Feasibility of risk assessment for breast cancer molecular subtypes.

PURPOSE: Few breast cancer risk assessment models account for the risk profiles of different tumor subtypes. This study evaluated whether a subtype-specific approach improves discrimination. METHODS: Among 3389 women who had a screening mammogram and were later diagnosed with invasive breast cancer we performed multinomial logistic regression with tumor subtype as the outcome and known breast cancer risk factors as predictors. Tumor subtypes were defined by expression of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) based on immunohistochemistry. Discrimination was assessed with the area under the receiver operating curve (AUC). Absolute risk of each subtype was estimated by proportioning Gail absolute risk estimates by the predicted probabilities for each subtype. We then compared risk factor distributions for women in the highest deciles of risk for each subtype. RESULTS: There were 3,073 ER/PR+ HER2 - , 340 ER/PR +HER2 + , 126 ER/PR-ER2+, and 300 triple-negative breast cancers (TNBC). Discrimination differed by subtype; ER/PR-HER2+ (AUC: 0.64, 95% CI 0.59, 0.69) and TNBC (AUC: 0.64, 95% CI 0.61, 0.68) had better discrimination than ER/PR+HER2+ (AUC: 0.61, 95% CI 0.58, 0.64). Compared to other subtypes, patients at high absolute risk of TNBC were younger, mostly Black, had no family history of breast cancer, and higher BMI. Those at high absolute risk of HER2+ cancers were younger and had lower BMI. CONCLUSION: Our study provides proof of concept that stratifying risk prediction for breast cancer subtypes may enable identification of patients with unique profiles conferring increased risk for tumor subtypes.

Effective alleviation of depressive and anxious symptoms and sleep disorders in benzodiazepine-dependent patients through repetitive transcranial magnetic stimulation.

Benzodiazepine (BZD) dependence poses a significant challenge in mental health, prompting the exploration of treatments like repetitive transcranial magnetic stimulation (rTMS). This research aims to assess the impact of rTMS on alleviating symptoms of BZD dependence. A randomized control trial was employed to study 40 BZD-dependent inpatients. Their symptoms were quantified using the Hamilton Anxiety Rating Scale (HAMA), Montgomery-Åsberg Depression Rating Scale (MADRS) and Pittsburgh Sleep Quality Index (PSQI). Participants were divided into a conventional treatment group (daily diazepam with gradual tapering) with supportive psychotherapy and another group receiving the same treatment supplemented with rTMS (five weekly sessions for 2 weeks). Significant improvements were observed in both groups over baseline in MADRS, HAMA and PSQI scores at the 2nd, 4th, 8th and 12th week assessments (p < 0.05). The group receiving rTMS in addition to conventional treatment exhibited superior improvements in all measures at the 8th and 12th weeks. The addition of rTMS to conventional treatment methods for BZD dependence significantly betters the recovery in terms of depression, anxiety and sleep quality, highlighting the role of rTMS as an effective adjunct therapy.

Association of Remote Patient-Reported Outcomes and Step Counts With Hospitalization or Death Among Patients With Advanced Cancer Undergoing Chemotherapy: Secondary Analysis of the PROStep Randomized Trial.

