Risk Factors Associated with PTLD Related Mortality in Adult Multivisceral Transplant Recipients - A Single Centre Cohort Study.

Background: PTLD is a heterogeneous group of lymphoproliferative diseases which can add significant mortality following multivisceral transplantation (MVTx). Our study aimed to identify potential risk factors of mortality in adult MVTx recipients who developed PTLD. Methods: All adult recipients of intestinal-containing grafts transplanted in our institution between 2013 and 2022, and who developed PTLD, were included in the study. Results: PTLD-associated mortality was 28.6% (6/21). Increased relative risk of mortality was associated with Stage 3 ECOG performance score (p=0.005; HR 34.77; 95%CI 2.94-410.91), if the recipients had a splenectomy (p=0.036; HR 14.36; 95%CI 1.19-172.89), or required retransplantation (p=0.039; HR 11.23; 95% CI 1.13-112.12). There was a significant trend for increased risk of PTLD mortality with higher peak EBV load (p=0.008), longer time from MVTx to PTLD diagnosis (p=0.008), and higher donor age (p 0.001). Peak LDH before treatment commencement was significantly higher in the mortality group vs the survival group (520.3 +- 422.8 IU/L vs 321.8 +- 154.4 IU/L; HR 1.00, 95%CI 1.00 to 1.01, p=0.019). Peak viral load prior to treatment initiation (Cycle Threshold (CT) cutoff = 32) correlated with the relative risk of death in MVTx patients who developed PTLD [29.4 (3.5) CTs in survivors compared to 23.0 (4.0) CTs in the mortality group]. Conclusions: This is the first study to identify risk factors for PTLD-associated mortality in an adult MVTx recipient cohort. Validation in larger multicentre studies and subsequent risk stratification according to these risk factors may contribute to better survival in this group of patients.

Cost-effectiveness of Improved WIC Food Package for Preventing Childhood Obesity.

BACKGROUND AND OBJECTIVES: The Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) prevents food insecurity and supports nutrition for more than 3 million low-income young children. Our objectives were to determine the cost-effectiveness of changes to WIC's nutrition standards in 2009 for preventing obesity and to estimate impacts on socioeconomic and racial/ethnic inequities. METHODS: We conducted a cost-effectiveness analysis to estimate impacts from 2010 through 2019 of the 2009 WIC food package change on obesity risk for children aged 2 to 4 years participating in WIC. Microsimulation models estimated the cases of obesity prevented in 2019 and costs per quality-adjusted-life year gained. RESULTS: An estimated 14.0 million 2- to 4-year old US children (95% uncertainty interval (UI), 13.7-14.2 million) were reached by the updated WIC nutrition standards from 2010 through 2019. In 2019, an estimated 62 700 (95% UI, 53 900-71 100) cases of childhood obesity were prevented, entirely among children from households with low incomes, leading to improved health equity. The update was estimated to cost $10 600 per quality-adjusted-life year gained (95% UI, $9760-$11 700). If WIC had reached all eligible children, more than twice as many cases of childhood obesity would have been prevented. CONCLUSIONS: Updates to WIC's nutrition standards for young children in 2009 were estimated to be highly cost-effective for preventing childhood obesity and contributed to reducing socioeconomic and racial/ethnic inequities in obesity prevalence. Improving nutrition policies for young children can be a sound public health investment; future research should explore how to improve access to them.

A Sugar-Sweetened Beverage Excise Tax in California: Projected Benefits for Population Obesity and Health Equity.

