Personalized Risk Estimates Research Articles

Communicating health risk in chronic kidney disease: a scoping review.

Communicating risk is a key component of shared decision-making and is vital for the management of advanced chronic kidney disease (CKD). Despite this, there is little evidence to suggest how best to communicate health risk information to people living with CKD. The aim of this review was to identify and understand the nature of evidence-based risk communication strategies for people living with CKD. We searched MEDLINE, CINAHL and Scopus databases for articles which described or evaluated the use of risk communication strategies within the renal population. Similar risk communication strategies were collated and summarised narratively. A total of 3700 sources were retrieved from the search, of which 19 were included in the review. Eleven studies reported primary research, and eight reported either narrative or systematic reviews. Seven main risk communication strategies were identified: framing, absolute versus relative risk, natural frequencies versus percentages, personalised risk estimates, qualitative risk communication, best-case/worst-case framework and use of graphs and graphics. There was a paucity of risk communication strategies specific to the CKD population. Evidence-based strategies to improve health risk communication for patients living with CKD are lacking. There is a need to establish the informational and communication preferences for patients living with CKD to better understand how to best communicate health risk information to individuals in this population.

Risk of serious adverse events after primary shoulder replacement: development and external validation of a prediction model using linked national data from England and Denmark

Despite a rising rate of serious medical complications after shoulder replacement surgery, there are no prediction models in widespread use to guide surgeons in identifying patients at high risk and to provide patients with personalised risk estimates to support shared decision making. Our aim was to develop and externally validate a prediction model for serious adverse events within 90 days of primary shoulder replacement surgery. Linked data from the National Joint Registry, National Health Service Hospital Episode Statistics Admitted Patient Care of England, and Civil Registration Mortality databases and Danish Shoulder Arthroplasty Registry and National Patient Register were used for our modelling study. Patients aged 18-100 years who had a primary shoulder replacement between April 1, 2012, and Oct 2, 2020, in England, and April 1, 2012, and Oct 2, 2018, in Denmark, were included. We developed a multivariable logistic regression model using the English dataset to predict the risk of 90-day serious adverse events, which were defined as medical complications requiring admission to hospital and all-cause death. We undertook internal validation using bootstrapping, and internal-external cross-validation across different geographical regions of England. The English model was externally validated on the Danish dataset. Data for 40 631 patients undergoing primary shoulder replacement (mean age 72·5 years [SD 9·9]; 28 709 [70·7%] women and 11 922 [29·3%] men) were used for model development, of whom 2270 (5·6%) had a 90-day serious adverse event. On internal validation, the model had a C-statistic of 0·717 (95% CI 0·707-0·728) and was well calibrated. Internal-external cross-validation showed consistent model performance across all regions in England. Upon external validation on the Danish dataset (n=6653; mean age 70·5 years [SD 10·3]; 4503 [67·7%] women and 2150 [32·3%] men), the model had a C-statistic of 0·750 (95% CI 0·723-0·776). Decision curve analysis showed clinical utility, with net benefit across all risk thresholds. This externally validated prediction model uses commonly available clinical variables to accurately predict the risk of serious medical complications after primary shoulder replacement surgery. The model is generalisable and applicable to most patients in need of a shoulder replacement. Its use offers support to clinicians and could inform and empower patients in the shared decision-making process. National Institute for Health and Care Research and the Department of Orthopaedic Surgery, Herlev and Gentofte Hospital, Denmark.

Pilot trial of an electronic decision support to improve care for emergency department patients with acute heart failure.