BACKGROUND: Patients with advanced cancer undergoing chemotherapy experience significant symptoms and declines in functional status, which are associated with poor outcomes. Remote monitoring of patient-reported outcomes (PROs; symptoms) and step counts (functional status) may proactively identify patients at risk of hospitalization or death. OBJECTIVE: The aim of this study is to evaluate the association of (1) longitudinal PROs with step counts and (2) PROs and step counts with hospitalization or death. METHODS: The PROStep randomized trial enrolled 108 patients with advanced gastrointestinal or lung cancers undergoing cytotoxic chemotherapy at a large academic cancer center. Patients were randomized to weekly text-based monitoring of 8 PROs plus continuous step count monitoring via Fitbit (Google) versus usual care. This preplanned secondary analysis included 57 of 75 patients randomized to the intervention who had PRO and step count data. We analyzed the associations between PROs and mean daily step counts and the associations of PROs and step counts with the composite outcome of hospitalization or death using bootstrapped generalized linear models to account for longitudinal data. RESULTS: Among 57 patients, the mean age was 57 (SD 10.9) years, 24 (42%) were female, 43 (75%) had advanced gastrointestinal cancer, 14 (25%) had advanced lung cancer, and 25 (44%) were hospitalized or died during follow-up. A 1-point weekly increase (on a 32-point scale) in aggregate PRO score was associated with 247 fewer mean daily steps (95% CI -277 to -213; P<.001). PROs most strongly associated with step count decline were patient-reported activity (daily step change -892), nausea score (-677), and constipation score (524). A 1-point weekly increase in aggregate PRO score was associated with 20% greater odds of hospitalization or death (adjusted odds ratio [aOR] 1.2, 95% CI 1.1-1.4; P=.01). PROs most strongly associated with hospitalization or death were pain (aOR 3.2, 95% CI 1.6-6.5; P<.001), decreased activity (aOR 3.2, 95% CI 1.4-7.1; P=.01), dyspnea (aOR 2.6, 95% CI 1.2-5.5; P=.02), and sadness (aOR 2.1, 95% CI 1.1-4.3; P=.03). A decrease in 1000 steps was associated with 16% greater odds of hospitalization or death (aOR 1.2, 95% CI 1.0-1.3; P=.03). Compared with baseline, mean daily step count decreased 7% (n=274 steps), 9% (n=351 steps), and 16% (n=667 steps) in the 3, 2, and 1 weeks before hospitalization or death, respectively. CONCLUSIONS: In this secondary analysis of a randomized trial among patients with advanced cancer, higher symptom burden and decreased step count were independently associated with and predictably worsened close to hospitalization or death. Future interventions should leverage longitudinal PRO and step count data to target interventions toward patients at risk for poor outcomes. TRIAL REGISTRATION: ClinicalTrials.gov NCT04616768; https://clinicaltrials.gov/study/NCT04616768. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2021-054675.

Efficient inference of parent-of-origin effect using case-control mother-child genotype data.

Parent-of-origin effect plays an important role in mammal development and disorder. Case-control mother-child pair genotype data can be used to detect parent-of-origin effect and is often convenient to collect in practice. Most existing methods for assessing parent-of-origin effect do not incorporate any covariates, which may be required to control for confounding factors. We propose to model the parent-of-origin effect through a logistic regression model, with predictors including maternal and child genotypes, parental origins, and covariates. The parental origins may not be fully inferred from genotypes of a target genetic marker, so we propose to use genotypes of markers tightly linked to the target marker to increase inference efficiency. A robust statistical inference procedure is developed based on a modified profile log-likelihood in a retrospective way. A computationally feasible expectation-maximization algorithm is devised to estimate all unknown parameters involved in the modified profile log-likelihood. This algorithm differs from the conventional expectation-maximization algorithm in the sense that it is based on a modified instead of the original profile log-likelihood function. The convergence of the algorithm is established under some mild regularity conditions. This expectation-maximization algorithm also allows convenient handling of missing child genotypes. Large sample properties, including weak consistency, asymptotic normality, and asymptotic efficiency, are established for the proposed estimator under some mild regularity conditions. Finite sample properties are evaluated through extensive simulation studies and the application to a real dataset.

A constrained maximum likelihood approach to developing well-calibrated models for predicting binary outcomes.

The added value of candidate predictors for risk modeling is routinely evaluated by comparing the performance of models with or without including candidate predictors. Such comparison is most meaningful when the estimated risk by the two models are both unbiased in the target population. Very often data for candidate predictors are sourced from nonrepresentative convenience samples. Updating the base model using the study data without acknowledging the discrepancy between the underlying distribution of the study data and that in the target population can lead to biased risk estimates and therefore an unfair evaluation of candidate predictors. To address this issue assuming access to a well-calibrated base model, we propose a semiparametric method for model fitting that enforces good calibration. The central idea is to calibrate the fitted model against the base model by enforcing suitable constraints in maximizing the likelihood function. This approach enables unbiased assessment of model improvement offered by candidate predictors without requiring a representative sample from the target population, thus overcoming a significant practical challenge. We study theoretical properties for model parameter estimates, and demonstrate improvement in model calibration via extensive simulation studies. Finally, we apply the proposed method to data extracted from Penn Medicine Biobank to inform the added value of breast density for breast cancer risk assessment in the Caucasian woman population.