INTRODUCTION: Amid the successes of local sugar-sweetened beverage (SSB) taxes, interest in state-wide policies has grown. This study evaluated the cost effectiveness of a hypothetical 2-cent-per-ounce excise tax in California and its implications for population health and health equity. METHODS: Using the Childhood Obesity Intervention Cost-Effectiveness Study microsimulation model, tax impacts on health, health equity, and cost effectiveness over 10 years in California were projected, both overall and stratified by race/ethnicity and income. Expanding on previous models, differences in the effect of intake of SSBs on weight by BMI category were incorporated. Costing was performed in 2020, and analyses were conducted in 2021-2022. RESULTS: The tax is projected to save $4.55 billion in healthcare costs, prevent 266,000 obesity cases in 2032, and gain 114,000 quality-adjusted life years. Cost-effectiveness metrics, including cost/quality-adjusted life year gained, were cost saving. Spending on SSBs was projected to decrease by $33 per adult and $26 per child overall in the first year. Reductions in obesity prevalence for Black and Hispanic Californians were 1.8 times larger than for White Californians, and reductions for adults with lowest incomes (<130% Federal Poverty Level) were 1.4 times the reduction among those with highest incomes (>350% Federal Poverty Level). The tax is projected to save $112 in obesity-related healthcare costs per $1 invested. CONCLUSIONS: A state-wide SSB tax in California would be cost saving, lead to reductions in obesity and improvement in SSB-related health equity, and lead to overall improvements in population health. The policy would generate more than $1.6 billion in state tax revenue annually that can also be used to improve health equity.

Modeling Risk Factors for Intraindividual Variability: A Mixed-Effects Beta-Binomial Model Applied to Cognitive Function in Older People in the English Longitudinal Study of Ageing.

Cognitive functioning in older age profoundly impacts quality of life and health. While most research on cognition in older age has focused on mean levels, intraindividual variability (IIV) around this may have risk factors and outcomes independent of the mean value. Investigating risk factors associated with IIV has typically involved deriving a summary statistic for each person from residual error around a fitted mean. However, this ignores uncertainty in the estimates, prohibits exploring associations with time-varying factors, and is biased by floor/ceiling effects. To address this, we propose a mixed-effects location scale beta-binomial model for estimating average probability and IIV in a word recall test in the English Longitudinal Study of Ageing. After adjusting for mean performance, an analysis of 9,873 individuals across 7 (mean = 3.4) waves (2002-2015) found IIV to be greater at older ages, with lower education, in females, with more difficulties in activities of daily living, in later birth cohorts, and when interviewers recorded issues potentially affecting test performance. Our study introduces a novel method for identifying groups with greater IIV in bounded discrete outcomes. Our findings have implications for daily functioning and care, and further work is needed to identify the impact for future health outcomes.

Cost Effectiveness of Calorie Labeling at Large Fast-Food Chains Across the U.S.

INTRODUCTION: Calorie labeling of standard menu items has been implemented at large restaurant chains across the U.S. since 2018. The objective of this study was to evaluate the cost effectiveness of calorie labeling at large U.S. fast-food chains. METHODS: This study evaluated the national implementation of calorie labeling at large fast-food chains from a modified societal perspective and projected its cost effectiveness over a 10-year period (2018-2027) using the Childhood Obesity Intervention Cost-Effectiveness Study microsimulation model. Using evidence from over 67 million fast-food restaurant transactions between 2015 and 2019, the impact of calorie labeling on calorie consumption and obesity incidence was projected. Benefits were estimated across all racial, ethnic, and income groups. Analyses were performed in 2022. RESULTS: Calorie labeling is estimated to be cost saving; prevent 550,000 cases of obesity in 2027 alone (95% uncertainty interval=518,000; 586,000), including 41,500 (95% uncertainty interval=33,700; 50,800) cases of childhood obesity; and save $22.60 in healthcare costs for every $1 spent by society in implementation costs. Calorie labeling is also projected to prevent cases of obesity across all racial and ethnic groups (range between 126 and 185 cases per 100,000 people) and all income groups (range between 152 and 186 cases per 100,000 people). CONCLUSIONS: Calorie labeling at large fast-food chains is estimated to be a cost-saving intervention to improve long-term population health. Calorie labeling is a low-cost intervention that is already implemented across the U.S. in large chain restaurants.

Sociodemographic characteristics and longitudinal progression of multimorbidity: A multistate modelling analysis of a large primary care records dataset in England.