Emergency department (ED) providers play an important role in the management of patients with acute heart failure (AHF). We present findings from a pilot study of an electronic decision support that includes personalized risk estimates using the STRIDE-HF risk tool and tailored recommendations for initiating guideline directed medical therapy (GDMT) among appropriate patients. Among ED patients treated for AHF who were discharged from the ED or the ED-based observation unit in two EDs from 1 January 2023 to 31 July 2023, we assess prescriptions to the four classes of GDMT at two intervals: (1) ED arrival and (2) ED discharge. Specifically, we report active prescriptions for beta-blockers (BBs), renin-angiotensin receptor system inhibitors (RASis), sodium-glucose transport protein 2 inhibitors (SGLT2is) and mineralocorticoid receptor antagonists (MRA) among patients with reduced ejection fraction (HFrEF) and mildly reduced (HFmrEF). Second, we describe rates of 30-day serious adverse events (SAE) (death, cardiopulmonary resuscitation, balloon-pump insertion, intubation, new dialysis, myocardial infarction or coronary revascularization) among patients predicted to be very low risk by STRIDE-HF and discharged home. Among 234 discharged patients, 55% were female and 76% were non-White. We found 51 (21.8%), 21 (9.0%) and 126 (53.8%) had HFrEF, HFmEF and HFpEF, respectively, while 36 (15.4%) were missing EF, and 51 (22%) were very low risk, 82 (35%) were low risk, 60 (26%) were medium risk and 41 (18%) were high risk. Among HFrEF patients, 68.6%, 66.7%, 25.5% and 19.6% were on a RASi, BB, SGLT2i and MRA, respectively, at ED arrival, while 42.9%, 66.7%, 14.3% and 4.8% of HFmrEF patients were on a RASi, BB, SGLT2i and MRA, respectively. Among patients with HFpEF, only 6 (4.8%) were on an SGLT2i at ED arrival. The most prescribed new medication at ED discharge was an SGLT2i, with a nearly 10% increase in the proportion of patients with an active prescription for SGLT2i at ED discharge among HFrEF and HFmEF patients. We observed no 30-day SAE among the 51 patients predicted to be very low risk and discharged home. Ongoing treatment with GDMT at ED arrival was sub-optimal. Initiation among appropriate patients at discharge may be feasible and safe.

Why do people avoid health risk information? A qualitative analysis

Despite the potential benefit of receiving personalized health risk information, when given the opportunity to learn their risk, some people avoid that information. An extensive body of research has revealed various reasons for such information avoidance. Most of this existing work has used quantitative methods, with less focus on self-reported reasons for avoiding health risk information. We used a content analysis approach across four datasets (Dataset 1: n = 174, Dataset 2: n = 326, Dataset 3: n = 83, Dataset 4: n = 168), with the goal of identifying a broad range of self-reported reasons for avoidance. In each study, U.S. adults had the opportunity to learn their personalized risk estimate for a health condition through an online risk calculator (Health condition contexts: Dataset 1: heart disease, stroke, diabetes, prediabetes, lung cancer, colon cancer, melanoma skin cancer, breast cancer, or prostate cancer; Datasets 2 and 3: prediabetes; Dataset 4: melanoma skin cancer, stroke, lung cancer, osteoporosis, prediabetes, or diabetes). Participants who avoided their risk were asked to explain their reason(s) for avoidance via an open-ended question. Coding of these responses resulted in four overarching categories of self-reported reasons for information avoidance: information appraisal, self-perceptions of health, low utility, and affective consequences. The reasons identified both support and extend the current understanding of why people avoid health risk information.

Patterns of Gestational Hypertension or Preeclampsia Across 2 Pregnancies in Relationship to Chronic Hypertension Development: A Retrospective Cohort Study.

Gestational hypertension (GHTN) and preeclampsia are established risk indicators for chronic hypertension. While recurrence is associated with a greater risk, it is unclear whether there are differences in risk when these gestational complications occur for the first time in an earlier pregnancy versus first occurrence in a subsequent one. We hypothesized that the absence of recurrence reflects a transition toward a lower hypertension risk trajectory, whereas a new occurrence in a later pregnancy indicates a transition toward elevated risk. We analyzed linked data in Quebec, Canada, from public health care insurance administrative databases and birth, stillbirth, and death registries. Our retrospective cohort study included mothers with 2 singleton deliveries between April 1990 and December 2012. The primary exposure was patterns of GHTN or preeclampsia across 2 pregnancies (GHTN/preeclampsia in neither, first only, second only, or both). The outcome was incident chronic hypertension. We performed an adjusted multivariable Cox regression analysis. Among 431 980 women with 2 singleton pregnancies, 27 755 developed hypertension during the follow-up period. Compared with those without GHTN/preeclampsia, those with GHTN/preeclampsia only in the first pregnancy had a 2.7-fold increase in hazards (95% CI, 2.6-2.8), those with GHTN/preeclampsia only in the second had a 4.9-fold increase (95% CI, 4.6-5.1), and those with GHTN/preeclampsia in both pregnancies experienced a 7.3-fold increase (95% CI, 6.9-7.6). Patterns and estimates were similar when we considered GHTN and preeclampsia separately. The magnitude of hypertension risk is associated with the number and sequence of GHTN/preeclampsia-affected pregnancies. Considering both allows more personalized risk estimates.

