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Background Reduced kidney function is a risk factor of cardiovascular and all-cause mortality. This association was demonstrated for several kidney function markers, but it is unclear whether integrating multiple measured markers may improve mortality risk prediction. Methods We conducted an exploratory factor analysis (EFA) of serum creatinine– and cystatin C–based estimated glomerular filtration rate [eGFRcre and eGFRcys; derived by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) and European Kidney Function Consortium (EKFC) equations], blood urea nitrogen (BUN), uric acid and serum albumin among 366 758 participants in the UK Biobank without a history of kidney failure. Fitting Cox proportional hazards models, we compared the ability of the identified latent factors to predict overall mortality and mortality by cardiovascular disease (CVD), also considering CVD-specific causes like coronary heart disease (CHD) and cerebrovascular disease. Results During 12.5 years of follow-up, 26 327 participants died from any cause, 5376 died from CVD, 2908 died from CHD and 1116 died from cerebrovascular disease. We identified two latent factors, EFA1 and EFA2, both representing kidney function variations. When using the CKD-EPI equation, EFA1 performed like eGFRcys, with EFA1 showing slightly larger hazard ratios for overall and CVD-related mortality. At 10 years of follow-up, EFA1 and eGFRcys showed moderate discrimination performance for CVD-related mortality, outperforming all other kidney indices. eGFRcre was the least predictive marker across all outcomes. When using the EKFC equation, eGFRcys performed better than EFA1 while all other results remaining similar. Conclusions While EFA is an attractive approach to capture the complex effects of kidney function, eGFRcys remains the most practical and effective measurement for all-cause and CVD mortality risk prediction. [ABSTRACT FROM AUTHOR]

HLA antigens of patients with adult T cell leukaemia (ATL), T cell malignant lymphoma (T-ML), and healthy carriers of human T cell leukaemia virus type I (HTLV-I) were investigated in an endemic area of ATL in Japan. Sixty-two patients with ATL were subdivided into three groups based on their clinical features, including two unclassified patients; 36 acute type. 10 chronic type, and 14 smouldering type. The frequency of HLA-Bw62 was significantly increased in acute ATL, compared with control (Pc <0.0002). Increased frequency of HLA-DQw3 was observed in patients with ATL. T-ML positive for the antibody to HTLV-I (Ab-positive), and Ab-positive healthy carriers, compared with control (Pc < 0.001, Pc< 0.01 and Pc < 0.0001, respectively). In addition, class I HLA antigens of peripheral lymphocytes of patients with ATL, especially acute ATL, showed altered expression, either extra antigens or decreased antigens. Analysis of 21 families, where more than two members were Ab-positive, showed that there was no linkage between the HLA complex and susceptibility to the virus infection. In 44 couples, in which either or both spouses were Ab-positive, no association with class ! HLA antigens was found in either Ab-positive spouses or Ab-negative sprouses. These findings might indicate that one class II HLA-linked gene controlled susceptibility to HTLV-I infection, and another class I HLA-linked gene exerted an influence on the clinical course of ATL. [ABSTRACT FROM AUTHOR]

The autopsy records between 1980 and 1995 of 399 female rhesus monkeys (Macaca mulatta) at the Wisconsin Regional Primate Research Center were examined. Spontaneous endometriosis was found in 81 (20%) of the animals. The mean (+/- SD) ages at death for animals with and without endometriosis were 20.7 +/- 5.5 (range 10-35) and 13.4 +/- 7.7 (range 4-37) years respectively. Many of the animals had been exposed to experimental procedures, including laparoscopies, hysterotomies and oestradiol implants, and these were examined as possible risk factors for endometriosis. Of the 81 affected animals, 62 were matched to unaffected controls for age at death (to within 1 year) and year of death (to within 2 years) and the effect of various factors on the development of endometriosis was determined using conditional logistic regression. Exposure to three or more oestradiol implants or one or more hysterotomies were both significant risk factors, with estimated relative risks of 9.7 (95% confidence interval 2.5-37.2) and 5.8 (95% confidence interval 1.6-20.2) respectively. Animals that had been exposed to one or more laparoscopies showed no increased risk for developing endometriosis. These findings provide insight into the aetiology of the disease in women. ?2P51 4RR00167 [ABSTRACT FROM AUTHOR]

