.1 years; 51.2% women) without prior CVD from the PREVEND (Prevention of Renal and Vascular End-stage Disease) cohort with a median follow-up of 12.5 years. Using Poisson regression, we calculated the increase in absolute as well as relative CVD risk associated with a comorbidity using incidence rate differences (IRD = IR comorbidity -IR no-comorbidity ) and incidence rate ratios (IRR = IR comorbidity /IR no-comorbidity ), respectively. Sex differences were presented as women-to-men differences (WMD = IRD women -IRD men ) and women-to-men ratios (WMR = IRR women /IRR men ). Absolute CVD risk was lower in women than in men (IR women : 6.73 vs. IR men : 14.58 per 1000 person-years). While increase in absolute CVD risk associated with prevalent hypertension was lower in women than in men [WMD: -6.12, 95% confidence interval: (-9.84 to -2.40), P = 0.001], increase in absolute CVD risk associated with prevalent obesity [WMD: -4.25 (-9.11 to 0.61), P = 0.087], type-2 diabetes [WMD: -1.04 (-14.36 to 12.29), P = 0.879] and AF [WMD: 18.39 (-39.65 to 76.43), P = 0.535] did not significantly differ between the sexes. Using relative risk measures, prevalent hypertension [WMR: 1.49%, 95% confidence interval: (1.12-1.99), P = 0.006], type-2 diabetes [WMR: 1.73 (1.09-2.73), P = 0.019], and AF [WMR: 2.53 (1.12-5.70), P = 0.025] were all associated with higher CVD risk in women than in men., Conclusion: Increase in absolute risk of developing CVD is higher in hypertensive men than in hypertensive women, but no substantial sex-related differences were observed among individuals with obesity, type-2 diabetes and AF. On a relative risk scale, comorbidities, in general, confer a higher CVD risk in women than in men., (© The Author(s) 2022. Published by Oxford University Press on behalf of European Society of Cardiology.)

Background: High plasma lipoprotein(a) and high body mass index are both causal risk factors for calcific aortic valve disease., Objectives: This study sought to test the hypothesis that risk of calcific aortic valve disease is the highest when both plasma lipoprotein(a) and body mass index are extremely high., Methods: From the Copenhagen General Population Study, we used information on 69,988 randomly selected individuals recruited from 2003 to 2015 (median follow-up 7.4 years) to evaluate the association between high lipoprotein(a) and high body mass index with risk of calcific aortic valve disease., Results: Compared with individuals in the 1st to 49th percentiles for both lipoprotein(a) and body mass index, the multivariable adjusted HRs for calcific aortic valve disease were 1.6 (95% CI: 1.3-1.9) for the 50th to 89th percentiles of both (16% of all individuals) and 3.5 (95% CI: 2.5-5.1) for the 90th to 100th percentiles of both (1.1%) (P for interaction = 0.92). The 10-year absolute risk of calcific aortic valve disease increased with higher lipoprotein(a), body mass index, and age, and was higher in men than in women. For women and men 70-79 years of age with body mass index ≥30.0 kg/m 2 , 10-year absolute risks were 5% and 8% for lipoprotein(a) ≤42 mg/dL (88 nmol/L), 7% and 11% for 42-79 mg/dL (89-169 nmol/L), and 9% and 14% for lipoprotein(a) ≥80 mg/dL (170 nmol/L), respectively., Conclusions: Extremely high lipoprotein(a) levels and extremely high body mass index together conferred a 3.5-fold risk of calcific aortic valve disease. Ten-year absolute risk of calcific aortic valve disease by categories of lipoprotein(a) levels, body mass index, age, and sex ranged from 0.4% to 14%., Competing Interests: Funding Support and Author Disclosures This work was supported by Herlev and Gentofte Hospital, Copenhagen University Hospital, Denmark; the Novo Nordisk Foundation (grant NNF18OC0052893), Denmark; and Chief Physician Johan Boserup and Lise Boserup‘s Fund, Denmark. The Copenhagen General Population Study is supported by the Copenhagen County Foundation and Herlev and Gentofte Hospital, Copenhagen University Hospital, Denmark. Dr Kamstrup has served as a consultant for Silence Therapeutics. Dr Nordestgaard has served as a consultant and lecturer for AstraZeneca, Sanofi, Regeneron, Akcea, Amgen, Kowa, Denka, Amarin, Novartis, Novo Nordisk, Silence Therapeutics, and Esperion. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2022 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Several vaccines are being developed as part of the COVID-19 pandemic. The results of clinical trials for these vaccines were published with efficacy values of more than 90%, using mainly relative risk (RR). In this paper, we decided to reanalyse the data using the different validated methods of risk expression. Using main publications, absolute risks (AR), AR reduction (ARR), number needed to treat (NNT) were calculated for five COVID-19 vaccines (tozinameran Comirnaty®, Moderna, Vaxzevria®, Janssen, and Sputnik V vaccines). AR, ARR, NNT, and RR values varied according to COVID-19 vaccines. The order of the different vaccines was not the same according to the chosen efficacy parameters. This is a further example of the need to express results of clinical trials, using not only RR, but also AR, ARR, and NNT in order to clearly present the clinical interest of drugs., (© 2021 Société Française de Pharmacologie et de Thérapeutique.)