Exploring perceptions of online calculators for identifying community-dwelling older people at risk of dying: A qualitative study

ObjectivesThis study aimed to assess the acceptability, value, and perceived barriers of using electronic risk calculators for predicting and communicating the risk of death in community-dwelling older adults. MethodsOne focus group and eight interviews were conducted with 16 participants with experience caring for patients or family members at end of life. A prototype mortality risk tool was used to anchor discussions. Data were analysed using a qualitative content analysis approach. ResultsFive themes emerged: acceptability, communication, barriers to use, broadening the circle of care, and tool limitations. Participants found the tool helpful for preparation, planning, and providing care, but disagreed on its community availability. Personalized risk estimates were valued for facilitating early goals of care conversations and normalizing discussions about death. However, concerns were raised about the tool's interpretation for individuals with different language, cultural, or educational backgrounds. ConclusionsWhile electronic risk calculators were found to be acceptable, balancing autonomy with varying preferences for receiving the information and potential need for support is crucial. InnovationProviding patient-oriented life-expectancy estimates can enhance decisional capacity and facilitate shared decision-making between patients, their families, and healthcare professionals. Further research is needed to explore effective communication of personalized risk tools and additional benefits, harms, and barriers to implementation.

Investigating the psychological impact of communicating epistemic uncertainty in personalized and generic risk estimates: an experimental study

Nowadays, there is an increased availability of online health risk calculators aimed at providing people with personalized risk estimates of experiencing a medical disease. Despite being deemed as more relevant and useful than generic risk estimates, personalized risks are intrinsically imperfect and inherently uncertain, arising from limitations in the reliability, credibility, and accuracy of probability estimates (i.e. epistemic uncertainty). However, whether epistemic uncertainty around personalized risk estimates should be communicated to people is a topic of debate. In this pre-registered and conceptual replication study, participants (N = 239) were randomized to a 2 [Type of risk: personalized, generic] x 2 [Uncertainty: yes, no] between-subject design, in which they read a hypothetical scenario of a person who wanted to know his/her risk of developing colorectal cancer. Half of the participants used an online risk calculator for receiving a personalized risk, and half received a generic (non-personalized) risk of colon cancer. Furthermore, half of the participants received uncertainty information through a range estimate (‘5% to 13%’), and the other half received no uncertainty information by using a point estimate (‘9%’). Primary outcome measures were perceived risk and cancer-related worry. Perceived credibility was measured as a potential mediating variable, while subjective numeracy and health literacy were serving as control variables. People who received personalized cancer risk estimates reported lower risk perceptions and cancer worry compared to people who received generic cancer risk estimates. However, communicating risks with epistemic uncertainty led to higher risk perceptions than communicating risks without uncertainty, but only for those who received personalized risks. Such an interplay was not found for generic risk estimates. Overall, these interaction effects were not mediated by perceived credibility. In conclusion, psychological effects of disclosing epistemic uncertainty around risk estimates may only be applicable to individualized disease risk information.

Using the Cell-Cycle Risk Score to Predict the Benefit of Androgen-Deprivation Therapy Added to Radiation Therapy in Patients With Newly Diagnosed Prostate Cancer.

Guidelines recommend adding androgen-deprivation therapy (ADT) to radiation therapy (RT) in certain patients with localized prostate cancer. Individualized genomic testing may improve the prognostic accuracy of risk assessments. Herein, we describe a mathematical model of the benefit of adding ADT to RT as a function of the personalized clinical cell-cycle risk (CCR) score to inform 10-year metastasis risk. A model of absolute risk reduction (ARR) was built using a retrospective cohort of men tested with Prolaris who received RT alone (N = 467). The relative benefit of ADT added to RT to reduce distant metastasis was estimated at 41% on the basis of a meta-analysis of randomized trials. The ARR and number needed to treat (NNT) were computationally derived in patients clinically tested with Prolaris between January 1, 2020, and October 31, 2022 (N = 56,485). Risks were predicted using a cause-specific Cox proportional hazards model with CCR score predicting time to metastasis. A CCR score of 2.112 represents the validated multimodal treatment (MMT) threshold. The ARR from ADT increased from almost zero at low CCR scores to 17.1% at CCR = 3.690 with the corresponding NNT = 6, indicating that adding ADT to RT would prevent metastasis within 10 years for one of every six treated individuals. In the clinical cohort, the average ARR was 0.86% in individuals under the MMT threshold (NNT = 116). The average ARR was 8.19% in individuals above the MMT threshold (NNT = 12). Broad ranges of ADT benefit were observed within National Comprehensive Cancer Network risk categories. The precise and personalized risk estimate of metastasis provided by the CCR score can help inform patients and physicians when considering treatment intensification.