Background: A retrospective analysis was conducted on necropsy records from a large rhesus monkey colony to evaluate the age-related prevalence of endometriosis.Methods: A total of 314 records collected over a 15-year period were analyzed, yielding 66 monkeys with histologically verified endometriosis and 248 control subjects.Results: The analyses demonstrated that the incidence of endometriosis increases progressively across the life span, ultimately impacting 21-45% of aged monkeys over 20 years of age.Conclusions: Because mild disease is often not diagnosed premortem, the endocrine and immune sequelae of endometriosis may be a potential confound in even nonreproductive research with aging primates. Prior research-related events influence the occurrence and severity of endometriosis in these long-lived animals, and specifically could have contributed to the high prevalence of endometriosis in this particular monkey colony. [ABSTRACT FROM AUTHOR]

Introduction Studies suggest that many emergency department (ED) visits and hospitalizations for patients with cancer may be preventable. The Centers for Medicare & Medicaid Services has implemented changes to the hospital outpatient reporting program that targets acute care in-treatment patients for preventable conditions. Oncology urgent care centers aim to streamline patient care. Our cancer center developed an urgent care center called the direct referral unit in 2011. Methods We abstracted visits to our adjacent hospital ED and direct referral unit from January 2014 to June 2018. Patient demographics, cancer and visit diagnoses, visit charges, and 30-day therapy utilization were assessed. Results An analysis of 13 114 visits demonstrated that increased direct referral unit utilization was associated with decreased monthly ED visits (P  < .001). Common direct referral unit visit diagnoses were dehydration, nausea and vomiting, abdominal pain, and fever. Patients receiving active cancer treatment more frequently presented to the direct referral unit (P  < .001). The average charges were $2221 for the direct referral unit and $10 261 for the ED. Conclusion The association of decreased ED visits with increased direct referral unit utilization demonstrates the potential for urgent care centers to reduce acute care visits. Many patients presented to our direct referral unit with preventable conditions, and these visits were associated with considerable cost savings, supporting its use as a cost-effective method to reduce acute care costs. [ABSTRACT FROM AUTHOR]

Background Diabetes mellitus (DM) is associated with a greater risk of mortality in kidney transplant patients, primarily driven by a greater risk of cardiovascular disease (CVD)-related mortality. However, the associations between diabetes status at time of first allograft loss and mortality on dialysis remain unknown. Methods All patients with failed first kidney allografts transplanted in Australia and New Zealand between 2000 and 2020 were included. The associations between diabetes status at first allograft loss, all-cause and cause-specific mortality were examined using competing risk analyses, separating patients with diabetes into those with pre-transplant DM or post-transplant diabetes mellitus (PTDM). Results Of 3782 patients with a median (IQR) follow-up duration of 2.7 (1.1–5.4) years, 539 (14%) and 390 (10%) patients had pre-transplant DM or developed PTDM, respectively. In the follow-up period, 1336 (35%) patients died, with 424 (32%), 264 (20%) and 199 (15%) deaths attributed to CVD, dialysis withdrawal and infection, respectively. Compared to patients without DM, the adjusted subdistribution HRs (95% CI) for pre-transplant DM and PTDM for all-cause mortality on dialysis were 1.47 (1.17–1.84) and 1.47 (1.23–1.76), respectively; for CVD-related mortality were 0.81 (0.51–1.29) and 1.02 (0.70–1.47), respectively; for infection-related mortality were 1.84 (1.02–3.35) and 2.70 (1.73–4.20), respectively; and for dialysis withdrawal-related mortality were 1.71 (1.05–2.77) and 1.51 (1.02–2.22), respectively. Conclusions Patients with diabetes at the time of kidney allograft loss have a significant survival disadvantage, with the excess mortality risk attributed to infection and dialysis withdrawal. [ABSTRACT FROM AUTHOR]

Motivation Identification of genomic, molecular and clinical markers prognostic of patient survival is important for developing personalized disease prevention, diagnostic and treatment approaches. Modern omics technologies have made it possible to investigate the prognostic impact of markers at multiple molecular levels, including genomics, epigenomics, transcriptomics, proteomics and metabolomics, and how these potential risk factors complement clinical characterization of patient outcomes for survival prognosis. However, the massive sizes of the omics datasets, along with their correlation structures, pose challenges for studying relationships between the molecular information and patients' survival outcomes. Results We present a general workflow for survival analysis that is applicable to high-dimensional omics data as inputs when identifying survival-associated features and validating survival models. In particular, we focus on the commonly used Cox-type penalized regressions and hierarchical Bayesian models for feature selection in survival analysis, which are especially useful for high-dimensional data, but the framework is applicable more generally. Availability and implementation A step-by-step R tutorial using The Cancer Genome Atlas survival and omics data for the execution and evaluation of survival models has been made available at https://ocbe-uio.github.io/survomics. [ABSTRACT FROM AUTHOR]