Background: This study aims to identify predictors of self-perceived risk of myocardial infarction (MI)., Methods: Among 564 men and women (50-65 years; randomly selected from the Swedish population), we assessed risk perception as relative self-perceived risk compared to others (lower, same, higher) and percentage ten-year absolute risk. Predictors (added blockwise) were identified using multinomial or linear regression, providing odds ratios (ORs) or β coefficients with their 95% confidence intervals (CI)., Results: The mean of self-perceived 10-year MI risk was 12%. Lower BMI (AOR 0.57, 95% CI: 0.44-0.75), low stress (AOR 2.51, 95% CI: 1.39-4.52), high level of physical activity (AOR 1.66, 95% CI:1.01-2.74), hypertension (AOR 0.42, 95% CI: 0.23-0.76), family history (AOR 0.38, 95% CI: 0.21-0.69), and poor general health (AOR 0.41, 95% CI: 0.19-0.89) predicted if respondents perceived their MI risk as lower. Poor general health (AOR 1.94, 95% CI: 1.01-3.73), family history (AOR 2.72, 95% CI: 1.57-4.72), and high cholesterol (AOR 2.45, 95% CI: 1.18-5.09) predicted if respondents perceived their MI risk as higher. Low level of self-perceived CVD knowledge and low numeracy predicted if respondents perceived their MI risk as the same as others. High cholesterol (B 6.85, 95% CI: 2.47-11.32) and poor general health (B 8.75, 95% CI: 4.58-13.00) predicted a higher percentage of perceived ten-year risk., Conclusion: General health was a common predictor of self-perceived MI risk. Lifestyle factors (BMI, physical activity) and stress dominated the predictors for perceiving MI risk as lower than others, while high cholesterol predicted perception of high risk., Competing Interests: None., (© 2022 The Authors. Published by Elsevier B.V.)

Predicting risks of chronic diseases has become increasingly important in clinical practice. When a prediction model is developed in a cohort, there is a great interest to apply the model to other cohorts. Due to potential discrepancy in baseline disease incidences between different cohorts and shifts in patient composition, the risk predicted by the model built in the source cohort often under- or over-estimates the risk in a new cohort. In this article, we assume the relative risks of predictors are the same between the two cohorts, and propose a novel weighted estimating equation approach to re-calibrating the projected risk for the targeted population through updating the baseline risk. The recalibration leverages the knowledge about survival probabilities for the disease of interest and competing events, and summary information of risk factors from the target population. We establish the consistency and asymptotic normality of the proposed estimators. Extensive simulation demonstrate that the proposed estimators are robust, even if the risk factor distributions differ between the source and target populations, and gain efficiency if they are the same, as long as the information from the target is precise. The method is illustrated with a recalibration of colorectal cancer prediction model.

Differentiated vulvar intraepithelial neoplasia (dVIN) is the precursor of human papillomavirus (HPV)-independent vulvar squamous cell carcinoma (VSCC). Given the rare incidence of dVIN, limited information on the exact cancer risk is available. We systematically reviewed the primary and recurrent VSCC risk in patients with dVIN, as well as the time to cancer development. A systematic search was performed up to July 2021 according to the PRISMA guidelines. Five reviewers independently screened articles on title, abstract and full text, followed by critical appraisal of selected articles using the Quality in Prognostic Studies (QUIPS) tool. Of the 455 screened articles, 7 were included for analysis. The absolute risk for primary VSCC in dVIN varied between 33 and 86%, with a median time to progression to VSCC of 9-23 months. The risk of developing recurrent VSCC in dVIN associated VSCC was 32-94%, with a median time to recurrence of 13-32 months. In conclusion, patients with dVIN have a high risk of developing primary and recurrent VSCC with a short time to cancer progression. Increased awareness, timely recognition, aggressive treatment and close follow-up of HPV-independent vulvar conditions including dVIN is therefore strongly recommended.