Towards optimal model evaluation: enhancing active testing with actively improved estimators.

With rapid advancements in machine learning and statistical models, ensuring the reliability of these models through accurate evaluation has become imperative. Traditional evaluation methods often rely on fully labeled test data, a requirement that is becoming increasingly impractical due to the growing size of datasets. In this work, we address this issue by extending existing work on active testing (AT) methods which are designed to sequentially sample and label data for evaluating pre-trained models. We propose two novel estimators: the Actively Improved Levelled Unbiased Risk (AILUR) and the Actively Improved Inverse Probability Weighting (AIIPW) estimators which are derived from nonparametric smoothing estimation. In addition, a model recalibration process is designed for the AIIPW estimator to optimize the sampling probability within the AT framework. We evaluate the proposed estimators on four real-world datasets and demonstrate that they consistently outperform existing AT methods. Our study also shows that the proposed methods are robust to changes in subsample sizes, and effective at reducing labeling costs.

Case report: Dupilumab: a promising treatment option for adult linear IgA bullous dermatosis with severe pruritus.

Linear IgA bullous dermatosis (LABD) is an acquired autoimmune subepidermal blistering disorder. Diagnosis always relies on skin pathology and direct immunofluorescence (DIF), with typical linear deposits of IgA along the basement membrane zone (BMZ). The typical clinical manifestation is tense bullae arranged like the "string of pearls" companied with severe pruritus. Dapsone is often considered first-line therapy for LABD, and it is necessary to test the HLA-B*1301 gene to prevent the occurrence of dapsone-induced hypersensitivity syndrome (DHS). Here we report a case of LABD resistant to corticosteroid and sulfasalazine, while waiting for HLA-B*1301 gene test results, dupilumab was used to control severe pruritus.

Unconsciousness as the main nonfocal symptom of anterior circulation transient ischemic attack: A case report.

RATIONALE: Unconsciousness is a nonfocal symptom of transient ischemic attack (TIA) that is frequently observed in patients with vertebrobasilar artery stenosis or occlusion. Conversely, loss of consciousness due to anterior circulation involvement (e.g., middle cerebral artery [MCA]) is a rare occurrence in TIA. PATIENT CONCERNS: This report describes a rare case in a 59-year-old woman who experienced recurrent episodes of altered consciousness because of the occlusion or stenosis of her MCAs. DIAGNOSES: The diagnosis of the case was updated from TIA to acute cerebral infarction, finally. Following initial loss of consciousness, cranial magnetic resonance imaging (MRI) did not reveal any evidence of acute cerebral infarction. However, following the second and third episodes of unconsciousness, the MRI revealed multiple new acute cerebral infarcts affecting both the cerebral hemispheres. Further evaluation through digital subtraction angiography disclosed complete occlusion of the left MCA and severe stenosis of the right MCA. INTERVENTIONS: Early in her illness, the patient was treated with vasodilators, aspirin and atorvastatin. Finally, 2 stents in her right and left MCAs were placed respectively, followed by treatment with aspirin, clopidogrel, and double-dosed atorvastatin calcium. Meanwhile, the patient focused on avoiding conditions which may lead to dehydration in her daily life routine. OUTCOMES: The episodes of unconsciousness of this patient were completely resolved. During the 1-year postoperative follow-up, the patient remained clinically stable without any symptoms of unconsciousness, limb numbness or weakness, or dizziness. LESSONS: These findings suggested that hypoperfusion in the bilateral cerebral hemispheres played a pivotal role in precipitating the patient episodes of unconsciousness. This case underscores the possibility that occlusion or severe stenosis in both MCAs can contribute to recurrent episodes of unconsciousness due to hypoperfusion. Moreover, it emphasizes the association between these episodes of unconsciousness and an increased risk of subsequent ischemic stroke.