Somatic copy number alterations (SCNAs) are a predominant type of oncogenomic alterations that affect a large proportion of the genome in the majority of cancer samples. Current technologies allow high-throughput measurement of such copy number aberrations, generating results consisting of frequently large sets of SCNA segments. However, the automated annotation and integration of such data are particularly challenging because the measured signals reflect biased, relative copy number ratios. In this study, we introduce labelSeg , an algorithm designed for rapid and accurate annotation of CNA segments, with the aim of enhancing the interpretation of tumor SCNA profiles. Leveraging density-based clustering and exploiting the length–amplitude relationships of SCNA, our algorithm proficiently identifies distinct relative copy number states from individual segment profiles. Its compatibility with most CNA measurement platforms makes it suitable for large-scale integrative data analysis. We confirmed its performance on both simulated and sample-derived data from The Cancer Genome Atlas reference dataset, and we demonstrated its utility in integrating heterogeneous segment profiles from different data sources and measurement platforms. Our comparative and integrative analysis revealed common SCNA patterns in cancer and protein-coding genes with a strong correlation between SCNA and messenger RNA expression, promoting the investigation into the role of SCNA in cancer development. [ABSTRACT FROM AUTHOR]

Background Anisakis infects humans by consuming contaminated undercooked or raw fish, leading to gastric anisakiasis, gastro-allergic anisakiasis, or asymptomatic contamination. Although larvae usually die when penetrating the gastric tissue, cases of intra- and extra-abdominal spread were described. We report the first probable case of pericardial anisakiasis. Case summary A 26-year-old man presented to the emergency department because of progressive lower limb oedema and exertional dyspnoea. Two months prior, he had consumed raw fish without any gastrointestinal symptoms. The echocardiogram reported a circumferential pericardial effusion ('swinging heart') and mildly reduced left ventricular ejection fraction (LVEF). He was diagnosed with myopericarditis after a cardiac magnetic resonance. A fluorodeoxyglucose positron emission tomography scan revealed an intense pericardial metabolism. Blood tests exhibited persistent eosinophilia and mild elevation of Anisakis simplex IgE—as for past infestation. A pericardial drainage was performed, subsequently, serial echocardiograms revealed a spontaneous recovery of his LVEF. No autoimmune, allergic, or onco-haematologic diseases were identified. Based on a history of feeding with potentially contaminated raw fish and on long-lasting eosinophilia, we suspected a pericardial anisakiasis, despite a low but persistent titre of specific IgE. Albendazole was administered for 21 days, along with colchicine and ibuprofen for 2 months; pericardial effusion resolution and eosinophil normalization occurred two weeks after. Discussion We hypothesized that Anisakis larvae may have migrated outside the gastrointestinal tract, penetrating the diaphragm and settling in the pericardium, causing pericarditis and pericardial effusion. Clinicians should know that the pericardium may be another extra-abdominal localization of anisakiasis, beyond pleuro-pulmonary involvement. [ABSTRACT FROM AUTHOR]

Background We require a clinicopathological risk stratification method for immunoglobulin A nephropathy (IgAN) to predict kidney outcomes. We examined a renal failure risk group (RF-RG) classification system created following a prior multicentre, retrospective study to determine if RF-RG could predict kidney outcomes. Methods We collected data from Japanese patients with IgAN registered between 1 April 2005 and 31 August 2015. The primary outcome was a composite 50% increase in serum creatinine from baseline or dialysis induction. The secondary outcomes were times to proteinuria remission (ProR) and haematuria remission (HemR). Results The enrolled 991 patients from 44 facilities were followed for a median of 5.5 years (interquartile range 2.5–7.5), during which 87 composite events (8.8%) occurred. RF-RG was significantly associated with the primary outcome {hazard ratio [HR] II 2.78 [95% confidence interval (CI) 1.12–6.93], III 7.15 (2.90–17.6), IV 33.4 (14.1–79.0), I as a reference, P  < .001}. The discrimination performance was good [C-statistic 0.81 (95% CI 0.76–0.86)] and the time-dependent C-statistics exceeded 0.8 over 10 years. Among the 764 patients with proteinuria and 879 patients with haematuria at baseline, 515 and 645 patients showed ProR and HemR, respectively. ProR was significantly less frequent in patients with advanced disease [subdistribution HR: II 0.79 (95% CI 0.67–0.94), III 0.53 (0.41–0.66), IV 0.15 (0.09–0.23), I as a reference, P  < .001]. We also observed an association between HemR and RF-RG. Conclusions RF-RG demonstrated good predictive ability for kidney outcomes. [ABSTRACT FROM AUTHOR]

