Development and validation of a simple prostate cancer risk prediction model based on age, family history, and polygenic risk.

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.

Validation of a breast cancer risk prediction model based on the key risk factors: family history, mammographic density and polygenic risk.

PURPOSE: We compared a simple breast cancer risk prediction model, BRISK (which includes mammographic density, polygenic risk and clinical factors), against a similar model with more risk factors (simplified Rosner) and against two commonly used clinical models (Gail and IBIS). METHODS: Using nested case-control data from the Nurses' Health Study, we compared the models' association, discrimination and calibration. Classification performance was compared between Gail and BRISK for 5-year risks and between IBIS and BRISK for remaining lifetime risk. RESULTS: The odds ratio per standard deviation was 1.43 (95% CI 1.32, 1.55) for BRISK 5-year risk, 1.07 (95% CI 0.99, 1.14) for Gail 5-year risk, 1.72 (95% CI 1.59, 1.87) for simplified Rosner 10-year risk, 1.51 (95% CI 1.41, 1.62) for BRISK remaining lifetime risk and 1.26 (95% CI 1.16, 1.36) for IBIS remaining lifetime risk. The area under the receiver operating characteristic curve (AUC) was improved for BRISK over Gail for 5-year risk (AUC = 0.636 versus 0.511, P < 0.0001) and for BRISK over IBIS for remaining lifetime risk (AUC = 0.647 versus 0.571, P < 0.0001). BRISK was well calibrated for the estimation of both 5-year risk (expected/observed [E/O] = 1.03; 95% CI 0.73, 1.46) and remaining lifetime risk (E/O = 1.01; 95% CI 0.86, 1.17). The Gail 5-year risk (E/O = 0.85; 95% CI 0.58, 1.24) and IBIS remaining lifetime risk (E/O = 0.73; 95% CI 0.60, 0.87) were not well calibrated, with both under-estimating risk. BRISK improves classification of risk compared to Gail 5-year risk (NRI = 0.31; standard error [SE] = 0.031) and IBIS remaining lifetime risk (NRI = 0.287; SE = 0.035). CONCLUSION: BRISK performs better than two commonly used clinical risk models and no worse compared to a similar model with more risk factors.

In-Hospital Weight Loss and Outcomes in Patients With Heart Failure.

BACKGROUND: Acute decompensation of heart failure (HF) is often marked by fluid retention, and weight loss is a marker of successful diuresis. We examined the relationship between in-hospital weight loss and post-discharge outcomes in patients with HF. METHODS: We conducted a propensity score-matched study of 8830 patients hospitalized for decompensated HF in the Medicare-linked Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients with Heart Failure (OPTIMIZE-HF) registry, in which 4415 patients in the weight-loss group and 4415 patients in the no-weight-loss group were balanced on 75 baseline characteristics. We defined weight loss as an admission-to-discharge weight loss of 1-30 kilograms, and we defined no weight loss as a weight gain or loss of < 1 kilogram. Hazard ratios (HRs) and 95% confidence intervals (CIs) for outcomes associated with weight loss were estimated. RESULTS: Patients had a mean age of 78 years, 57% were women, and 11% were African American. The median weight loss in the weight-loss group was 3.6 (interquartile range, 2.0-6.0) kilograms. HRs and 95% CIs for 30-day all-cause mortality, all-cause readmission and HF readmission associated with weight loss were 0.75 (0.63-0.90), 0.90 (0.83-0.99) and 0.83 (0.72-0.96), respectively. Respective 60-day HRs (95% CIs) were 0.80 (0.70-0.92), 0.91 (0.85-0.98) and 0.88 (0.79-0.98). These associations were attenuated and lost significance during 6 months of follow-up. CONCLUSIONS: Among older patients hospitalized for decompensated HF, in-hospital weight loss was associated with a lower risk of mortality and hospital readmission. These findings suggest that in-hospital weight loss, a marker of successful diuresis and decongestion, is also a marker of improved clinical outcomes.

Development and validation of a clinical and genetic model for predicting risk of severe COVID-19.