BACKGROUND: Multimorbidity, characterised by the coexistence of multiple chronic conditions in an individual, is a rising public health concern. While much of the existing research has focused on cross-sectional patterns of multimorbidity, there remains a need to better understand the longitudinal accumulation of diseases. This includes examining the associations between important sociodemographic characteristics and the rate of progression of chronic conditions. METHODS AND FINDINGS: We utilised electronic primary care records from 13.48 million participants in England, drawn from the Clinical Practice Research Datalink (CPRD Aurum), spanning from 2005 to 2020 with a median follow-up of 4.71 years (IQR: 1.78, 11.28). The study focused on 5 important chronic conditions: cardiovascular disease (CVD), type 2 diabetes (T2D), chronic kidney disease (CKD), heart failure (HF), and mental health (MH) conditions. Key sociodemographic characteristics considered include ethnicity, social and material deprivation, gender, and age. We employed a flexible spline-based parametric multistate model to investigate the associations between these sociodemographic characteristics and the rate of different disease transitions throughout multimorbidity development. Our findings reveal distinct association patterns across different disease transition types. Deprivation, gender, and age generally demonstrated stronger associations with disease diagnosis compared to ethnic group differences. Notably, the impact of these factors tended to attenuate with an increase in the number of preexisting conditions, especially for deprivation, gender, and age. For example, the hazard ratio (HR) (95% CI; p-value) for the association of deprivation with T2D diagnosis (comparing the most deprived quintile to the least deprived) is 1.76 ([1.74, 1.78]; p < 0.001) for those with no preexisting conditions and decreases to 0.95 ([0.75, 1.21]; p = 0.69) with 4 preexisting conditions. Furthermore, the impact of deprivation, gender, and age was typically more pronounced when transitioning from an MH condition. For instance, the HR (95% CI; p-value) for the association of deprivation with T2D diagnosis when transitioning from MH is 2.03 ([1.95, 2.12], p < 0.001), compared to transitions from CVD 1.50 ([1.43, 1.58], p < 0.001), CKD 1.37 ([1.30, 1.44], p < 0.001), and HF 1.55 ([1.34, 1.79], p < 0.001). A primary limitation of our study is that potential diagnostic inaccuracies in primary care records, such as underdiagnosis, overdiagnosis, or ascertainment bias of chronic conditions, could influence our results. CONCLUSIONS: Our results indicate that early phases of multimorbidity development could warrant increased attention. The potential importance of earlier detection and intervention of chronic conditions is underscored, particularly for MH conditions and higher-risk populations. These insights may have important implications for the management of multimorbidity.

Prioritising cardiovascular disease risk assessment to high risk individuals based on primary care records.

OBJECTIVE: To provide quantitative evidence for systematically prioritising individuals for full formal cardiovascular disease (CVD) risk assessment using primary care records with a novel tool (eHEART) with age- and sex- specific risk thresholds. METHODS AND ANALYSIS: eHEART was derived using landmark Cox models for incident CVD with repeated measures of conventional CVD risk predictors in 1,642,498 individuals from the Clinical Practice Research Datalink. Using 119,137 individuals from UK Biobank, we modelled the implications of initiating guideline-recommended statin therapy using eHEART with age- and sex-specific prioritisation thresholds corresponding to 5% false negative rates to prioritise adults aged 40-69 years in a population in England for invitation to a formal CVD risk assessment. RESULTS: Formal CVD risk assessment on all adults would identify 76% and 49% of future CVD events amongst men and women respectively, and 93 (95% CI: 90, 95) men and 279 (95% CI: 259, 297) women would need to be screened (NNS) to prevent one CVD event. In contrast, if eHEART was first used to prioritise individuals for formal CVD risk assessment, we would identify 73% and 47% of future events amongst men and women respectively, and a NNS of 75 (95% CI: 72, 77) men and 162 (95% CI: 150, 172) women. Replacing the age- and sex-specific prioritisation thresholds with a 10% threshold identify around 10% less events. CONCLUSIONS: The use of prioritisation tools with age- and sex-specific thresholds could lead to more efficient CVD assessment programmes with only small reductions in effectiveness at preventing new CVD events.

The societal costs and health impacts on obesity of BMI report cards in US schools.