Evaluation of the Implementation of the Dutch Breast Cancer Surveillance Decision Aid including Personalized Risk Estimates in the SHOUT-BC Study: A Mixed Methods Approach.

To improve Shared decision-making (SDM) regarding personalized post-treatment surveillance, the Breast Cancer Surveillance Decision Aid (BCS-PtDA), integrating personalized risk information, was developed and implemented in eight hospitals. The aim of this mixed-methods study was to (1) assess the implementation and participation rates, (2) identify facilitators and barriers for use by health care professionals (HCPs), (3) quantify the observed level of SDM, and (4) evaluate risk communication and SDM application in consultations. Implementation and participation rates and patients' BCS-PtDA use were calculated using hospital registry data and BCS-PtDA log data. HCPs' perspective on facilitators and barriers were collected using the MIDI framework. Observed SDM levels in consultation transcripts were quantified using the OPTION-5 scale. Thematic analysis was performed to assess consultation content. The average PtDA implementation and participation rates were, respectively, 26% and 61%. HCPs reported that the PtDA supported choice awareness. Reported barriers for implementation were mainly increased workload and a lack of perceived benefits. The consultation analysis (n = 64) showed patients were offered a choice, but deliberation was lacking. Risk communication was generally adequate. When the BCS-PtDA was used, patients were clearly given a choice regarding their post-treatment surveillance, but information provision and SDM application can be improved.

Patients’ and physicians’ beliefs and attitudes towards integrating personalized risk estimates into patient education about left ventricular assist device therapy

BackgroundPersonalized risk (PR) estimates may enhance clinical decision making and risk communication by providing individualized estimates of patient outcomes. We explored stakeholder attitudes toward the utility, acceptability, usefulness and best-practices for integrating PR estimates into patient education and decision making about Left Ventricular Assist Device (LVAD). Methods and ResultsAs part of a 5-year multi-institutional AHRQ project, we conducted 40 interviews with stakeholders (physicians, nurse coordinators, patients, and caregivers), analyzed using Thematic Content Analysis. All stakeholder groups voiced positive views towards integrating PR in decision making. Patients, caregivers and coordinators emphasized that PR can help to better understand a patient’s condition and risks, prepare mentally and logistically for likely outcomes, and meaningfully engage in decision making. Physicians felt it can improve their decision making by enhancing insight into outcomes, enhance tailored pre-emptive care, increase confidence in decisions, and reduce bias and subjectivity. All stakeholder groups also raised concerns about accuracy, representativeness and relevance of algorithms; predictive uncertainty; utility in relation to physician's expertise; potential negative reactions among patients; and overreliance. ConclusionStakeholders are optimistic about integrating PR into clinical decision making, but acceptability depends on prospectively demonstrating accuracy, relevance and evidence that benefits of PR outweigh potential negative impacts on decision making quality.

Risk Prediction in Male Adolescents With Congenital Long QT Syndrome: Implications for Sex-Specific Risk Stratification in Potassium Channel-Mediated Long QT Syndrome.

Sex-specific risk management may improve outcomes in congenital long QT syndrome (LQTS). We recently developed a prediction score for cardiac events (CEs) and life-threatening events (LTEs) in postadolescent women with LQTS. In the present study, we aimed to develop personalized risk estimates for the burden of CEs and LTEs in male adolescents with potassium channel-mediated LQTS. The prognostic model was derived from the LQTS Registry headquartered in Rochester, NY, comprising 611 LQT1 or LQT2 male adolescents from age 10 through 20 years, using the following variables: genotype/mutation location, QTc-specific thresholds, history of syncope, and β-blocker therapy. Anderson-Gill modeling was performed for the end point of CE burden (total number of syncope, aborted cardiac arrest, and appropriate defibrillator shocks). The applicability of the CE prediction model was tested for the end point of the first LTE(excluding syncope and adding sudden cardiac death) using Cox modeling. A total of 270 CEs occurred during follow-up. The genotype-phenotype risk prediction model identified low-, intermediate-, and high-risk groups, comprising 74%, 14%, and 12% of the study population, respectively. Compared with the low-risk group, high-risk male subjects experienced a pronounced 5.2-fold increased risk of recurrent CEs (P<0.001), whereas intermediate-risk patients had a 2.1-fold (P=0.004) increased risk . At age 20 years, the low-, intermediate-, and high-risk adolescent male patients had on average 0.3, 0.6, and 1.4 CEs per person, respectively. Corresponding 10-year adjusted probabilities for a first LTE were 2%, 6%, and 8%. Personalized genotype-phenotype risk estimates can be used to guide sex-specific management in male adolescents with potassium channel-mediated LQTS.