Background Hypoxia-inducible factor prolyl hydroxylase inhibitors (HIF-PHIs) are new therapeutic agents for anaemia in chronic kidney disease (CKD). We evaluated by meta-analysis and meta-regression the efficacy and safety of HIF-PHIs in patients with CKD-related anaemia. Methods We selected phase 3 randomized clinical trials (RCTs) comparing HIF-PHIs and erythropoiesis-stimulating agents (ESAs) in dialysis and non-dialysis patients. Efficacy outcomes were the changes from baseline of haemoglobin, iron parameters (hepcidin, serum iron, TIBC, TSAT, ferritin) and intravenous iron dose; as safety outcomes we considered cancer, adjudicated major adverse cardiovascular events (MACE), MACE+ (MACE plus hospitalization for hearth failure or unstable angina or thromboembolic event), thrombotic events (deep vein thrombosis, pulmonary embolism), arterovenous fistula (AVF) thrombosis and death. Results We included 26 RCTs with 24   387 patients. Random effect meta-analysis of the unstandardized mean difference between HIF-PHIs and ESAs showed a significant change in haemoglobin levels from baseline of 0.10 g/dL (95% CI 0.02 to 0.17). Meta-regression analysis showed a significantly higher haemoglobin change for HIF-PHIs in younger patients and versus short-acting ESA (0.21 g/dL, 95% CI 0.12 to 0.29 versus –0.01, 95% CI –0.09 to 0.07 in studies using long-acting ESA, P  < .001). No significant effect on heterogeneity was found for type of HIF-PHIs. In comparison with ESAs, HIF-PHIs induced a significant decline in hepcidin and ferritin and a significant increase in serum iron and TIBC, while TSAT did not change; intravenous iron dose was lower with HIF-PHI (–3.1 mg/week, 95% CI –5.6 to –0.6, P  = .020). Rate ratio of cancer (0.93, 95% CI 0.76 to 1.13), MACE (1.00, 95% CI 0.94 to 1.07), MACE+ (1.01, 95% CI 0.95 to 1.06), thrombotic events (1.08, 95% CI 0.84 to 1.38), AVF thrombosis (1.02, 95% CI 0.93 to 1.13) and death (1.02, 95% CI 0.95 to 1.13) did not differ between HIF-PHIs and ESAs. Conclusions HIF-PHIs at the doses selected for the comparisons are effective in correcting anaemia in comparison with ESA therapy with a significant impact on iron metabolism without notable difference among various agents. No safety signals emerge with use of HIF-PHIs. [ABSTRACT FROM AUTHOR]

Background Current guidelines establish the same hemoglobin (Hb) and iron biomarkers targets for hemodialysis (HD) and peritoneal dialysis (PD) in patients receiving erythropoiesis-stimulating agents (ESAs) even though patients having PD are usually younger, more active and less comorbid. Unfortunately, specific renal anemia [anemia in chronic kidney disease (aCKD)] trials or observational studies on PD are scanty. The aims of this study were to describe current aCKD management, goals and adherence to clinical guidelines, identifying opportunities for healthcare improvement in PD patients. Methods This was a retrospective, nationwide, multicentre study including patients from 19 PD units. The nephrologists collected baseline data, demographics, comorbidities and data related to anemia management (laboratory values, previously prescribed treatments and subsequent adjustments) from electronic medical records. The European adaptation of KDIGO guidelines was the reference for definitions, drug prescriptions and targets. Results A total of 343 patients (mean age 62.9 years, 61.2% male) were included; 72.9% were receiving ESAs and 33.2% iron therapy [20.7% intravenously (IV)]. Eighty-two patients were receiving ESA without iron therapy, despite 53 of them having an indication according to the European Renal Best Practice guidelines. After laboratory results, iron therapy was only started in 15% of patients. Among ESA-treated patients, 51.9% had an optimal control [hemoglobin (Hb) 10–12 g/dL] and 28.3% between 12–12.9 g/dL. Seventeen patients achieved Hb >13 g/dL, and 12 of them remained on ESA after overshooting. Only three patients had Hb <10 g/dL without ESAs. Seven patients (2%) met criteria for ESA resistance (epoetin dose >300 IU/kg/week). The highest tertile of erythropoietin resistance index (>6.3 UI/kg/week/g/dL) was associated with iron deficiency and low albumin corrected by renal replacement therapy vintage and hospital admissions in the previous 3 months. Conclusion Iron therapy continues to be underused (especially IV). Low albumin, iron deficiency and prior events explain most of the ESA hyporesponsiveness. Hb targets are titrated to/above the upper limits. Thus, several missed opportunities for adequate prescriptions and adherence to guidelines were identified. [ABSTRACT FROM AUTHOR]