Clinical and genetic risk factors for severe coronavirus disease 2019 (COVID-19) are often considered independently and without knowledge of the magnitudes of their effects on risk. Using severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) positive participants from the UK Biobank, we developed and validated a clinical and genetic model to predict risk of severe COVID-19. We used multivariable logistic regression on a 70% training dataset and used the remaining 30% for validation. We also validated a previously published prototype model. In the validation dataset, our new model was associated with severe COVID-19 (odds ratio per quintile of risk = 1.77, 95% confidence interval (CI) 1.64-1.90) and had acceptable discrimination (area under the receiver operating characteristic curve = 0.732, 95% CI 0.708-0.756). We assessed calibration using logistic regression of the log odds of the risk score, and the new model showed no evidence of over- or under-estimation of risk (α = -0.08; 95% CI -0.21-0.05) and no evidence or over-or under-dispersion of risk (ß = 0.90, 95% CI 0.80-1.00). Accurate prediction of individual risk is possible and will be important in regions where vaccines are not widely available or where people refuse or are disqualified from vaccination, especially given uncertainty about the extent of infection transmission among vaccinated people and the emergence of SARS-CoV-2 variants of concern.

Development and evolution of a two-day intensive resident experience in geriatric medicine.

As the older adult population increases, the need to enhance medical education and training in Geriatric Medicine (GM) is essential. To enhance resident training, faculty at two southeastern universities developed a Resident Award Summit, a two-day active learning experience, designed to expose family and internal medicine residents to GM principles and the various career options available in GM.Over 10 years, 353 residents from 108 residency programs participated. Resident feedback indicated that attending the event had a positive impact on future practice (M = 4.65, SD = .58) and showed that the amount of GM training received was limited, with 83.5% and 70.2% ranking adequacy of medical student and resident training as limited, respectively.To impact practice, long-term change must occur. Experiences such as the Resident Award Summit allow GM faculty to educate and prepare residents though positive teaching experiences, providing residents with the skills needed to care for older adults in their communities.

Opioid Use and Outcomes in Hospitalized Older Patients With Heart Failure Receiving and Not Receiving Hospice Referrals.

BACKGROUND: The use of opioids is associated with poor outcomes. Less is known about this association in patients with heart failure (HF) and whether it varies by the receipt of hospice care. METHODS: Of the 7467 patients hospitalized for HF without previous opioid use, 124 received discharge opioids. We matched 123 of these patients with 123 not receiving opioids based on their propensity scores for opioid use, thus assembling a matched cohort of 246 patients balanced on 30 baseline characteristics (mean age, 76 years, 60% women, and 11% African American). We repeated the process in hospice (n = 155; 20 received opioids) and nonhospice (n = 7298; 104 received opioids) subgroups, thus assembling 2 matched cohorts of 22 and 208 patients, respectively. Hazard ratios (HRs) and 95% confidence intervals (CIs) associated with opioid use were estimated from matched cohorts. RESULTS: During 8.6 (median, 1.4) years of follow-up, all-cause mortality occurred in 80% and 68% of matched patients in the opioid and nonopioid groups, respectively (HR, 1.49; 95% CI, 1.11-1.99; P = 0.008). There was evidence of heterogeneity in this association between hospice and nonhospice patients (P for interaction, 0.027). Among matched hospice and nonhospice patients, HRs (95% CIs) for mortality were 6.37 (2.06-19.69; P = 0.001) and 1.42 (1.03-1.96; P = 0.035), respectively. HRs (95% CIs) for 30-day and 1-year mortality were 1.98 (1.06-3.70; P = 0.033) and 1.72 (1.18-2.49; P = 0.004), respectively. HRs (95% CIs) for all-cause, HF, and non-HF readmissions were 1.31 (0.97-1.76; P = 0.079), 1.03 (0.71-1.49; P = 0.866), and 1.75 (1.05-2.91; P = 0.031), respectively. Readmission associations were similar among matched nonhospice patients. There was no readmission among matched hospice patients receiving opioids. CONCLUSIONS: In older patients with HF, opioid use is associated with a higher risk of mortality, which is greater in the hospice subgroup, and a higher risk of non-HF readmission in the nonhospice subgroup.

Renin-Angiotensin Inhibition and Outcomes in Nursing Home Residents With Heart Failure.