Implementing systematic melanoma risk assessment and risk-tailored surveillance in a skin cancer focussed dermatology clinic: A qualitative study of feasibility and acceptability to patients and clinic staff.

International bodies recommend that melanoma risk assessment should be integrated into skin cancer care provision, but evidence to support implementation is lacking. To explore the acceptability and feasibility of implementing personalised melanoma risk assessment and tailored patient education and skin surveillance within routine clinical care. This prospective qualitative implementation study was informed by the Theoretical Framework of Acceptability (TFA). Personalised, systematic melanoma risk assessment was implemented in the dermatology clinic at the Melanoma Institute Australia, Sydney, Australia February-May 2021. Pre- and post-implementation observations and semi-structured interviews with patients and staff were conducted (September 2020-March 2021). Observational notes and interview transcript data were analysed thematically using the TFA as a classifying framework. A total of 37 h of observations were made, and 29 patients and 12 clinic staff were interviewed. We found that the delivery of personalised melanoma risk estimates did not impact on patient flow through the clinic. Dermatologists reported that the personalised risk information enhanced their confidence in assessing patient risk and recommending tailored surveillance schedules. Most patients reported that the risk assessment and tailored information were a beneficial addition to their care. Among patients whose risk deviated from their expectations, some reported feeling worried, confused or mistrust in the risk information, including those at lower risk who were recommended to decrease surveillance frequency. It is feasible and acceptable to patients and clinic staff to calculate and deliver personalised melanoma risk information and tailored surveillance as part of routine clinical care within dermatology clinics.

Development and evaluation of a method to assess breast cancer risk using a longitudinal history of mammographic density: a cohort study

BackgroundWomen with dense breasts have an increased risk of breast cancer. However, breast density is measured with variability, which may reduce the reliability and accuracy of its association with breast cancer risk. This is particularly relevant when visually assessing breast density due to variation in inter- and intra-reader assessments. To address this issue, we developed a longitudinal breast density measure which uses an individual woman’s entire history of mammographic density, and we evaluated its association with breast cancer risk as well as its predictive ability.MethodsIn total, 132,439 women, aged 40–73 yr, who were enrolled in Kaiser Permanente Washington and had multiple screening mammograms taken between 1996 and 2013 were followed up for invasive breast cancer through 2014. Breast Imaging Reporting and Data System (BI-RADS) density was assessed at each screen. Continuous and derived categorical longitudinal density measures were developed using a linear mixed model that allowed for longitudinal density to be updated at each screen. Predictive ability was assessed using (1) age and body mass index-adjusted hazard ratios (HR) for breast density (time-varying covariate), (2) likelihood-ratio statistics (ΔLR-χ2) and (3) concordance indices.ResultsIn total, 2704 invasive breast cancers were diagnosed during follow-up (median = 5.2 yr; median mammograms per woman = 3). When compared with an age- and body mass index-only model, the gain in statistical information provided by the continuous longitudinal density measure was 23% greater than that provided by BI-RADS density (follow-up after baseline mammogram: ΔLR-χ2 = 379.6 (degrees of freedom (df) = 2) vs. 307.7 (df = 3)), which increased to 35% (ΔLR-χ2 = 251.2 vs. 186.7) for follow-up after three mammograms (n = 76,313, 2169 cancers). There was a sixfold difference in observed risk between densest and fattiest eight-category longitudinal density (HR = 6.3, 95% CI 4.7–8.7), versus a fourfold difference with BI-RADS density (HR = 4.3, 95% CI 3.4–5.5). Discriminatory accuracy was marginally greater for longitudinal versus BI-RADS density (c-index = 0.64 vs. 0.63, mean difference = 0.008, 95% CI 0.003–0.012).ConclusionsEstimating mammographic density using a woman’s history of breast density is likely to be more reliable than using the most recent observation only, which may lead to more reliable and accurate estimates of individual breast cancer risk. Longitudinal breast density has the potential to improve personal breast cancer risk estimation in women attending mammography screening.