OBJECTIVE: This study aimed to estimate the 10-year cost-effectiveness of school-based BMI report cards, a commonly implemented program for childhood obesity prevention in the US where student BMI is reported to parents/guardians by letter with nutrition and physical activity resources, for students in grades 3 to 7. METHODS: A microsimulation model, using data inputs from evidence reviews on health impacts and costs, estimated: how many students would be reached if the 15 states currently measuring student BMI (but not reporting to parents/guardians) implemented BMI report cards from 2023 to 2032; how many cases of childhood obesity would be prevented; expected changes in childhood obesity prevalence; and costs to society. RESULTS: BMI report cards were projected to reach 8.3 million children with overweight or obesity (95% uncertainty interval [UI]: 7.7-8.9 million) but were not projected to prevent any cases of childhood obesity or significantly decrease childhood obesity prevalence. Ten-year costs totaled $210 million (95% UI: $30.5-$408 million) or $3.33 per child per year with overweight or obesity (95% UI: $3.11-$3.68). CONCLUSIONS: School-based BMI report cards are not cost-effective childhood obesity interventions. Deimplementation should be considered to free up resources for implementing effective programs.

Using Polygenic Risk Scores for Prioritizing Individuals at Greatest Need of a Cardiovascular Disease Risk Assessment.

Background The aim of this study was to provide quantitative evidence of the use of polygenic risk scores for systematically identifying individuals for invitation for full formal cardiovascular disease (CVD) risk assessment. Methods and Results A total of 108 685 participants aged 40 to 69 years, with measured biomarkers, linked primary care records, and genetic data in UK Biobank were used for model derivation and population health modeling. Prioritization tools using age, polygenic risk scores for coronary artery disease and stroke, and conventional risk factors for CVD available within longitudinal primary care records were derived using sex-specific Cox models. We modeled the implications of initiating guideline-recommended statin therapy after prioritizing individuals for invitation to a formal CVD risk assessment. If primary care records were used to prioritize individuals for formal risk assessment using age- and sex-specific thresholds corresponding to 5% false-negative rates, then the numbers of men and women needed to be screened to prevent 1 CVD event are 149 and 280, respectively. In contrast, adding polygenic risk scores to both prioritization and formal assessments, and selecting thresholds to capture the same number of events, resulted in a number needed to screen of 116 for men and 180 for women. Conclusions Using both polygenic risk scores and primary care records to prioritize individuals at highest risk of a CVD event for a formal CVD risk assessment can efficiently prioritize those who need interventions the most than using primary care records alone. This could lead to better allocation of resources by reducing the number of risk assessments in primary care while still preventing the same number of CVD events.

Post-mastectomy radiotherapy for women with early breast cancer and one to three positive lymph nodes.

BACKGROUND: Continual improvement in adjuvant therapies has resulted in a better prognosis for women diagnosed with breast cancer. A surrogate marker used to detect the spread of disease after treatment of breast cancer is local and regional recurrence. The risk of local and regional recurrence after mastectomy increases with the number of axillary lymph nodes affected by cancer. There is a consensus to use radiotherapy as an adjuvant treatment after mastectomy (postmastectomy radiotherapy (PMRT)) in women diagnosed with breast cancer and found to have disease in four or more positive axillary lymph nodes. Despite data showing almost double the risk of local and regional recurrence in women treated with mastectomy and found to have one to three positive lymph nodes, there is a lack of international consensus on the use of PMRT in this group. OBJECTIVES: To assess the effects of PMRT in women diagnosed with early breast cancer and found to have one to three positive axillary lymph nodes. SEARCH METHODS: We searched the Cochrane Breast Cancer Group's Specialised Register, CENTRAL, MEDLINE, Embase, the World Health Organization (WHO) International Clinical Trials Registry Platform (ICTRP) and ClinicalTrials.gov up to 24 September 2021. SELECTION CRITERIA: We included randomised controlled trials (RCTs). The inclusion criteria included women diagnosed with breast cancer treated with simple or modified radical mastectomy and axillary surgery (sentinel lymph node biopsy (SLNB) alone or those undergoing axillary lymph node clearance with or without prior SLNB). We included only women receiving PMRT using X-rays (electron and photon radiation), and we defined the radiotherapy dose to reflect what is currently being recommended (i.e. 40 Gray (Gy) to 50 Gy in 15 to 25/28 fractions in 3 to 5 weeks. The included studies did not administer any boost to the tumour bed. In this review, we excluded studies using neoadjuvant chemotherapy as a supportive treatment before surgery. DATA COLLECTION AND ANALYSIS: We used Covidence to screen records. We collected data on tumour characteristics, adjuvant treatments and the outcomes of local and regional recurrence, overall survival, disease-free survival, time to progression, short- and long-term adverse events and quality of life. We reported on time-to-event outcome measures using the hazard ratio (HR) and subdistribution HR. We used Cochrane's risk of bias tool (RoB 1), and we presented overall certainty of the evidence using the GRADE approach. MAIN RESULTS: The RCTs included in this review were subgroup analyses of original RCTs conducted in the 1980s to assess the effectiveness of PMRT. Hence, the type and duration of adjuvant systemic treatments used in the studies included in this review were suboptimal compared to the current standard of care. The review involved three RCTs with a total of 829 women diagnosed with breast cancer and low-volume axillary disease. Amongst the included studies, only a single study pertained to the modern-day radiotherapy practice. The results from this one study showed a reduction of local and regional recurrence (HR 0.20, 95% confidence interval (CI) 0.13 to 0.33, 1 study, 522 women; low-certainty evidence) and improvement in overall survival with PMRT (HR 0.76, 95% CI 0.60 to 0.97, 1 study, 522 women; moderate-certainty evidence). One of the other studies using radiotherapy techniques that do not reflect modern-day practice reported on disease-free survival in women with low-volume axillary disease (subdistribution HR 0.63, 95% CI 0.41 to 0.96, 1 study, 173 women). None of the included studies reported on PMRT side effects or quality-of-life outcome measures. AUTHORS' CONCLUSIONS: Based on one study, the use of PMRT in women diagnosed with breast cancer and low-volume axillary disease indicated a reduction in locoregional recurrence and an improvement in survival. There is a need for more research to be conducted using modern-day radiotherapy equipment and methods to support and supplement the review findings.