Aims: The categories in the comprehensive lipid and risk management guidelines were proposed by the Japan Atherosclerosis Society (JAS Guidelines 2017), which adopted the estimated 10 year absolute risk of coronary artery disease (CAD) incidence in the Suita score. We examined whether those categories were concordant with the degree of arterial stiffness., Methods: In 2014, the cardio-ankle vascular index (CAVI), an arterial stiffness parameter, was measured in 1,972 Japanese participants aged 35-74 years in Tsuruoka City, Yamagata Prefecture, Japan. We examined the mean CAVI and the proportion and odds ratios (ORs) of CAVI ≥ 9.0 on the basis of the following three management classifications using the analysis of variance and logistic regression: "Category I (Low risk)," "Category II (Middle risk)," and "Category III (High risk).", Results: The mean CAVI and proportion of CAVI ≥ 9.0 were 8.6 and 34.8% among males and 8.1 and 18.3% among females, respectively. The mean CAVI and proportion of CAVI ≥ 9.0 were associated with an estimated 10 year absolute risk for CAD among males and females, excluding High risk for females. These results were similar to the management classification by the guideline: the multivariable-adjusted ORs (95% confidence intervals) of CAVI ≥ 9.0 among Category II and Category III compared with those among Category I were 2.96 (1.61-5.43) and 7.33 (4.03-13.3) for males and 3.99 (2.55-6.24) and 3.34 (2.16-5.16) for females, respectively., Conclusions: The risk stratification, which was proposed in the JAS Guidelines 2017, is concordant with the arterial stiffness parameter.

Objectives: Absolute risk and cost-benefit analyses are necessary to guide clinical decision making. The purpose of this study was to evaluate whether clinical recommendations in dermatology publications were supported by adequate evidence. We also assessed whether dermatology residents report sufficient evidence when they author publications., Methods: We analyzed the clinical cohort, case-control, and case series studies published in JAMA Dermatology and the Journal of American Academy of Dermatology from January 2018 to December 2018 for statistical significance, absolute associations, diagnostic and therapeutic clinical recommendations, and risk-benefit analysis. We also identified articles with a U.S. dermatology resident as first or second author., Results: We found that the majority of articles reported statistical significance, but only 3% included absolute risk analyses and none had risk-benefit analysis. Furthermore, 42% of studies with a dermatology resident as a primary author reported statistical significance, but none provided absolute risk or risk-benefit analyses., Conclusions: Reviewers need to be more aware of the evidentiary needs required for clinical recommendations, and dermatology residents may benefit from additional statistics training.

Introduction: The optimal length for clinical follow-up of renal cell carcinoma (RCC) patients is unclear. We evaluated the impact of ISUP/WHO tumor grade and histological subtype on short- and long-term survival and risk of recurrence/metastasis in a large cohort of RCC patients., Patients and Methods: We studied 1679 RCC patients from a single referral center in Italy. Adjusted hazard ratios for overall survival were estimated using Cox regression models. Adjusted absolute risk of developing recurrence or metastasis was computed considering competing risks of mortality., Results: During up to 13 years of follow-up, 175 (10.4%) RCC patients died, of whom 92% beyond 5 years. Hazard ratio of grade IV clear cell carcinomas (ccRCC) was 3.82 compared to grade II. Notably, 33% of recurrences and 56% of distant metastases occurred beyond 5 years of follow-up. The estimated probabilities of recurrence/metastasis were 15% and 45% within and beyond 5 years of follow-up, respectively. After 5 years, the absolute risk of recurrences increased also for papillary renal cell carcinoma type I (35.2%) and grade I ccRCC (17%)., Conclusion: After 5 years of follow-up, both risk of mortality and recurrences or metastases were high and were modified by histological types and tumor grade. These data strongly support histology- and grade-tailored surveillance strategies and long-term follow-up for RCC patients., (Copyright © 2021. Published by Elsevier Inc.)

In risk-stratified cancer screening, multiple risk factors are incorporated into the risk assessment. An individual's estimated absolute cancer risk is linked to risk categories with tailored screening recommendations for each risk category. Absolute risk, expressed as either remaining lifetime risk or shorter-term (five- or ten-year) risk, is estimated from the age at assessment. These risk estimates vary by age; however, some clinical guidelines (e.g., enhanced breast cancer surveillance guidelines) and ongoing personalised breast screening trials, stratify women based on absolute risk thresholds that do not vary by age. We examine an alternative approach in which the risk thresholds used for risk stratification vary by age and consider the implications of using age-independent risk thresholds on risk stratification. We demonstrate that using an age-independent remaining lifetime risk threshold approach could identify high-risk younger women but would miss high-risk older women, whereas an age-independent 5-year or 10-year absolute risk threshold could miss high-risk younger women and classify lower-risk older women as high risk. With risk misclassification, women with an equivalent risk level would be offered a different screening plan. To mitigate these problems, age-dependent absolute risk thresholds should be used to inform risk stratification.