91 Circulating inflammatory proteins and the risk of age-related macular degeneration: A bidirectional Mendelian randomization study.

Previous observational studies have indicated a correlation between circulating inflammatory proteins and age-related macular degeneration (AMD), yet the causal nature of this relationship remains uncertain. This study aims to investigate the causal link between circulating inflammatory proteins and AMD utilizing a bidirectional two-sample Mendelian randomization approach. The findings indicated that elevated levels of four circulating inflammatory proteins, including C-C Motif Chemokine Ligand 11 (CCL11), Signaling Lymphocytic Activation Molecule Family Member 1 (SLAMF1), TNF Superfamily Member 11 (TRANCE) and Vascular Endothelial Growth Factor A (VEGF-A) lead to the increased risk of AMD, while increased levels of two circulating inflammatory proteins, including Fibroblast Growth Factor 19 (FGF-19) and Interleukin 10 Receptor Subunit Alpha (IL-10RA), resulted in the decreased risk of AMD. Conversely, the results from reverse Mendelian randomization suggested that the presence of AMD lead to the reduction in levels of 15 circulating inflammatory proteins. The findings of this study support the association between elevated levels of circulating inflammatory proteins and the risk of AMD, as well as the potential impact of AMD on reducing circulating inflammatory protein levels. CCL11, SLAMF1, TRANCE and VEGF-A are identified as potential molecular markers in the progression of AMD. These results offer a novel molecular therapeutic target for the prevention and treatment of AMD.

Case report: Managing pemphigus foliaceus using apremilast without systemic glucocorticosteroids or immunosuppressive agents.

Pemphigus foliaceus (PF) is a superficial form of pemphigus. Treatment options for PF resemble pemphigus vulgaris, including glucocorticosteroids, immunosuppressive agents and rituximab et al. These treatment approaches can effectively improve the condition but may also be accompanied by high risks of side effects. Therefore, it is crucial to find a safe and effective treatment options for patients with PF. It will not only benefit/be necessary for patients who refuse glucocorticosteroids or immunosuppressive agents treatments, but also for patients who cannot be treated with glucocorticosteroids or immunosuppressive agents. Herein, we reported a case of PF that was treated with apremilast without systemic glucocorticosteroids or immunosuppressive agents. A 54-year-old woman presented with itchy erythema and erosions on the trunk for more than 1 month. The patient applied mometasonefuroate cream without improvement for a duration of two weeks. The past history of diabetes mellitus and atrophic gastritis was reported. Physical examination revealed scattered erythematous macules and erosions on the trunk. No mucosal involvement was observed. The condition was assessed by the pemphigus disease area index and numerical rating scale, with baseline scores of 7 and 8, respectively. Histopathological examination showed acantholysis and intraepithelial blister. Direct immunofluorescence revealed the presence of IgG and Complement 3 deposition between the acanthocytes with the reticular distribution. Based on enzyme-linked immunosorbent assay results, the levels of Dsg1 and Dsg3 antibodies were 28.18 and 0.26 kU/L respectively. The diagnosis of PF was made. This patient was successfully treated with apremilast without systemic glucocorticosteroids or immunosuppressive agents. The patient has continued with apremilast 30mg once daily for maintenance and no adverse events related to apremilast such as gastrointestinal side effects were observed during the 9-month follow-up period. In conclusion, apremilast therapy without systemic glucocorticosteroids nor immunosuppressive agents might provide an effective alternative to management of mild PF without obvious side effect.

Association between tea consumption and risk of kidney stones: results from dose-response meta-analysis of prospective studies and Mendelian randomization analysis.