Use of Evidence-Based Interventions to Promote Healthy Weight, Nutrition, and Physical Activity in Community Health Improvement Plans from Large Local Health Departments.

We sought to identify evidence-based healthy weight, nutrition, and physical activity strategies related to obesity prevention in large local health department (LHD) Community Health Improvement Plans (CHIPs). We analyzed the content of the most recent, publicly available plans from 72 accredited LHDs serving a population of at least 500 000 people. We matched CHIP strategies to the County Health Rankings and Roadmaps' What Works for Health (WWFH) database of interventions. We identified 739 strategies across 55 plans, 62.5% of which matched a "WWFH intervention" rated for effectiveness on diet and exercise outcomes. Among the 20 most commonly identified WWFH interventions in CHIPs, 10 had the highest evidence for effectiveness while 4 were rated as likely to decrease health disparities according to WWFH. Future prioritization of strategies by health agencies could focus on strategies with the strongest evidence for promoting healthy weight, nutrition, and physical activity outcomes and reducing health disparities.

Skin-sparing mastectomy for the treatment of breast cancer.

BACKGROUND: Skin-sparing mastectomy (SSM) is a surgical technique that aims to maximize skin preservation, facilitate breast reconstruction, and improve cosmetic outcomes. Despite its use in clinical practice, the benefits and harms related to SSM are not well established. OBJECTIVES: To assess the effectiveness and safety of skin-sparing mastectomy for the treatment of breast cancer. SEARCH METHODS: We searched Cochrane Breast Cancer's Specialized Register, CENTRAL, MEDLINE, Embase, LILACS, the World Health Organization's International Clinical Trials Registry Platform (WHO ICTRP), and ClinicalTrials.gov on 9 August 2019. SELECTION CRITERIA: Randomized controlled trials (RCTs), quasi-randomized or non-randomized studies (cohort and case-control) comparing SSM to conventional mastectomy for treating ductal carcinoma in situ (DCIS) or invasive breast cancer. DATA COLLECTION AND ANALYSIS: We used standard methodological procedures expected by Cochrane. The primary outcome was overall survival. Secondary outcomes were local recurrence free-survival, adverse events (including overall complications, breast reconstruction loss, skin necrosis, infection and hemorrhage), cosmetic results, and quality of life. We performed a descriptive analysis and meta-analysis of the data. MAIN RESULTS: We found no RCTs or quasi-RCTs. We included two prospective cohort studies and twelve retrospective cohort studies. These studies included 12,211 participants involving 12,283 surgeries (3183 SSM and 9100 conventional mastectomies). It was not possible to perform a meta-analysis for overall survival and local recurrence free-survival due to clinical heterogeneity across studies and a lack of data to calculate hazard ratios (HR).  Based on one study, the evidence suggests that SSM may not reduce overall survival for participants with DCIS tumors (HR 0.41, 95% CI 0.17 to 1.02; P = 0.06; 399 participants; very low-certainty evidence) or for participants with invasive carcinoma (HR 0.81, 95% CI 0.48 to 1.38; P = 0.44; 907 participants; very low-certainty evidence). For local recurrence-free survival, meta-analysis was not possible, due to high risk of bias in nine of the ten studies that measured this outcome. Informal visual examination of effect sizes from nine studies suggested the size of the HR may be similar between groups. Based on one study that adjusted for confounders, SSM may not reduce local recurrence-free survival (HR 0.82, 95% CI 0.47 to 1.42; P = 0.48; 5690 participants; very low-certainty evidence).  