Objective: Information about prognostic outcomes can be of great help for people with prediabetes and for physicians in the face of scientific controversy about the cutoff point for defining prediabetes. We aimed to estimate different prognostic outcomes in people with prediabetes., Design: Prospective cohort of subjects with prediabetes according to American Diabetes Association guidelines., Main Outcome Measures: The probabilities of diabetes onset versus non-onset, the odds against diabetes onset, and the probability of reverting to normoglycemia according to different prediabetes categories were calculated., Results: The odds against diabetes onset ranged from 29:1 in individuals with isolated FPG of 100-109 mg/dL to 1:1 in individuals with FPG 110-125 mg/dL plus HbA1c 6.0-6.4%. The probability of reversion to normoglycemia was 31.2% (95% CI 24.0-39.6) in those with isolated FPG 100-109 mg/dL and 6.2% (95% CI 1.4-10.0) in those with FPG 110-125 mg/dL plus HbA1c 6.0-6.4%. Of every 100 participants in the first group, 97 did not develop diabetes and 31 reverted to normoglycemia, while in the second group those figures were 52 and 6., Conclusions: Using odds of probabilities and absolute numbers might be useful for people with prediabetes and physicians to share decisions on potential interventions.Key pointsCommunicating knowledge on the course of the disease to make clinical decisions is not always done appropriately.Prediabetes is an example where risk communication is important because the prognosis of subjects with prediabetes is very heterogeneous.Depending on fasting plasma glucose and HbA1c levels, the odds of probabilities against diabetes onset ranged from 29: 1 to 1: 1.Depending on fasting plasma glucose and HbA1c levels, the number of subjects in 100 who revert to normoglycemia ranged from 31 to 6.Using probabilities and number absolutes on the prognosis of prediabetes may be useful for people with prediabetes and physicians to share decisions on potential interventions.

Aims: Brisk walking and a greater muscle strength have been associated with a longer life; whether these associations are influenced by other lifestyle behaviours, however, is less well known., Methods: Information on usual walking pace (self-defined as slow, steady/average, or brisk), dynamometer-assessed handgrip strength, lifestyle behaviours (physical activity, TV viewing, diet, alcohol intake, sleep and smoking) and body mass index was collected at baseline in 450,888 UK Biobank study participants. We estimated 10-year standardised survival for individual and combined lifestyle behaviours and body mass index across levels of walking pace and handgrip strength., Results: Over a median follow-up of 7.0 years, 3808 (1.6%) deaths in women and 6783 (3.2%) in men occurred. Brisk walkers had a survival advantage over slow walkers, irrespective of the degree of engagement in other lifestyle behaviours, except for smoking. Estimated 10-year survival was higher in brisk walkers who otherwise engaged in an unhealthy lifestyle compared to slow walkers who engaged in an otherwise healthy lifestyle: 97.1% (95% confidence interval: 96.9-97.3) vs 95.0% (94.6-95.4) in women; 94.8% (94.7-95.0) vs 93.7% (93.3-94.2) in men. Body mass index modified the association between walking pace and survival in men, with the largest survival benefits of brisk walking observed in underweight participants. Compared to walking pace, for handgrip strength there was more overlap in 10-year survival across lifestyle behaviours., Conclusion: Except for smoking, brisk walkers with an otherwise unhealthy lifestyle have a lower mortality risk than slow walkers with an otherwise healthy lifestyle., (Published on behalf of the European Society of Cardiology. All rights reserved. © The Author(s) 2019. For permissions, please email: journals.permissions@oup.com.)

Backgrounds: In contrast to developed countries, breast cancer in China is characterized by a rapidly escalating incidence rate in the past two decades, lower survival rate, and vast geographic variation. However, there is no validated risk prediction model in China to aid early detection yet., Methods: A large nationwide prospective cohort, China Kadoorie Biobank (CKB), was used to evaluate relative and attributable risks of invasive breast cancer. A total of 300,824 women free of any prior cancer were recruited during 2004-2008 and followed up to Dec 31, 2016. Cox models were used to identify breast cancer risk factors and build a relative risk model. Absolute risks were calculated by incorporating national age- and residence-specific breast cancer incidence and non-breast cancer mortality rates. We used an independent large prospective cohort, Shanghai Women's Health Study (SWHS), with 73,203 women to externally validate the calibration and discriminating accuracy., Results: During a median of 10.2 years of follow-up in the CKB, 2287 cases were observed. The final model included age, residence area, education, BMI, height, family history of overall cancer, parity, and age at menarche. The model was well-calibrated in both the CKB and the SWHS, yielding expected/observed (E/O) ratios of 1.01 (95% confidence interval (CI), 0.94-1.09) and 0.94 (95% CI, 0.89-0.99), respectively. After eliminating the effect of age and residence, the model maintained moderate but comparable discriminating accuracy compared with those of some previous externally validated models. The adjusted areas under the receiver operating curve (AUC) were 0.634 (95% CI, 0.608-0.661) and 0.585 (95% CI, 0.564-0.605) in the CKB and the SWHS, respectively., Conclusions: Based only on non-laboratory predictors, our model has a good calibration and moderate discriminating capacity. The model may serve as a useful tool to raise individuals' awareness and aid risk-stratified screening and prevention strategies.