BACKGROUND: Angiotensin-converting enzyme inhibitors or angiotensin receptor blockers (ACEIs-ARBs) improve outcomes in heart failure (HF). Less is known about this association in nursing home (NH) residents. METHODS: Of the 8024 hospitalized HF patients, 542 were NH residents, of whom 250 received ACEIs-ARBs. We assembled a propensity score-matched cohort of 157 pairs of NH residents receiving and not receiving ACEIs-ARBs balanced on 29 baseline characteristics (mean age, 83 years, 74% women, 17% African American), in which we estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for outcomes associated with ACEI-ARB use. We then checked for interaction in a matched cohort of 5130 patients (378 were NH residents) assembled from the 8024 patients. RESULTS: Among 314 matched NH residents, HRs (95% CIs) for 30-day all-cause readmission, HF readmission, and all-cause mortality were 0.78 (0.47-1.28), 0.68 (0.29-1.60), and 1.26 (0.70-2.27), respectively. Respective HRs (95% CIs) at 1 year were 0.76 (0.56-1.02), 0.68 (0.42-1.09), and 1.04 (0.78-1.38). Among 5130 matched patients, ACEI-ARB use was associated with a significantly lower risk of all outcomes at both times, with no significant interactions, except for 1-year mortality, which was only significant in the non-NH subgroup (P for interaction, 0.026). CONCLUSIONS: We found no evidence that the use of ACEIs or ARBs is associated with improved outcomes in patients with HF in the NH setting. However, we also found no evidence that this association is different in NH residents with HF versus non-NH patients with HF. Future larger studies are needed to demonstrate effectiveness of these drugs in the NH setting.

Geographic variation in mental health care disparities among racially/ethnically diverse adults with psychiatric disorders.

PURPOSE: The main purpose of this paper is to examine geographic variation in unmet need for mental health care among racially/ethnically diverse adults with psychiatric disorders in the US. METHODS: Drawn from the Collaborative Psychiatric Epidemiology Surveys (CPES; 2001-2003), adults with any past year psychiatric disorder diagnosis (n = 3211) from diverse racial/ethnic backgrounds were selected for analyses. Using weighted data, descriptive analyses and logistic regression analyses were conducted. RESULTS: Two-thirds of the total sample had unmet mental health care need, which differed significantly by race/ethnicity (p < .001). Logistic regression analyses show regional variation of the effect of race/ethnicity in unmet need: after adjusting for covariates, Latinos in the South, Blacks and Latinos in the Midwest, and Latinos and Asians in the West had higher unmet need than non-Hispanic Whites, whereas no significant racial/ethnic effects were found in the Northeast. CONCLUSIONS: Findings suggest that geographic region plays an important role in the sufficient use of mental health services among racial/ethnic minorities. Further research should elucidate reasons for geographic disparities in mental health care among racial/ethnic minority adults to reduce disparities.

SNPs and breast cancer risk prediction for African American and Hispanic women.

For African American or Hispanic women, the extent to which clinical breast cancer risk prediction models are improved by including information on susceptibility single nucleotide polymorphisms (SNPs) is unknown, even though these women comprise increasing proportions of the US population and represent a large proportion of the world's population. We studied 7539 African American and 3363 Hispanic women from the Women's Health Initiative. The age-adjusted 5-year risks from the BCRAT and IBIS risk prediction models were measured and combined with a risk score based on >70 independent susceptibility SNPs. Logistic regression, adjusting for age group, was used to estimate risk associations with log-transformed age-adjusted 5-year risks. Discrimination was measured by the odds ratio (OR) per standard deviation (SD) and the area under the receiver operator curve (AUC). When considered alone, the ORs for African American women were 1.28 for BCRAT, and 1.04 for IBIS. When combined with the SNP risk score (OR 1.23), the corresponding ORs were 1.39 and 1.22. For Hispanic women the corresponding ORs were 1.25 for BCRAT, and 1.15 for IBIS. When combined with the SNP risk score (OR 1.39), the corresponding ORs were 1.48 and 1.42. There was no evidence that any of the combined models were not well calibrated. Including information on known breast cancer susceptibility loci provides approximately 10 and 19% improvement in risk prediction using BCRAT for African Americans and Hispanics, respectively. The corresponding figures for IBIS are approximately 18 and 26%, respectively.

Association between neighborhood disadvantage and hypertension prevalence, awareness, treatment, and control in older adults: results from the University of Alabama at Birmingham Study of Aging.