The effect of SSM on overall complications is unclear (RR 1.55, 95% CI 0.97 to 2.46; P = 0.07, I2 = 88%; 4 studies, 677 participants; very low-certainty evidence). Skin-sparing mastectomy may not reduce the risk of breast reconstruction loss (RR 1.79, 95% CI 0.31 to 10.35; P = 0.52; 3 studies, 475 participants; very low-certainty evidence), skin necrosis (RR 1.15, 95% CI 0.62 to 2.12; P = 0.22, I2 = 33%; 4 studies, 677 participants; very low-certainty evidence), local infection (RR 2.04, 95% CI 0.03 to 142.71; P = 0.74, I2 = 88%; 2 studies, 371 participants; very low-certainty evidence), nor hemorrhage (RR 1.23, 95% CI 0.47 to 3.27; P = 0.67, I2 = 0%; 4 studies, 677 participants; very low-certainty evidence). We downgraded the certainty of the evidence due to the risk of bias, imprecision, and inconsistency among the studies. There were no data available on the following outcomes: systemic surgical complications, local complications, explantation of implant/expander, hematoma, seroma, rehospitalization, skin necrosis with revisional surgery, and capsular contracture of the implant. It was not possible to perform a meta-analysis for cosmetic and quality of life outcomes due to a lack of data. One study performed an evaluation of aesthetic outcome after SSM: 77.7% of participants with immediate breast reconstruction had an overall aesthetic result of excellent or good versus 87% of participants with delayed breast reconstruction. AUTHORS' CONCLUSIONS: Based on very low-certainty evidence from observational studies, it was not possible to draw definitive conclusions on the effectiveness and safety of SSM for breast cancer treatment. The decision for this technique of breast surgery for treatment of DCIS or invasive breast cancer must be individualized and shared between the physician and the patient while considering the potential risks and benefits of available surgical options.

Evaluating the provision of paediatric liaison psychiatry services in England.

BACKGROUND: Liaison psychiatry provision for children and young people in England is poorly evaluated. AIMS: We sought to evaluate paediatric liaison psychiatry provision and develop recommendations to improve practice. METHOD: The liaison psychiatry surveys of England (LPSE) cross-sectional surveys engage all liaison psychiatry services in England. Services are systematically identified by contacting all acute hospitals with emergency departments in England. Questions are developed in consultation with NHS England and the Royal College of Psychiatrists' Faculty of Liaison Psychiatry, and updated based on feedback. Responses are submitted by email, post or telephone. Questions on paediatric services were included from 2015 (LPSE-2), and we analysed data from this and the subsequent four surveys. RESULTS: The number of acute hospitals with access to paediatric liaison psychiatry services increased from 29 (15.9%) in 2015 to 46 (26.6%) in 2019, compared with 100% provision for adults. For LPSE-4, only one site met the Core-24 criteria of 11 full-time equivalent mental health practitioners and 1.5 full-time equivalent consultants, and for LPSE-5, just two sites exceeded them. Acute hospitals with access to 24/7 paediatric liaison psychiatry services increased from 12 to 19% between LPSE-4 and LPSE-5. The proportion of paediatric liaison psychiatry services based offsite decreased from 30 to 24%. CONCLUSIONS: There is an unacceptable under-provision of paediatric liaison psychiatry services compared with provision for adults. Number of services, staffing levels and hours of operation have increased, but continued improvement is required, as few services meet the Core-24 criteria.