Aims The validated HCM Risk-Kids model provides accurate individualized estimates of sudden cardiac death risk in children with hypertrophic cardiomyopathy (HCM). A second validated model, PRIMaCY, also provides individualized estimates of risk, but its performance and clinical impact has not been independently investigated. The aim of this study was to investigate the clinical impact of using the PRIMaCY sudden cardiac death (SCD) risk model in childhood HCM. Methods and results The estimated 5-year SCD risk was calculated for children meeting diagnostic criteria for HCM in a large single-centre cohort using PRIMaCY (clinical and genetic) and HCM Risk-Kids model, and model performance was assessed. Three hundred one patients [median age 10 (interquartile range 4–14)] were followed up for an average of 4.9 (±3.8) years, during which 30 (10.0%) reached the SCD or equivalent event endpoint. Harrell's C -statistic for the clinical and genetic models was 0.66 [95% confidence interval (CI) 0.52–0.8] and 0.66 (95% CI 0.54–0.80) with a calibration slope of 0.19 (95% CI 0.04–0.54) and 0.26 (95% CI −0.03–0.62), respectively. The number needed to treat to potentially treat one life-threatening arrhythmia for the PRIMaCY clinical, PRIMaCY genetic, and HCM Risk-Kids models was 13.7, 14.5, and 9.4, respectively. Conclusion Although PRIMaCY has a similar discriminatory ability to that reported for HCM Risk-Kids, estimated risk estimates did not correlate well with observed risk. A higher proportion of patients met implantable cardioverter-defibrillator thresholds using PRIMaCY model compared with HCM Risk-Kids. This has important clinical implications as these patients will be exposed to a lifetime risk of complications and inappropriate therapies. [ABSTRACT FROM AUTHOR]

Microsatellite instability (MSI) is a hypermutator phenotype caused by DNA mismatch repair deficiency. MSI has been reported in various human cancers, particularly colorectal, gastric and endometrial cancers. MSI is a promising biomarker for cancer prognosis and immune checkpoint blockade immunotherapy. Several computational methods have been developed for MSI detection using DNA- or RNA-based approaches based on next-generation sequencing. Epigenetic mechanisms, such as DNA methylation, regulate gene expression and play critical roles in the development and progression of cancer. We here developed MSI-XGNN, a new computational framework for predicting MSI status using bulk RNA-sequencing and DNA methylation data. MSI-XGNN is an explainable deep learning model that combines a graph neural network (GNN) model to extract features from the gene-methylation probe network with a CatBoost model to classify MSI status. MSI-XGNN, which requires tumor-only samples, exhibited comparable performance with two well-known methods that require tumor-normal paired sequencing data, MSIsensor and MANTIS and better performance than several other tools. MSI-XGNN also showed good generalizability on independent validation datasets. MSI-XGNN identified six MSI markers consisting of four methylation probes (EPM2AIP1|MLH1:cg14598950, EPM2AIP1|MLH1:cg27331401, LNP1:cg05428436 and TSC22D2:cg15048832) and two genes (RPL22L1 and MSH4) constituting the optimal feature subset. All six markers were significantly associated with beneficial tumor microenvironment characteristics for immunotherapy, such as tumor mutation burden, neoantigens and immune checkpoint molecules such as programmed cell death-1 and cytotoxic T-lymphocyte antigen-4. Overall, our study provides a powerful and explainable deep learning model for predicting MSI status and identifying MSI markers that can potentially be used for clinical MSI evaluation. [ABSTRACT FROM AUTHOR]