Objectives: To assess the efficacy of a pro-active, absolute cardiovascular risk-guided approach to opportunistically modifying cardiovascular risk factors in patients without coronary ischaemia attending a chest pain clinic., Design: Prospective, randomised, open label, blinded endpoint study., Setting: The rapid access chest pain clinic of Royal Hobart Hospital, a tertiary hospital., Participants: Patients who presented to the chest pain clinic between 1 July 2014 and 31 December 2017 who had intermediate to high absolute cardiovascular risk scores (5-year risk ≥ 8%). Patients with known cardiac disease or from groups with clinically determined high risk of cardiovascular disease were excluded., Main Outcome Measures: The primary endpoint was change in 5-year absolute risk score (Australian absolute risk calculator) at follow-up (at least 12 months after baseline assessment). Secondary endpoints were changes in lipid profile, blood pressure, smoking status, and body mass index, and major adverse cardiovascular events., Results: The mean change in risk at follow-up was +0.4 percentage points (95% CI, -0.8 to 1.5 percentage points) for the 98 control group patients and -2.4 percentage points (95% CI, -1.5 to -3.4 percentage points) for the 91 intervention group patients; the between-group difference in change was 2.7 percentage points (95% CI, 1.2-4.1 percentage points). Mean changes in lipid profile, systolic blood pressure, and smoking status were larger for the intervention group, but not statistically different from those for the control group., Conclusions: An absolute cardiovascular risk-guided, pro-active risk factor management strategy employed opportunistically in a chest pain clinic significantly improved 5-year absolute cardiovascular risk scores., Trial Registration: Australia New Zealand Clinical Trial Registry, ACTRN12617000615381 (retrospective)., (© 2021 AMPCo Pty Ltd.)

Background: Long-term absolute risks for cardiovascular disease and mortality and cardiovascular disease-free survival according to diet quality at different adult ages are unclear., Methods: Data from 6 prospective cohorts collected in 1985-2016 were analyzed (n = 29,497). Baseline diet quality was assessed by alternate Healthy Eating Index 2010 (aHEI-2010), alternate Mediterranean (aMED) diet score, and Dietary Approaches to Stop Hypertension (DASH) score. Absolute risks were estimated using modified Kaplan-Meier analysis and cardiovascular disease-free survival using Irwin's restricted mean. Analyses were stratified by sex and baseline age: young (20-39 years), middle-aged (40-59), and older (60-79)., Results: Comparing participants in the lowest quintile with those in the highest quintile of aHEI-2010 score, the 40-year risks for incident cardiovascular disease were 14.3% (95% confidence interval [CI]: 10.0-18.6) compared to 5.9% (3.0-8.9) in young men, 8.8% (4.3-13.3) compared to 3.0% (1.6-4.4) in young women, 39.6% (36.1-43.2) compared to 30.8% (26.2-35.3) in middle-aged men, and 32.9% (28.0-37.8) compared to 19.5% (16.6-22.4) in middle-aged women. For older adults, the 30-year risks for incident cardiovascular disease were 54.7% (49.3-60.2) compared to 49.7% (44.5-55.0) in men and 48.3% (44.0-52.5) compared to 42.4% (38.2-46.7) in women. Similar inverse associations were identified for all-cause mortality. Compared with participants in the lowest quintile of aHEI-2010 score, those in the highest quintile had ~0.5-2.2 years of longer cardiovascular disease-free survival. Results based on DASH score, but not aMED score, were similar to results based on aHEI-2010 score., Conclusions: Consuming a higher quality diet was associated with lower long-term absolute risks for cardiovascular disease and mortality and longer cardiovascular disease-free survival, regardless of sex or age at dietary assessment., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Background: Carotenoids represent 1 of few modifiable factors to reduce breast cancer risk. Elucidation of interactions between circulating carotenoids and genetic predispositions or mammographic density (MD) may help inform more effective primary preventive strategies in high-risk populations., Objectives: We tested whether women at high risk for breast cancer due to genetic predispositions or high MD would experience meaningful and greater risk reduction from higher circulating levels of carotenoids in a nested case-control study in the Nurses' Health Studies (NHS and NHSII)., Methods: This study included 1919 cases and 1695 controls in a nested case-control study in the NHS and NHSII. We assessed both multiplicative and additive interactions. RR reductions and 95% CIs were calculated using unconditional logistic regressions, adjusting for matching factors and breast cancer risk factors. Absolute risk reductions (ARR) were calculated based on Surveillance, Epidemiology, and End Results incidence rates., Results: We showed that compared with women at low genetic risk or low MD, those with higher genetic risk scores or high MD had greater ARRs for breast cancer as circulating carotenoid levels increase (additive P-interaction = 0.05). Among women with a high polygenic risk score, those in the highest quartile of circulating carotenoids had a significant ARR (28.6%; 95% CI, 14.8-42.1%) compared to those in the lowest quartile of carotenoids. For women with a high percentage MD (≥50%), circulating carotenoids were associated with a 37.1% ARR (95% CI, 21.7-52.1%) when comparing the highest to the lowest quartiles of circulating carotenoids., Conclusions: The inverse associations between circulating carotenoids and breast cancer risk appeared to be more pronounced in high-risk women, as defined by germline genetic makeup or MD., (© The Author(s) 2020. Published by Oxford University Press on behalf of the American Society for Nutrition.)