In simulated data and health records, latent class analysis was the optimum multimorbidity clustering algorithm.

BACKGROUND AND OBJECTIVES: To investigate the reproducibility and validity of latent class analysis (LCA) and hierarchical cluster analysis (HCA), multiple correspondence analysis followed by k-means (MCA-kmeans) and k-means (kmeans) for multimorbidity clustering. METHODS: We first investigated clustering algorithms in simulated datasets with 26 diseases of varying prevalence in predetermined clusters, comparing the derived clusters to known clusters using the adjusted Rand Index (aRI). We then them investigated the medical records of male patients, aged 65 to 84 years from 50 UK general practices, with 49 long-term health conditions. We compared within cluster morbidity profiles using the Pearson correlation coefficient and assessed cluster stability using in 400 bootstrap samples. RESULTS: In the simulated datasets, the closest agreement (largest aRI) to known clusters was with LCA and then MCA-kmeans algorithms. In the medical records dataset, all four algorithms identified one cluster of 20-25% of the dataset with about 82% of the same patients across all four algorithms. LCA and MCA-kmeans both found a second cluster of 7% of the dataset. Other clusters were found by only one algorithm. LCA and MCA-kmeans clustering gave the most similar partitioning (aRI 0.54). CONCLUSION: LCA achieved higher aRI than other clustering algorithms.

Lead Concentrations in US School Drinking Water: Testing Programs, Prevalence, and Policy Opportunities, 2016‒2018.

Objectives. To detail baseline drinking water sample lead concentrations and features of US state-level programs and policies to test school drinking water for lead in 7 states' operating programs between 2016 and 2018. Methods. We coded program and policy documents using structured content analysis protocols and analyzed state-provided data on lead concentration in drinking water samples collected in public schools during initial testing phases. Results. We analyzed data from 5688 public schools, representing 35% of eligible schools in 7 states. The number of samples per school varied. The proportion of schools identifying any sample lead concentration exceeding 5 parts per billion varied (13%-81%). Four states exceeded 20%. Other program features varied among states. Instances of lead above the state action level were identified in all states. Conclusions. In 2018, many US public school students attended schools in states without drinking water lead-testing programs. Testing all drinking water sources may be recommended. Public Health Implications. Initiating uniform school drinking water lead testing programs and surveillance over time could be used to reduce risk of lead exposure in drinking water. (Am J Public Health. 2022;112(S7):S679-S689. https://doi.org/10.2105/AJPH.2022.306961).

Incremental value of risk factor variability for cardiovascular risk prediction in individuals with type 2 diabetes: results from UK primary care electronic health records.

BACKGROUND: Cardiovascular disease (CVD) risk prediction models for individuals with type 2 diabetes are important tools to guide intensification of interventions for CVD prevention. We aimed to assess the added value of incorporating risk factors variability in CVD risk prediction for people with type 2 diabetes. METHODS: We used electronic health records (EHRs) data from 83 910 adults with type 2 diabetes but without pre-existing CVD from the UK Clinical Practice Research Datalink for 2004-2017. Using a landmark-modelling approach, we developed and validated sex-specific Cox models, incorporating conventional predictors and trajectories plus variability of systolic blood pressure (SBP), total and high-density lipoprotein (HDL) cholesterol, and glycated haemoglobin (HbA1c). Such models were compared against simpler models using single last observed values or means. RESULTS: The standard deviations (SDs) of SBP, HDL cholesterol and HbA1c were associated with higher CVD risk (P < 0.05). Models incorporating trajectories and variability of continuous predictors demonstrated improvement in risk discrimination (C-index = 0.659, 95% CI: 0.654-0.663) as compared with using last observed values (C-index = 0.651, 95% CI: 0.646-0.656) or means (C-index = 0.650, 95% CI: 0.645-0.655). Inclusion of SDs of SBP yielded the greatest improvement in discrimination (C-index increase = 0.005, 95% CI: 0.004-0.007) in comparison to incorporating SDs of total cholesterol (C-index increase = 0.002, 95% CI: 0.000-0.003), HbA1c (C-index increase = 0.002, 95% CI: 0.000-0.003) or HDL cholesterol (C-index increase= 0.003, 95% CI: 0.002-0.005). CONCLUSION: Incorporating variability of predictors from EHRs provides a modest improvement in CVD risk discrimination for individuals with type 2 diabetes. Given that repeat measures are readily available in EHRs especially for regularly monitored patients with diabetes, this improvement could easily be achieved.