PURPOSE: The association between tea consumption and kidney stones is inconsistent in observational studies. Thus, we performed a dose-response meta-analysis of prospective cohort studies and a two-sample Mendelian randomization (MR) analysis to identify this association. METHODS: The prospective cohort studies reporting the relationship between tea consumption and kidney stones were searched from PubMed, the Cochrane Library, EMBASE, and Web of Science from inception to December 1, 2023. For MR analysis, the summary-level data for tea consumption and kidney stones were extracted from the UK Biobank available data and the 8th release of the FinnGen consortium, respectively. The inverse-variance weighted (IVW) method was the primary analytical method. RESULTS: In our dose-response meta-analysis, four prospective cohort studies involving 1,263,008 participants were included, and tea consumption was found to have significant associations with kidney stones (RR: 0.80, 95% CI: 0.73-0.87). We also observed a substantially linear negative relationship between tea consumption and the risk of kidney stones. In MR analysis, the IVW method indicated that tea consumption was inversely associated with kidney stones (OR: 0.71, 95% CI: 0.53-0.94). CONCLUSION: Our study confirmed a causal relationship between tea consumption and kidney stones, and higher tea consumption may reduce the risk of kidney stones.

ALA-PDT promotes the death and contractile capacity of hypertrophic scar fibroblasts through inhibiting the TGF-ß1/Smad2/3/4 signaling pathway.

BACKGROUND: Hypertrophic scars, an abnormal wound-healing response to burn injuries, are characterized by massive fibroblast proliferation and excessive deposition of extracellular matrix and collagen. 5-aminolevulinic acid-based photodynamic therapy (ALA-PDT) is a promising therapy for hypertrophic scar, details of the mechanisms remain to be elucidated. In this study, we aimed to investigate the molecular mechanisms involved in ALA-PDT against hypertrophic scar fibroblasts. METHODS: The morphologies of hypertrophic scar fibroblasts (HSFs) treated with ALA-PDT were observed under a light microscopy. The viability of HSFs was detected using the CCK-8 assay. HSFs-populated collagen gel contraction assays were conducted to examine the fibroblast contractility and the cytotoxicity of HSFs in 3D collagen tissues were observed using confocal microscopy. The effect of ALA-PDT on TGF-ß1/Smad2/3/4 signaling pathway activation and effector gene expression were verified by immunoprecipitation, western blot and real-time quantitative PCR analysis. RESULTS: We observed significant changes in cell morphology after ALA-PDT treatment of HSFs. As ALA concentration and light dose increased, the viability of HSFs significantly decreased. ALA-PDT can significantly alleviate the contractile capacity and promote the death of HSFs induced by TGF-ß1 treatment in a three-dimensional collagen culture model. TGF-ß1 treatment of HSFs can significantly induce phosphorylation of Smad2/3 (p-Smad2/3) in whole cells, as well as p-Smad2/3 and Smad4 proteins into the nucleus and increase the mRNA levels of collagen 1/3 and α-SMA. ALA-PDT hampers the TGF-ß1-Smad2/3/4 signaling pathway activation by inducing K48-linked ubiquitination and degradation of Smad4. CONCLUSIONS: Our results provide evidence that ALA-PDT can inhibit fibroblast contraction and promote cell death by inhibiting the activation of the TGF-ß1 signaling pathway that mediates hypertrophic scar formation, which may be the basis for the efficacy of ALA-PDT in the treatment of hypertrophic scars.

Metabolic Syndrome and the Risk of Kidney Stones: a Large-scale Cohort Study from 487,860 UK Biobank participants.