For survival analysis in comparative coronavirus disease 2019 trials, the routinely used hazard ratio may not provide a meaningful summary of the treatment effect. The mean survival time difference/ratio is an intuitive, assumption-free alternative. However, for short-term studies, landmark mortality rate differences/ratios are more clinically relevant and should be formally analyzed and reported. [ABSTRACT FROM AUTHOR]

Background Cancer-related financial hardship is a side effect of cancer diagnosis and treatment, and affects both patients and caregivers. Although many oncology clinics have increased financial navigation services, few have resources to proactively provide financial counseling and assistance to families affected by cancer before financial hardship occurs. As part of an ongoing randomized study testing a proactive financial navigation intervention, S1912CD, among sites of the National Cancer Institute Community Oncology Research Program (NCORP), we conducted a baseline survey to learn more about existing financial resources available to patients and caregivers. Methods The NCORP sites participating in the S1912CD study completed a required 10-question survey about their available financial resources and an optional 5-question survey that focused on financial screening and navigation workflow and challenges prior to starting recruitment. The proportion of NCORP sites offering financial navigation services was calculated and responses to the optional survey were reviewed to determine current screening and navigation practices and identify any challenges. Results Most sites (96%) reported offering financial navigation for cancer patients. Sites primarily identified patients needing financial assistance through social work evaluations (78%) or distress screening tools (76%). Sites revealed challenges in addressing financial needs at the outset and through diagnosis, including lack of proactive screening and referral to financial navigation services as well as staffing challenges. Conclusions Although most participating NCORP sites offer some form of financial assistance, the survey data enabled identification of gaps and challenges in providing services. Utilizing community partners to deliver comprehensive financial navigation guidance to cancer patients and caregivers may help meet needs while reducing site burden. [ABSTRACT FROM AUTHOR]

The discovery and development of erythropoiesis-stimulating agents was a journey lasting more than a century, leading to the cloning and approval of recombinant human erythropoietin (rHuEpo). This was an impressive clinical advance, providing the possibility of correcting the symptoms associated with anaemia in chronic kidney disease. Associated iron use was needed to produce new haemoglobin-containing blood red cells. Partial anaemia correction became the standard of care since trials aiming for near-normal haemoglobin levels showed a higher risk of adverse cardiovascular events. Hoping to reduce the cardiovascular risks, a new category of drugs was developed and tested. Hypoxia-inducible factor prolyl hydroxylase inhibitors (HIF-PHIs) are small molecules than can be formulated into orally active pills. They simulate reduced tissue oxygen pressure, thus stimulating the production of endogenous erythropoietin (Epo) by the kidneys and liver. Clinical trials with these compounds demonstrated that HIF-PHIs are at least as effective as rHuEpo in treating or correcting anaemia in non-dialysis and dialysis patients. Trials with HIF-PHIs did not demonstrate superiority in safety outcomes and in some trials, outcomes were worse. There was also a focus on oral delivery, a possible beneficial iron-sparing effect and the ability to overcome Epo resistance in inflamed patients. A negative effect is possible iron depletion, which may explain adverse outcomes. [ABSTRACT FROM AUTHOR]

Background Progression of chronic kidney disease (CKD) has proven to be faster in men than in women. Whether the same holds true for cardiovascular risk remains ill-defined. Methods We conducted a pooled analysis of four cohort studies from 40 nephrology clinics in Italy including patients with CKD [estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2 or higher if proteinuria >0.15 g/day]. The aim was to compare multivariable-adjusted risk (hazard ratio, 95% confidence interval) of a composite cardiovascular endpoint (cardiovascular death and non-fatal myocardial infarction, congestive heart failure, stroke, revascularization, peripheral vascular disease and non-traumatic amputation) in women (n  = 1192) versus men (n  = 1635). Results At baseline, women had slightly higher systolic blood pressure (SBP) as compared with men (139 ± 19 vs 138 ± 18 mmHg, P  = .049), lower eGFR (33.4 vs 35.7 mL/min/1.73 m2, P  = .001) and lower urine protein excretion (0.30 g/day vs 0.45 g/day in men, P  < .001). Women did not differ from men in age and prevalence of diabetes, while having a lower prevalence of cardiovascular disease, left ventricular hypertrophy and smoking habit. During a median follow-up of 4.0 years, 517 fatal and non-fatal cardiovascular events were registered (199 in women and 318 in men). The adjusted risk of cardiovascular events was lower in women (0.73, 0.60–0.89, P  = .002) than in men; however, the cardiovascular risk advantage of women progressively diminished as SBP (as continuous variable) increased (P for interaction = .021). Similar results were obtained when considering SBP categories: when compared with men, women had lower cardiovascular risk for SBP <130 mmHg (0.50, 0.31–0.80, P  = .004) and SBP 130–140 mmHg (0.72, 0.53–0.99, P  = .038), while no difference was observed for SBP >140 mmHg (0.85, 0.64–1.11, P  = .232). Conclusions Higher BP levels abolish the cardiovascular protection seen in female vs male patients with overt CKD. This finding supports the need for higher awareness of hypertensive burden in women with CKD. [ABSTRACT FROM AUTHOR]