OBJECTIVES: We evaluated the effect of neighborhood disadvantage (ND) on older adults' prevalence, awareness, treatment, and control of hypertension. METHODS: Data were from the University of Alabama at Birmingham Study of Aging, an observational study of 1000 community-dwelling Black and White Alabamians aged 65 years and older, in 1999 to 2001. We assessed hypertension prevalence, awareness, treatment, and control with blood pressure measurements and self-report data. We assessed ND with US Census data corresponding with participants' census tracts, created tertiles of ND, and fit models with generalized estimating equations via a logit link function with a binomial distribution. Adjusted models included variables assessing personal advantage and disadvantage, place-based factors, sociodemographics, comorbidities, and health behaviors. RESULTS: Living in mid-ND (adjusted odds ratio [AOR] = 1.6; 95% confidence interval [CI] = 1.2, 2.1) and high-ND tertiles (AOR = 1.8; 95% CI = 1.3, 2.3) was associated with higher hypertension prevalence, and living in high-ND tertiles was associated with lower odds of controlled hypertension (AOR = 0.6; 95% CI = 0.4, 0.6). In adjusted models, ND was not associated with hypertension awareness or treatment. CONCLUSIONS: These findings show that neighborhood environmental factors matter for hypertension outcomes and suggest the importance of ND for hypertension management in older adults.

The Impact of Veteran Status on Life-Space Mobility among Older Black and White Men in the Deep South.

OBJECTIVE: To examine life-space mobility over 8.5 years among older Black and White male veterans and non-veterans in the Deep South. DESIGN: A prospective longitudinal study of community-dwelling Black and White male adults aged >65 years (N=501; mean age=74.9; 50% Black and 50% White) enrolled in the University of Alabama at Birmingham (UAB) Study of Aging. Data from baseline in-home assessments with follow-up telephone assessments of life-space mobility completed every 6 months were used in linear mixed-effects modeling analyses to examine life-space mobility trajectories. MAIN OUTCOME MEASURES: Life-space mobility. RESULTS: In comparison to veterans, non-veterans were more likely to be Black, single, and live in rural areas. They also reported lower income and education. Veterans had higher baseline life-space (73.7 vs 64.9 for non-veterans; P<.001). Race-veteran subgroup analyses revealed significant differences in demographics, comorbidity, cognition, and physical function. Relative to Black veterans, there were significantly greater declines in life-space trajectories for White non-veterans (P=.009), but not for White veterans (P=.807) nor Black non-veterans (P=.633). Mortality at 8.5 years was 43.5% for veterans and 49.5% for non-veterans (P=.190) with no significant differences by race-veteran status. CONCLUSIONS: Veterans had significantly higher baseline life-space mobility. There were significantly greater declines in life-space trajectories for White non-veterans in comparison to other race-veteran subgroups. Black veterans and non-veterans did not have significantly different trajectories.

Community mobility among older adults with reduced kidney function: a study of life-space.

BACKGROUND: Life-Space Assessment captures community mobility and social participation and quantifies the distance, frequency, and independence obtained as an older adult moves through his or her environment. Reduced estimated glomerular filtration rate (eGFR) is associated with decline in activities of daily living among older adults, but less is known about the association of eGFR with restrictions in mobility. STUDY DESIGN: Prospective observational cohort study. SETTING & PARTICIPANTS: Community-dwelling Medicare beneficiaries from the University of Alabama at Birmingham Study of Aging who had serum creatinine measured during a baseline in-home study visit and completed at least one telephone follow-up (N = 390). PREDICTOR: eGFR ≥ 60, 45-59, and <45 mL/min/1.73 m(2). OUTCOME: Life-space mobility trajectory. MEASUREMENTS: Life-space mobility was evaluated by telephone every 6 months for up to 4.5 years using the previously validated Life-Space Assessment. Scores using this tool range from 0-120 (higher scores indicate greater mobility). RESULTS: Mean age of the 390 participants was 77.6 ± 5.8 (SD) years, 41% were African American, 50.5% were women; 30.0% had eGFR of 45-59 mL/min/1.73 m(2), and 20.2% had eGFR < 45 mL/min/1.73 m(2). Age-, race-, and sex-adjusted mean baseline life-space mobility scores were 64.8(95% CI, 62.0-67.6), 63.8 (95% CI, 60.3-67.4), and 58.3 (95% CI, 53.8-62.7) among those with eGFR categories ≥ 60, 45-59, and <45 mL/min/1.73 m(2), respectively. Compared with those with eGFRs ≥ 60 mL/min/1.73 m(2), a more rapid decline in life-space mobility was found among those with eGFRs < 45 mL/min/1.73 m(2), though this did not reach statistical significance (P=0.06); a similar effect was not seen among those with eGFRs of 45-59 mL/min/1.73 m(2) (P=0.3). LIMITATIONS: Urinary albumin or longitudinal measures of eGFR were not available. CONCLUSIONS: eGFR < 45 mL/min/1.73 m(2) was associated with a trend toward a more rapid decline in life-space mobility among community-dwelling older adults. Findings should be confirmed in a larger population.