OBJECTIVE: While some studies have suggested an association between metabolic syndrome and kidney stones, the quality and level of evidence in these studies vary. Whether some individual characteristics and clustering of metabolic syndrome traits increase the risk of kidney stones has not been examined in a large-scale prospective cohort. MATERIALS: We conducted a retrospective analysis of data from a prospective cohort of 487,860 UK Biobank participants who were free from kidney stones at baseline. The presence of metabolic syndrome was based on five criteria: abdominal obesity, high triglyceride levels, low high-density lipoprotein (HDL) cholesterol levels, high blood pressure (HBP), and type 2 diabetes mellitus (T2DM). Cox proportional hazards regression models were used to evaluate the association between metabolic syndrome and risk of kidney stones. RESULTS: After an average follow-up period of 12.6 years, a total of 5,213 of the 487,860 participants included in the UK Biobank study developed kidney stones. The partial traits of metabolic syndrome, including waist circumference (HR: 1.15, 95% CI: 1.10-1.20), HDL cholesterol (0.66, 0.55-0.79), HBP (1.11, 1.03-1.19) and T2DM (1.14, 1.04-1.21), were independently associated with the occurrence of kidney stones. The clustering of metabolic syndrome is significantly associated with kidney stone formation, and as the number of metabolic syndrome traits increases, the risk of kidney stones gradually increases. CONCLUSION: Metabolic syndrome is a significant and independent risk factor for the development of kidney stones. This association suggests that kidney stones may represent a systemic disorder influenced by the interplay of various metabolic risk factors.

Targeting gut and intratumoral microbiota: a novel strategy to improve therapy resistance in cancer with a focus on urologic tumors.

INTRODUCTION: Growing attention has been drawn to urologic tumors due to their rising incidence and suboptimal clinical treatment outcomes. Cancer therapy resistance poses a significant challenge in clinical oncology, limiting the efficacy of conventional treatments and contributing to disease progression. Recent research has unveiled a complex interplay between the host microbiota and cancer cells, highlighting the role of the microbiota in modulating therapeutic responses. AREAS COVERED: We used the PubMed and Web of Science search engines to identify key publications in the fields of tumor progression and urologic tumor treatment, specifically focusing on the role of the microbiota. In this review, we summarize the current literature on how microbiota influence the tumor microenvironment and anti-tumor immunity, as well as their impact on treatments for urinary system malignancies, highlighting promising future applications. EXPERT OPINION: We explore how the composition and function of the gut microbiota influence the tumor microenvironment and immune response, ultimately impacting treatment outcomes. Additionally, we discuss emerging strategies targeting the microbiota to enhance therapeutic efficacy and overcome resistance. The application of antibiotics, fecal microbiota transplantation, and oncolytic bacteria has improved tumor treatment outcomes, which provides a novel insight into developing therapeutic strategies for urologic cancer.

Impact response of lightweight steel foam concrete composite slabs: Experimental, numerical and analytical studies.

This paper presents a study on the low-velocity impact response of lightweight steel foam concrete (LSFC) composite slabs. The LSFC composite slab consisted of a W-shaped steel plate, foam concrete and oriented strand board (OSB). Low-velocity impact tests on the LSFC composite slabs were conducted by employing an ultra-high heavy-duty drop hammer testing machine. The tests revealed the failure mode, impact force and displacement response of LSFC composite slabs. The effects of density and thickness of foam concrete and drop height on the peak impact force and energy absorption ratio were investigated. A finite element (FE) model was set up to predict the impact resistance of the LSFC composite slabs, and a good agreement between simulation and test results was achieved. In addition, an equivalent-single-degree-of-freedom (ESDOF) model was set up to predict the displacement response of the LSFC composite slabs under impact loading.

Family cascade screening for equitable identification of familial hypercholesterolemia: study protocol for a hybrid effectiveness-implementation type III randomized controlled trial.