Background: The Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) and the Tyrer-Cuzick breast cancer risk prediction models are commonly used in clinical practice and have recently been extended to include polygenic risk scores (PRS). In addition, BOADICEA has also been extended to include reproductive and lifestyle factors, which were already part of Tyrer-Cuzick model. We conducted a comparative prospective validation of these models after incorporating the recently developed 313-variant PRS., Methods: Calibration and discrimination of 5-year absolute risk was assessed in a nested case-control sample of 1337 women of European ancestry (619 incident breast cancer cases) aged 23-75 years from the Generations Study., Results: The extended BOADICEA model with reproductive/lifestyle factors and PRS was well calibrated across risk deciles; expected-to-observed ratio (E/O) at the highest risk decile :0.97 (95 % CI 0.51 - 1.86) for women younger than 50 years and 1.09 (0.66 - 1.80) for women 50 years or older. Adding reproductive/lifestyle factors and PRS to the BOADICEA model improved discrimination modestly in younger women (area under the curve (AUC) 69.7 % vs. 69.1%) and substantially in older women (AUC 64.6 % vs. 56.8%). The Tyrer-Cuzick model with PRS showed evidence of overestimation at the highest risk decile: E/O = 1.54(0.81 - 2.92) for younger and 1.73 (1.03 - 2.90) for older women., Conclusion: The extended BOADICEA model identified women in a European-ancestry population at elevated breast cancer risk more accurately than the Tyrer-Cuzick model with PRS. With the increasing availability of PRS, these analyses can inform choice of risk models incorporating PRS for risk stratified breast cancer prevention among women of European ancestry.

Background: Esophageal squamous cell carcinoma (ESCC) has a high incidence rate and poor prognosis. In this study, we aimed to develop a predictive model to estimate the individualized 5-year absolute risk for ESCC in Chinese populations living in the high-risk areas of China., Methods: We developed a risk-predicting model based on the epidemiologic data from a population-based case-control study including 244 newly diagnosed ESCC patients and 1,220 healthy controls. Initially, we included easy-to-obtain risk factors to construct the model using the multivariable logistic regression analysis. The area under the ROC curves (AUC) with cross-validation methods was used to evaluate the performance of the model. Combined with local age- and sex-specific ESCC incidence and mortality rates, the model was then used to estimate the absolute risk of developing ESCC within 5 years., Results: A relative risk model was established that included eight factors: age, sex, tobacco smoking, alcohol drinking, education, and dietary habits (intake of hot food, intake of pickled/salted food, and intake of fresh fruit). The relative risk model had good discrimination [AUC, 0.785; 95% confidence interval (CI), 0.749-0.821]. The estimated 5-year absolute risk of ESCC for individuals varied widely, from 0.0003% to 19.72% in the studied population, depending on the exposure to risk factors., Conclusions: Our model based on readily identifiable risk factors showed good discriminative accuracy and strong robustness. And it could be applied to identify individuals with a higher risk of developing ESCC in the Chinese population, who might benefit from further targeted screening to prevent esophageal cancer., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Shen, Xie, Zhao, Song, Shao, Hao, Niu, Ruan, Zang, Nakyeyune, Liu and Wei.)