Nomogram of uveal melanoma as prediction model of metastasis risk

BackgroundSince the poor prognosis of uveal melanoma with distant metastasis, we intended to screen out possible biomarkers for uveal melanoma metastasis risk and establish a nomogram model for predicting the risk of uveal melanoma (UVM) metastasis. MethodsTwo datasets of UVM (GSE84976, GSE22138) were selected. Data was analyzed by R language, CTD database and GEPIA. ResultsThe co-upregulated genes of two datasets, HTR2B, CHAC1, AHNAK2, and PTP4A3 were identified using a Venn diagram. These biomarkers are combined with clinical characteristics, and Lasso regression was conducted to filter the metastasis-related biomarkers. HTR2B, CHAC1, AHNAK2, PTP4A3, tumor thickness, and retinal detachment (RD) were selected to establish the nomogram. ConclusionOur study provides a comprehensive predictive model and personalized risk estimation tool for assessment of 3-year metastasis risk of UVM with a better accuracy.

Combining polygenic risk scores and human leukocyte antigen variants for personalized risk assessment of type 1 diabetes in the Taiwanese population.

To analyse the genome-wide association study (GWAS) data of patients with type 1 diabetes mellitus (T1D) in order to develop a risk score for the genetic effects on T1D risk and age at diagnosis in the Taiwanese population. We selected 610 patients with T1D and 2511 healthy individuals from an electronic medical record database of more than 300 000 individuals with genetic information, analysed their GWAS data, and developed a polygenic risk score (PRS). The PRS, based on 149 selected single-nucleotide polymorphisms, could effectively predict T1D risk. A PRS increase was associated with increased T1D risk (odds ratio [OR] 2.09, 95% confidence interval [CI] 1.72-2.55). Moreover, a 1-unit increase in standardized T1D PRS decreased the age at diagnosis by 0.74 years. Combined PRS and human leukocyte antigen (HLA) DQA1*03:02-DQA1*05:01 genotypes could accurately predict T1D risk. In multivariable models, HLA variants and PRS were independent risk factors for T1D risk (OR 3.76 [95% CI 1.54-9.16] and 1.71 [95% CI 1.37-2.13] for HLA DQA1*03:02-DQA1*05:01 and PRS, respectively). In a limited study population of those aged ≤18 years, PRS remained significantly associated with T1D risk. The association between T1D PRS and age at diagnosis was more obvious among males and patients aged ≤18 years. Polygenic risk score and HLA variations enable personalized risk estimates, enhance newborn screening efficiency for ketoacidosis prevention, and addresses the gap in data on T1D prediction in isolated Asian populations.

Anomogram to predict the cumulative risk for brain metastases in patients with limited-stage small cell lung cancer without prophylactic cranial irradiation.

Patients with small cell lung cancer (SCLC) have ahigh risk of developing brain metastases (BM). Prophylactic cranial irradiation (PCI) is astandard therapy for limited-stage SCLC (LS-SCLC) patients who achieved complete or partial response after thoracic chemoradiotherapy (Chemo-RT). Recent studies have indicated that asubgroup of patients with alower risk of BM can avoid PCI, and the present study therefore tries to construct anomogram to predict the cumulative risk of development of BM in LS-SCLC patients without PCI. After screening of 2298 SCLC patients who were treated at the Zhejiang Cancer Hospital from December 2009 to April 2016, atotal of 167consecutive patients with LS-SCLC who received thoracic Chemo-RT without PCI were retrospectively analyzed. The paper analyzed clinical and laboratory factors that may be correlated with BM, such as response to treatment, pretreatment serum neuron-specific enolase (NSE) and lactate dehydrogenase (LDH) levels, and TNM stage. Thereafter, anomogram was constructed to predict 3‑ and 5‑year intracranial progression-free survival (IPFS). Of 167patients with LS-SCLC, 50developed subsequent BM. Univariate analysis showed that pretreatment LDH (pre-LDH) ≥ 200 IU/L, an incomplete response to initial chemoradiation, and UICC stageIII were positively correlated to ahigher risk of BM (p < 0.05). Multivariate analysis identified pretreatment LDH level (hazard ratio [HR] 1.90, 95% confidence interval [CI] 1.08-3.34, p = 0.026), response to chemoradiation (HR 1.87, 95% CI 1.04-3.34, p = 0.035), and UICC stage (HR 6.67, 95% CI 1.03-49.15, p = 0.043) as independent predictors for the development of BM. Anomogram model was then established, and areas under the curve of 3‑year and 5‑year IPFS were 0.72 and 0.67, respectively. The present study has developed an innovative tool that is able to predict the individual cumulative risk for development of BM in LS-SCLC patients without PCI, which is beneficial for providing personalized risk estimates and facilitating the decision to perform PCI.