ReClassification of Patients with Ambiguous CA125 for Optimised Pre-Surgical Triage.

Pre-surgical clinical assessment of an adnexal mass is a complex process, and ideally requires accurate and rapid identification of disease status. Gold standard biomarker CA125 is extensively used off-label for this purpose; however its performance is typically inadequate, particularly for the detection of early stage disease and discrimination between benign versus malignant status. We recently described a multi-marker panel (MMP) and associated risk index for the differentiation of benign from malignant ovarian disease. In this study we applied a net reclassification approach to assess the use of MMP index to rescue those cases where low CA125 incorrectly excludes cancer diagnoses, or where benign disease is incorrectly assessed as "high risk" due to elevated CA125. Reclassification of such patients is of significant value to assist in the timely and accurate referral for patients where CA125 titer is uninformative.

Utility of a Multi-Marker Panel with Ultrasound for Enhanced Classification of Adnexal Mass.

Pre-surgical clinical assessment of an adnexal mass typically relies on transvaginal ultrasound for comprehensive morphological assessment, with further support provided by biomarker measurements and clinical evaluation. Whilst effective for masses that are obviously benign or malignant, a large proportion of masses remain sonographically indeterminate at surgical referral. As a consequence, post-surgical diagnoses of benign disease can outnumber malignancies up to 9-fold, while less than 50% of cancer cases receive a primary referral to a gynecological oncology specialist. We recently described a blood biomarker signature (multi-marker panel-MMP) that differentiated patients with benign from malignant ovarian disease with high accuracy. In this study, we have examined the use of the MMP, both individually and in combination with transvaginal ultrasound, as an alternative tool to CA-125 for enhanced decision making in the pre-surgical referral process.

Measuring symptoms in community-dwelling older adults: the psychometric properties of a brief symptom screen.

BACKGROUND: With aging, the probability of experiencing multiple chronic conditions has increased, along with symptoms associated with these conditions. Symptoms form a central component of illness burden, and distress. To date, most symptom measures have focused on a particular disease population. OBJECTIVE: We aimed to develop and evaluate a simple symptom screen using data obtained from a representative sample of community-dwelling older adults. METHODS: Psychometric analyses were conducted on 10 self-reported dichotomous symptom indicators collected during in-person interviews from a sample of 1000 community-dwelling older adults. Symptoms included shortness of breath, feeling tired or fatigued, problems with balance or dizziness, perceived weakness in legs, constipation, daily pain, stiffness, poor appetite, anxiety, and anhedonia. RESULTS: Over one third of the individuals (37.4%) had 5 or more concurrent symptoms. Stiffness and feeling tired were the most common symptoms. Confirmatory factor analyses were performed on the 10 symptoms for single factor and bifactor (physical and affective) models of symptom reporting. Goodness-of-fit indices indicated better fit for the bifactor model (χdf=10=89.6; P<0.001), but the practical significance of the improvement in fit was negligible. Differential item functioning analyses showed some differences of relatively high magnitude in location parameters by race; however, because the differential item functioning was in different directions, the impact on the overall measure was most likely lessened. CONCLUSIONS: Among community-dwelling older adults, a large proportion experienced multiple co-occurring symptoms. This Brief Symptom Screen can be used to quickly measure the overall symptom load in older adult populations, including those with multiple chronic conditions.

Functional status, life-space mobility, and quality of life: a longitudinal mediation analysis.