This study derived a set of Australian low-risk gambling limits and explored the relative and absolute risk associated with exceeding these limits. Secondary analysis of population-representative Tasmanian and Australian Capital Territory (ACT) cross-sectional (11,597 respondents) and longitudinal studies (2027 respondents) was conducted. Balancing sensitivity and specificity, the limits were: gambling frequency of 20-30 times per year; gambling expenditure of AUD $380-$615 per year (USD $240-$388 per year); gambling expenditure comprising 0.83-1.68% of gross personal income; and two types of gambling activities per year. All limits, except number of activities, predicted subsequent harm, with limits related to gambling expenditure consistently the best-performing. Exceeding the limits generally conferred a higher degree of relative and absolute risk, with gamblers exceeding the limits being 3-20 times more likely to experience harm than those who do not, and having a 5-17% risk of experiencing harm. Only 7-12% of gamblers exceeding the limits actually experienced harm. Gambling consumption lower than the limits also conferred a considerable amount of harm. Using a relative risk method, this study derived similar limits from disparate Australian states and territories. These limits can serve as working guidelines for the consideration of researchers, clinicians, and policy makers, but need to be subject to further rigorous empirical investigation.

Background: In increasingly ageing populations, there is an emergent need to develop a robust prediction model for estimating an individual absolute risk for all-cause mortality, so that relevant assessments and interventions can be targeted appropriately. The objective of the study was to derive, evaluate and validate (internally and externally) a risk prediction model allowing rapid estimations of an absolute risk of all-cause mortality in the following 10 years., Methods: For the model development, data came from English Longitudinal Study of Ageing study, which comprised 9154 population-representative individuals aged 50-75 years, 1240 (13.5%) of whom died during the 10-year follow-up. Internal validation was carried out using Harrell's optimism-correction procedure; external validation was carried out using Health and Retirement Study (HRS), which is a nationally representative longitudinal survey of adults aged ≥50 years residing in the United States. Cox proportional hazards model with regularisation by the least absolute shrinkage and selection operator, where optimisation parameters were chosen based on repeated cross-validation, was employed for variable selection and model fitting. Measures of calibration, discrimination, sensitivity and specificity were determined in the development and validation cohorts., Results: The model selected 13 prognostic factors of all-cause mortality encompassing information on demographic characteristics, health comorbidity, lifestyle and cognitive functioning. The internally validated model had good discriminatory ability (c-index=0.74), specificity (72.5%) and sensitivity (73.0%). Following external validation, the model's prediction accuracy remained within a clinically acceptable range (c-index=0.69, calibration slope β=0.80, specificity=71.5% and sensitivity=70.6%). The main limitation of our model is twofold: 1) it may not be applicable to nursing home and other institutional populations, and 2) it was developed and validated in the cohorts with predominately white ethnicity., Conclusions: A new prediction model that quantifies absolute risk of all-cause mortality in the following 10-years in the general population has been developed and externally validated. It has good prediction accuracy and is based on variables that are available in a variety of care and research settings. This model can facilitate identification of high risk for all-cause mortality older adults for further assessment or interventions.

Dermatologic care of inflammatory skin conditions has been transformed over recent decades through the use of small molecules disease-modifying anti-rheumatic drugs and targeted biologic therapies. Alongside the tremendous benefit of these agents, concerns remain regarding possible side effects, particularly cancer risk. To improve guidance and counseling of patients with skin diseases who are considering treatment with such agents, this article reviews available information on the risk of malignancies in patients treated with these agents. When possible, this article adds clinical context to risk through a number needed to harm that estimates the number of patients a provider would need to treat with a given agent in 1 year to cause a single adverse outcome over time., (© 2020 Wiley Periodicals LLC.)

Aims/hypothesis: Several pathophysiological mechanisms would suggest a causal link between hypoglycaemia and cardiovascular death; conversely, current knowledge would not support a causal relationship with other causes of death. To clarify the nature and the magnitude of the association between hypoglycaemia and death, we investigated the 5 year mortality risks for cardiovascular disease, cancer and other causes in individuals with type 2 diabetes admitted to hospital for a severe hypoglycaemic episode., Methods: We defined in the UK Clinical Practice Research Datalink database a prevalent cohort of adults with type 2 diabetes diagnosed between 1 January 1998 and 1 January 2011 (index date), with available linkage to the Office for National Statistics (ONS) and the Hospital Episode Statistics (HES). A hospital admission reporting hypoglycaemia as the underlying cause was identified before the index date in the HES; date and underlying cause of death were obtained from the ONS. We quantified the 5 year risk of cause-specific death in people with and without admission to hospital for severe hypoglycaemia, adjusting for potential confounders and accounting for competing risk., Results: Of the 74,610 subjects included in the cohort, 388 (0.5%) were admitted at least once for a severe hypoglycaemic episode; subjects admitted were older, with higher HbA 1c and a greater prevalence of multimorbidity. During a median follow-up of 7.1 years, 236 (60.8%) and 18,539 (25.0%) deaths occurred in subjects with and without a previous severe hypoglycaemia, respectively. Non-cardiovascular causes accounted for 71% of all deaths in both subjects with and without hypoglycaemia. In a 60-year-old person with severe hypoglycaemia, the 5 year absolute risk of death, adjusted for age, sex, ethnicity, systolic blood pressure, total cholesterol, HbA 1c , BMI, eGFR, smoking status, alcohol consumption and deprivation (Townsend score), was 6.6%, 1.1% and 13.1% for cardiovascular, cancer and other causes, respectively, while the 5 year absolute risk difference compared with a subject without severe hypoglycaemia was 4.7% (95% CI 1.0, 8.3) for cardiovascular, -1.4% (-4.1, 1.4) for cancer and 11.1% (6.1, 16.1) for other causes of death. Results were consistent in models further adjusted for medications and comorbidities (myocardial infarction, stroke, peripheral artery disease, heart failure, atrial fibrillation, cancer), with sulfonylurea and insulin associated with increased mortality rates (from cause-specific hazard ratio of 1.06 [95% CI 0.99, 1.14] for cancer death with use of sulfonylurea to 1.42 [1.29, 1.56] for cardiovascular death with use of insulin). Results were robust to missing data., Conclusions/interpretation: The results of this study indicate severe hypoglycaemia as a marker of, rather than causally linked to, an increased risk of long-term mortality. Regardless of the nature of the association, a severe hypoglycaemic episode represents a strong negative prognostic factor in patients with type 2 diabetes. Graphical abstract.