Abstract P6-02-08: Identifying preferences that may motivate choice of ovarian cancer risk prevention strategies using a discrete choice experiment

Abstract Background: Women with a familial or hereditary risk for ovarian cancer are at a much greater risk of developing ovarian cancer compared with women in the general population. This high risk demands prevention strategies to reduce ovarian cancer incidence and mortality. Currently there is little information about how women with a hereditary risk for ovarian cancer make trade-offs when choosing among prevention strategies and their associated risks. In anticipation of the likelihood that when given more personalized risk estimates, patients may have different preferences based on their mutation specific cancer risk as well as demographic and clinical factors, it is critical that we have the necessary information to develop counseling models that are tailored to individual patients’ preferences for cancer risk reduction and tolerance of associated risks. Methods: We performed a discrete choice experiment to investigate how women at higher risk of ovarian cancer weigh benefits (e.g. reduced risk of ovarian) versus costs (e.g. increased risk of heart disease) in choosing a treatment strategy. N=396 pre-menopausal women with a personal history of breast cancer or familial history suggestive of increased breast and/or ovarian cancer risk were surveyed from August, 2019, to January, 2022. Participants were asked to choose between two sets of attributes that specified type of surgery (risk-reducing salpingo-oophorectomy [RRSO], risk reducing salpingectomy [RRS] vs. non-surgical surveillance), age of menopause (natural versus immediate), quality of menopausal symptoms (mild, moderate, severe), and risk of ovarian cancer, heart disease, or osteoporosis. Risks of disease varied in discrete intervals. We fit a Bradley-Terry logistic regression to estimate preferences. The binary response was the randomly generated choice set selected versus the set not selected. Results: Women were more likely to choose sets with either surveillance (odds ratio [OR]= 1.28, 95% confidence interval [CI] 0.98, 1.67) or RRSO (OR= 1.39, 95% CI 1.07, 1.81) over RSS. In weighing trade-offs in the choice sets that included type of surgery, women had a stronger independent preference for reducing the risk of ovarian cancer (OR= 0.66 of choosing set per 10% increase in risk, 95% CI 0.62, 0.71) than in reducing the risk of osteoporosis (OR= 0.82 per 10% increase, 95% CI 0.75, 0.90) or heart disease (OR = 0.82 per 10% increase, 95% CI 0.76,0.88). Women also had a strong preference for delaying the expected age of ovarian cancer (OR= 1.34 per 10-year increase in age, 95% CI 1.19, 1.51). Women had strong preferences for having a natural age of menopause (OR= 1.58 compared to immediate menopause post-treatment, 95% CI 1.27, 1.95), and better less severe symptoms (OR= 0.65 for each ordinal increase in the severity of symptoms, 95% CI 0.60, 0.70). Conclusions: Our results suggest that women may prefer either surveillance or the most extensive type of surgery (RRSO) over more limited surgery (RRS). In weighing trade-offs, reducing the risk of ovarian cancer seemed to be more important than reducing the risk of osteoporosis or heart disease. Still, having a natural age of menopause and reducing the severity of symptoms could motivate the choice of treatment. Our work will allow us to estimate thresholds of measured factors that may motivate women to choose a specific treatment strategy. Citation Format: Mary Daly, Brian Egleston, Kaitlyn Lew, Lisa Bealin, Alexander Husband, Jill Stopfe, Pawel Przybysz, Olga Tchuvatkina, Yu-Ning Wong, Judy Garber, Timothy Rebbeck. Identifying preferences that may motivate choice of ovarian cancer risk prevention strategies using a discrete choice experiment. [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P6-02-08.