BACKGROUND: Familial hypercholesterolemia (FH) is a heritable disorder affecting 1.3 million individuals in the USA. Eighty percent of people with FH are undiagnosed, particularly minoritized populations including Black or African American people, Asian or Asian American people, and women across racial groups. Family cascade screening is an evidence-based practice that can increase diagnosis and improve health outcomes but is rarely implemented in routine practice, representing an important care gap. In pilot work, we leveraged best practices from behavioral economics and implementation science-including mixed-methods contextual inquiry with clinicians, patients, and health system constituents-to co-design two patient-facing implementation strategies to address this care gap: (a) an automated health system-mediated strategy and (b) a nonprofit foundation-mediated strategy with contact from a foundation-employed care navigator. This trial will test the comparative effectiveness of these strategies on completion of cascade screening for relatives of individuals with FH, centering equitable reach. METHODS: We will conduct a hybrid effectiveness-implementation type III randomized controlled trial testing the comparative effectiveness of two strategies for implementing cascade screening with 220 individuals with FH (i.e., probands) per arm identified from a large northeastern health system. The primary implementation outcome is reach, or the proportion of probands with at least one first-degree biological relative (parent, sibling, child) in the USA who is screened for FH through the study. Our secondary implementation outcomes include the number of relatives screened and the number of relatives meeting the American Heart Association criteria for FH. Our secondary clinical effectiveness outcome is post-trial proband cholesterol level. We will also use mixed methods to identify implementation strategy mechanisms for implementation strategy effectiveness while centering equity. DISCUSSION: We will test two patient-facing implementation strategies harnessing insights from behavioral economics that were developed collaboratively with constituents. This trial will improve our understanding of how to implement evidence-based cascade screening for FH, which implementation strategies work, for whom, and why. Learnings from this trial can be used to equitably scale cascade screening programs for FH nationally and inform cascade screening implementation efforts for other genetic disorders. TRIAL REGISTRATION: ClinicalTrials.gov, NCT05750667. Registered 15 February 2023-retrospectively registered, https://clinicaltrials.gov/study/NCT05750667 .

Polygenic risk score for acute rejection based on donor-recipient non-HLA genotype mismatch.

BACKGROUND: Acute rejection (AR) after kidney transplantation is an important allograft complication. To reduce the risk of post-transplant AR, determination of kidney transplant donor-recipient mismatching focuses on blood type and human leukocyte antigens (HLA), while it remains unclear whether non-HLA genetic mismatching is related to post-transplant complications. METHODS: We carried out a genome-wide scan (HLA and non-HLA regions) on AR with a large kidney transplant cohort of 784 living donor-recipient pairs of European ancestry. An AR polygenic risk score (PRS) was constructed with the non-HLA single nucleotide polymorphisms (SNPs) filtered by independence (r2 < 0.2) and P-value (< 1×10-3) criteria. The PRS was validated in an independent cohort of 352 living donor-recipient pairs. RESULTS: By the genome-wide scan, we identified one significant SNP rs6749137 with HR = 2.49 and P-value = 2.15×10-8. 1,307 non-HLA PRS SNPs passed the clumping plus thresholding and the PRS exhibited significant association with the AR in the validation cohort (HR = 1.54, 95% CI = (1.07, 2.22), p = 0.019). Further pathway analysis attributed the PRS genes into 13 categories, and the over-representation test identified 42 significant biological processes, the most significant of which is the cell morphogenesis (GO:0000902), with 4.08 fold of the percentage from homo species reference and FDR-adjusted P-value = 8.6×10-4. CONCLUSIONS: Our results show the importance of donor-recipient mismatching in non-HLA regions. Additional work will be needed to understand the role of SNPs included in the PRS and to further improve donor-recipient genetic matching algorithms. Trial registry: Deterioration of Kidney Allograft Function Genomics (NCT00270712) and Genomics of Kidney Transplantation (NCT01714440) are registered on ClinicalTrials.gov.

Polygenic risk scores for cardiometabolic traits demonstrate importance of ancestry for predictive precision medicine.