PURPOSE: Using the Wilson-Cleary model of patient outcomes as a conceptual framework, the impact of functional status on health-related quality of life (HRQoL) among older adults was examined, including tests of the mediation provided by life-space mobility. METHODS: Participants were enrollees in a population-based, longitudinal study of mobility among community-dwelling older adults. Data from four waves of the study equally spaced approximately 18 months apart (baseline, 18, 36, and 54 months) were used for participants who survived at least 1 year beyond the 54-month assessment (n = 677). Autoregressive mediation models using longitudinal data and cross-sectional mediation models using baseline data were evaluated and compared using structural equation modeling. RESULTS: The longitudinal autoregressive models supported the mediating role of life-space mobility and suggested that this effect is larger for the mental component summary score than the physical component summary score of the SF-12. Evidence for a reciprocal relationship over time between functional status, measured by ADL difficulty, and life-space mobility was suggested by modification indices; these model elaborations did not alter the substantive meaning of the mediation effects. Mediated effect estimates from longitudinal autoregressive models were generally larger than those from cross-sectional models, suggesting that mediating relationships would have been missed or were potentially underestimated in cross-sectional models. CONCLUSIONS: These results support a mediating role for life-space mobility in the relationship between functional status and HRQoL. Functional status limitations might cause diminished HRQoL in part by limiting mobility. Mobility limitations may precede functional status limitations in addition to being a consequence thereof.

Validation of an Abridged Breast Cancer Risk Prediction Model for the General Population.

PREVENTION RELEVANCE: In this prospective population-based cohort study, we show the improved performance of a new risk assessment model compared with a gold-standard model (BCRAT). The classification of at-risk women using this new model highlights the opportunity to improve risk stratification and implement existing clinical risk-reduction interventions.

A combined clinical and genetic model for predicting risk of ovarian cancer.

OBJECTIVE: Women with a family history of ovarian cancer or a pathogenic or likely pathogenic gene variant are at high risk of the disease, but very few women have these risk factors. We assessed whether a combined polygenic and clinical risk score could predict risk of ovarian cancer in population-based women who would otherwise be considered as being at average risk. METHODS: We used the UK Biobank to conduct a prospective cohort study assessing the performance of 10-year ovarian cancer risks based on a polygenic risk score, a clinical risk score and a combined risk score. We used Cox regression to assess association, Harrell's C-index to assess discrimination and Poisson regression to assess calibration. RESULTS: The combined risk model performed best and problems with calibration were overcome by recalibrating the model, which then had a hazard ratio per quintile of risk of 1.338 [95% confidence interval (CI), 1.152-1.553], a Harrell's C-index of 0.663 (95% CI, 0.629-0.698) and overall calibration of 1.000 (95% CI, 0.874-1.145). In the refined model with estimates based on the entire dataset, women in the top quintile of 10-year risk were at 1.387 (95% CI, 1.086-1.688) times increased risk, while women in the top quintile of full-lifetime risk were at 1.527 (95% CI, 1.187-1.866) times increased risk compared with the population. CONCLUSION: Identification of women who are at high risk of ovarian cancer can allow healthcare providers and patients to engage in joint decision-making discussions around the risks and benefits of screening options or risk-reducing surgery.

Melanoma risk prediction based on a polygenic risk score and clinical risk factors.

Melanoma is one of the most commonly diagnosed cancers in the Western world: third in Australia, fifth in the USA and sixth in the European Union. Predicting an individual's personal risk of developing melanoma may aid them in undertaking effective risk reduction measures. The objective of this study was to use the UK Biobank to predict the 10-year risk of melanoma using a newly developed polygenic risk score (PRS) and an existing clinical risk model. We developed the PRS using a matched case-control training dataset ( N  = 16 434) in which age and sex were controlled by design. The combined risk score was developed using a cohort development dataset ( N  = 54 799) and its performance was tested using a cohort testing dataset ( N  = 54 798). Our PRS comprises 68 single-nucleotide polymorphisms and had an area under the receiver operating characteristic curve of 0.639 [95% confidence interval (CI) = 0.618-0.661]. In the cohort testing data, the hazard ratio per SD of the combined risk score was 1.332 (95% CI = 1.263-1.406). Harrell's C-index was 0.685 (95% CI = 0.654-0.715). Overall, the standardized incidence ratio was 1.193 (95% CI = 1.067-1.335). By combining a PRS and a clinical risk score, we have developed a risk prediction model that performs well in terms of discrimination and calibration. At an individual level, information on the 10-year risk of melanoma can motivate people to take risk-reduction action. At the population level, risk stratification can allow more effective population-level screening strategies to be implemented.