Current Controversies in Melanoma Treatment.

After reading this article and viewing the videos, the participant should be able to: 1. Discuss margins for in situ and invasive disease and describe reconstructive options for wide excision defects, including the keystone flap. 2. Describe a digit-sparing alternative for subungual melanoma. 3. Calculate personalized risk estimates for sentinel node biopsy using predictive nomograms. 4. Describe the indications for lymphadenectomy and describe a technique intended to reduce the risk of lymphedema following lymphadenectomy. 5. Offer options for in-transit melanoma management. Melanoma management continues to evolve, and plastic surgeons need to stay at the forefront of advances and controversies. Appropriate margins for in situ and invasive disease require consideration of the trials on which they are based. A workhorse reconstruction option for wide excision defects, particularly in extremities, is the keystone flap. There are alternative surgical approaches to subungual tumors besides amputation. It is now possible to personalize a risk estimate for sentinel node positivity beyond what is available for groups of patients with a given stage of disease. Sentinel node biopsy can be made more accurate and less morbid with novel adjuncts. Positive sentinel node biopsies are now rarely managed with completion lymphadenectomy. Should a patient require lymphadenectomy, immediate lymphatic reconstruction may mitigate the lymphedema risk. Finally, there are minimally invasive modalities for effective control of in-transit recurrences.

MyLynch: A Patient-Facing Clinical Decision Support Tool for Genetically-Guided Personalized Medicine in Lynch Syndrome.

Lynch syndrome (LS) is a hereditary cancer susceptibility condition associated with varying cancer risks depending on which of the five causative genes harbors a pathogenic variant; however, lifestyle and medical interventions provide options to lower those risks. We developed MyLynch, a patient-facing clinical decision support (CDS) web application that applies genetically-guided personalized medicine (GPM) for individuals with LS. The tool was developed in R Shiny through a patient-focused iterative design process. The knowledge base used to estimate patient-specific risk leveraged a rigorously curated literature review. MyLynch informs LS patients of their personal cancer risks, educates patients on relevant interventions, and provides patients with adjusted risk estimates, depending on the interventions they choose to pursue. MyLynch can improve risk communication between patients and providers while also encouraging communication among relatives with the goal of increasing cascade testing. As genetic panel testing becomes more widely available, GPM will play an increasingly important role in patient care, and CDS tools offer patients and providers tailored information to inform decision-making. MyLynch provides personalized cancer risk estimates and interventions to lower these risks for patients with LS.

Health workers’ perception vs medically approved COVID-19 infection risk: the risk communication gap

Abstract Background This study analyses how healthcare workers (HCWs) perceived risks, protection and preventive measures during the COVID-19 pandemic in relation to medically approved risks and organisational measures. We aim to explore ‘blind spots’ of pandemic protection and identify mental health needs. Methods A German multi-method hospital study at Hannover Medical School serves as an ‘optimal-case’ scenario of a high-income country, well-resourced hospital sector and an organisation with low HCW infection rate serves to explore governance gaps in HCW protection. Document analysis, expert information and survey data (n = 1163) were collected as part of a clinical study into SARS-CoV-2 serology testing during the second wave of the pandemic (November 2020-February 2021). Selected survey items included perceptions of risks, protection and preventive measures. Descriptive statistical analysis and regression were undertaken for gender, profession and COVID-19 patient care. Results Our study reveals a low risk of 1% medically approved infections among participants, but a much higher mean personal risk estimate of 15%. The majority (68.4%) expressed ‘some’ to ‘very strong’ fear of acquiring infection at the workplace. Individual protective behaviour and compliance with protective workplace measures were estimated as very high. Yet only about half of the respondents felt strongly protected by the employer; 12% even perceived ‘no’ or ‘little’ protection. Gender and contact with COVID-19 patients had no significant effect on the estimations of infection risks and protective workplace behaviour, but nursing was correlated with higher levels of personal risk estimations and fear of infection. Conclusions A strong mismatch between low medically approved risk and personal risk perceptions of HCWs brings stressors and threats into view, that may be preventable through improved information, risk communication and inclusion of mental health support in pandemic preparedness. Key messages • Healthcare workers’ perceptions of COVID-19 infection risks are much higher than medically approved infection risk. • Pandemic preparedness and protection plans must pay greater attention to information, risk communication and mental health needs.