Polygenic risk scores (PRS) have predominantly been derived from genome-wide association studies (GWAS) conducted in European ancestry (EUR) individuals. In this study, we present an in-depth evaluation of PRS based on multi-ancestry GWAS for five cardiometabolic phenotypes in the Penn Medicine BioBank (PMBB) followed by a phenome-wide association study (PheWAS). We examine the PRS performance across all individuals and separately in African ancestry (AFR) and EUR ancestry groups. For AFR individuals, PRS derived using the multi-ancestry LD panel showed a higher effect size for four out of five PRSs (DBP, SBP, T2D, and BMI) than those derived from the AFR LD panel. In contrast, for EUR individuals, the multi-ancestry LD panel PRS demonstrated a higher effect size for two out of five PRSs (SBP and T2D) compared to the EUR LD panel. These findings underscore the potential benefits of utilizing a multi-ancestry LD panel for PRS derivation in diverse genetic backgrounds and demonstrate overall robustness in all individuals. Our results also revealed significant associations between PRS and various phenotypic categories. For instance, CAD PRS was linked with 18 phenotypes in AFR and 82 in EUR, while T2D PRS correlated with 84 phenotypes in AFR and 78 in EUR. Notably, associations like hyperlipidemia, renal failure, atrial fibrillation, coronary atherosclerosis, obesity, and hypertension were observed across different PRSs in both AFR and EUR groups, with varying effect sizes and significance levels. However, in AFR individuals, the strength and number of PRS associations with other phenotypes were generally reduced compared to EUR individuals. Our study underscores the need for future research to prioritize 1) conducting GWAS in diverse ancestry groups and 2) creating a cosmopolitan PRS methodology that is universally applicable across all genetic backgrounds. Such advances will foster a more equitable and personalized approach to precision medicine.

Spending Analysis of Machine Learning-Based Communication Nudges in Oncology.

BACKGROUND: Serious illness conversations (SICs) in the outpatient setting may improve mood and quality of life among patients with cancer and decrease aggressive end-of-life care. Interventions informed by behavioral economics may increase rates of SICs between oncology clinicians and patients, but the impact of these interventions on end-of-life spending is unknown. METHODS: This study is a secondary analysis of a stepped-wedge cluster randomized, controlled trial that involved nine medical oncology practices and their high-risk patients at a large academic institution between June 2019 and April 2020. The study included 1187 patients who were identified by a machine-learning algorithm as high risk of 180-day mortality and who died by December 2020. The patients were randomly assigned to standard of care (controls) or to a behavioral intervention designed to increase clinician-initiated SICs. We abstracted spending - defined as inflation-adjusted costs for acute care (inpatient plus emergency room), office/outpatient care, intravenous systemic therapy, other therapy (e.g., radiation), long-term care, and hospice - from the institution's accounting system, and we captured spending at inpatient, outpatient, and pharmacy settings. To evaluate intervention impacts on spending, we used a two-part model, first using logistic regression to model zero versus nonzero spending and second using generalized linear mixed models with gamma distribution and log-link function to model daily mean spending in the last 180days of life. Models were adjusted for clinic and wedge fixed effects, and they were clustered at the oncologist level. For all patients with at least one SIC within 6 months of death, we also calculated their mean daily spending before and after SIC. RESULTS: Median age at death was 68years (interquartile range, 15.5), 317 patients (27%) were Black or of ethnicities other than white, and 448 patients (38%) had an SIC. The intervention was associated with lower unadjusted mean daily spending in the last 6 months of life for the intervention group versus controls ($377.96 vs. $449.92; adjusted mean difference, -$75.33; 95% confidence interval, -$136.42 to -$14.23; P=0.02), translating to $13,747 total adjusted savings per decedent and $13 million in cumulative savings across all decedents in the intervention group. Compared with controls, patients in the intervention group incurred lower mean daily spending for systemic therapy (adjusted difference, -$44.59; P=0.001), office/outpatient care (-$9.62; P=0.001), and other therapy (-$8.65; P=0.04). The intervention was not associated with differences in end-of-life spending for acute care, long-term care, or hospice. Results were consistent for spending in the last 1 and 3 months of life and after adjusting for age, race, and ethnicity. For patients with SICs, mean daily spending decreased by $37.92 following the first SIC ($329.87 vs. $291.95). CONCLUSIONS: A machine learning-based, behaviorally informed intervention to prompt SICs led to end-of-life savings among patients with cancer, driven by decreased systemic therapy and outpatient spending. (Funded by the Penn Center for Precision Medicine and the National Institutes of Health; ClinicalTrials.gov number, NCT03984773.).