Evaluation of efforts to reduce sodium and ensure access to healthier beverages in four healthcare settings in Massachusetts, US 2016-2018.

Considerable science links diets lower in sodium and sugar-sweetened beverage consumption with better health outcomes. This study describes the evaluation process and outcomes of intervention strategies to reduce sodium in foods and sugar in beverages as part of a collaborative partnership between state public health, academic, community, and healthcare partners in Massachusetts, US. This quasi-experimental, pre-post study used nutrient data linked to observations of foods and beverages available in cafeterias and vending machines in four community healthcare settings to inform intervention strategies and evaluate changes. At post-assessment, beverages with no or very low sugar were significantly more prevalent in vending machines (OR = 1.93, p < 0.001) and cafeterias (OR = 1.83, p = 0.01) and low-sodium packaged foods were significantly more prevalent in cafeterias (OR = 2.45, p < 0.001), but not vending machines. These types of partnerships and tailored feedback and technical assistance strategies may support healthier food and beverage options within healthcare settings that serve patients, their families, and employees each day.

Neural Survival Clustering: Non-parametric mixture of neural networks for survival clustering.

Survival analysis involves the modelling of the times to event. Proposed neural network approaches maximise the predictive performance of traditional survival models at the cost of their interpretability. This impairs their applicability in high stake domains such as medicine. Providing insights into the survival distributions would tackle this issue and advance the medical understanding of diseases. This paper approaches survival analysis as a mixture of neural baselines whereby different baseline cumulative hazard functions are modelled using positive and monotone neural networks. The efficiency of the solution is demonstrated on three datasets while enabling the discovery of new survival phenotypes.

Sample size estimation using a latent variable model for mixed outcome co-primary, multiple primary and composite endpoints.

Mixed outcome endpoints that combine multiple continuous and discrete components are often employed as primary outcome measures in clinical trials. These may be in the form of co-primary endpoints, which conclude effectiveness overall if an effect occurs in all of the components, or multiple primary endpoints, which require an effect in at least one of the components. Alternatively, they may be combined to form composite endpoints, which reduce the outcomes to a one-dimensional endpoint. There are many advantages to joint modeling the individual outcomes, however in order to do this in practice we require techniques for sample size estimation. In this article we show how the latent variable model can be used to estimate the joint endpoints and propose hypotheses, power calculations and sample size estimation methods for each. We illustrate the techniques using a numerical example based on a four-dimensional endpoint and find that the sample size required for the co-primary endpoint is larger than that required for the individual endpoint with the smallest effect size. Conversely, the sample size required in the multiple primary case is similar to that needed for the outcome with the largest effect size. We show that the empirical power is achieved for each endpoint and that the FWER can be sufficiently controlled using a Bonferroni correction if the correlations between endpoints are less than 0.5. Otherwise, less conservative adjustments may be needed. We further illustrate empirically the efficiency gains that may be achieved in the composite endpoint setting.

Imputation Strategies Under Clinical Presence: Impact on Algorithmic Fairness.

Biases have marked medical history, leading to unequal care affecting marginalised groups. The patterns of missingness in observational data often reflect these group discrepancies, but the algorithmic fairness implications of group-specific missingness are not well understood. Despite its potential impact, imputation is too often an overlooked preprocessing step. When explicitly considered, attention is placed on overall performance, ignoring how this preprocessing can reinforce groupspecific inequities. Our work questions this choice by studying how imputation affects downstream algorithmic fairness. First, we provide a structured view of the relationship between clinical presence mechanisms and groupspecific missingness patterns. Then, through simulations and real-world experiments, we demonstrate that the imputation choice influences marginalised group performance and that no imputation strategy consistently reduces disparities. Importantly, our results show that current practices may endanger health equity as similarly performing imputation strategies at the population level can affect marginalised groups differently. Finally, we propose recommendations for mitigating inequities that may stem from a neglected step of the machine learning pipeline.