The well-known gene-environment interaction between alcohol consumption and aldehyde dehydrogenase 2 (ALDH2) genotype in upper aerodigestive tract cancer risk may improve our ability to identify high-risk subjects. Here, we developed and validated risk prediction models for this cancer in Japanese men and evaluated whether adding the gene-environment interaction to the model improved the predictive performance. We developed two case-cohort datasets in the Japan Public Health Center-based Prospective Study: one from subjects in the baseline survey for model development (108 cases and 4049 subcohort subjects) and the second from subjects in the 5-year follow-up survey for model validation (31 cases and 1527 subcohort subjects). We developed an environmental model including age, smoking status, and alcohol consumption, and a gene-environment interaction model including age, smoking status, and the combination of alcohol consumption and the ALDH2 genotype. We found a statistically significant gene-environment interaction for alcohol consumption and the ALDH2 genotype. The c-index for the gene-environment interaction model (0.71) was slightly higher than that for the environmental model (0.67). The values of integrated discrimination improvement and net reclassification improvement for the gene-environment interaction model were also slightly higher than those for the environmental model. Goodness-of-fit tests suggested that the models were well calibrated. Results from external model validation by the 5-year follow-up survey were consistent with those from the model development by the baseline survey. The addition of a gene-environment interaction to a lifestyle-based model might improve the performance to estimate the probability of developing upper aerodigestive tract cancer for Japanese men., (© 2020 The Authors. Cancer Science published by John Wiley & Sons Australia, Ltd on behalf of Japanese Cancer Association.)

Background/aims: The difference in mean survival time, which quantifies the treatment effect in terms most meaningful to patients and retains its interpretability regardless of the shape of the survival distribution or the proportionality of the treatment effect, is an alternative endpoint that could be used more often as the primary endpoint to design clinical trials. The underuse of this endpoint is due to investigators' lack of familiarity with the test comparing the mean survival times and the lack of tools to facilitate trial design with this endpoint. The aim of this article is to provide investigators with insights and software to design trials with restricted mean survival time as the primary endpoint., Methods: A closed-form formula for the asymptotic power of the test of restricted mean survival time difference is presented. The effects of design parameters on power were evaluated for the mean survival time test and log-rank test. An R package which calculates the power or the sample size for user-specified parameter values and provides power plots for each design parameter is provided. The R package also calculates the probability that the restricted mean survival time is estimable for user-defined trial designs., Results: Under proportional hazards and late differences in survival, the power of the mean survival time test can approach that of the log-rank test if the restriction time is late. Under early differences, the power of the restricted mean survival time test is higher than that of the log-rank test. Duration of accrual and follow-up have little influence on the power of the restricted mean survival time test. The choice of restriction time, on the other hand, has a large impact on power. Because the power depends on the interplay among the design factors, plotting the relationship between each design parameter and power allows the users to select the designs most appropriate for their trial. When modification is necessary to ensure the difference in restricted mean survival time is estimable, the three available modifications all perform adequately in the scenarios studied., Conclusion: The restricted mean survival time is a survival endpoint that is meaningful to investigators and to patients and at the same time requires less restrictive assumptions. The biggest challenge with this endpoint is selection of the restriction time. We recommend selecting a restriction time that is clinically relevant to the disease and the clinical setting of the trial of interest. The practical considerations and the R package provided in this work are readily available tools that researchers can use to design trials with restricted mean survival time as the primary endpoint.