Aims To determine whether fully automated artificial intelligence-based global circumferential strain (GCS) assessed during vasodilator stress cardiovascular (CV) magnetic resonance (CMR) can provide incremental prognostic value. Methods and results Between 2016 and 2018, a longitudinal study included all consecutive patients with abnormal stress CMR defined by the presence of inducible ischaemia and/or late gadolinium enhancement. Control subjects with normal stress CMR were selected using a propensity score-matching. Stress-GCS was assessed using a fully automatic machine-learning algorithm based on featured-tracking imaging from short-axis cine images. The primary outcome was the occurrence of major adverse clinical events (MACE) defined as CV mortality or nonfatal myocardial infarction. Cox regressions evaluated the association between stress-GCS and the primary outcome after adjustment for traditional prognosticators. In 2152 patients [66 ± 12 years, 77% men, 1:1 matched patients (1076 with normal and 1076 with abnormal CMR)], stress-GCS was associated with MACE [median follow-up 5.2 (4.8–5.5) years] after adjustment for risk factors in the propensity-matched population [adjusted hazard ratio (HR), 1.12 (95% CI, 1.06–1.18)], and patients with normal CMR [adjusted HR, 1.35 (95% CI, 1.19–1.53), both P < 0.001], but not in patients with abnormal CMR (P = 0.058). In patients with normal CMR, an increased stress-GCS showed the best improvement in model discrimination and reclassification above traditional and stress CMR findings (C-statistic improvement: 0.14; NRI = 0.430; IDI = 0.089, all P < 0.001; LR-test P < 0.001). Conclusion Stress-GCS is not a predictor of MACE in patients with ischaemia, but has an incremental prognostic value in those with a normal CMR although the absolute event rate remains low. [ABSTRACT FROM AUTHOR]

Aging is the most significant risk factor for neurodegenerative disorders such as Alzheimer's disease (AD) associated with profound socioeconomic and personal costs. Consequently, there is an urgent need for animal models that recapitulate the age-related spatial and temporal complexity and patterns of pathology identical to human AD. Our research in aging nonhuman primate models involving rhesus macaques has revealed naturally occurring amyloid and tau pathology, including the formation of amyloid plaques and neurofibrillary tangles comprising hyperphosphorylated tau. Moreover, rhesus macaques exhibit synaptic dysfunction in association cortices and cognitive impairments with advancing age, and thus can be used to interrogate the etiological mechanisms that generate neuropathological cascades in sporadic AD. Particularly, unique molecular mechanisms (eg, feedforward cyclic adenosine 3ʹ,5ʹ-monophosphate [cAMP]-Protein kinase A (PKA)-calcium signaling) in the newly evolved primate dorsolateral prefrontal cortex are critical for persistent firing required for subserving higher-order cognition. For example, dendritic spines in primate dorsolateral prefrontal cortex contain a specialized repertoire of proteins to magnify feedforward cAMP-PKA-calcium signaling such as N -methyl- d -aspartic acid receptors and calcium channels on the smooth endoplasmic reticulum (eg, ryanodine receptors). This process is constrained by phosphodiesterases (eg, PDE4) that hydrolyze cAMP and calcium-buffering proteins (eg, calbindin) in the cytosol. However, genetic predispositions and age-related insults exacerbate feedforward cAMP-Protein kinase A-calcium signaling pathways that induce a myriad of downstream effects, including the opening of K+ channels to weaken network connectivity, calcium-mediated dysregulation of mitochondria, and activation of inflammatory cascades to eliminate synapses, thereby increasing susceptibility to atrophy. Therefore, aging rhesus macaques provide an invaluable model to explore novel therapeutic strategies in sporadic AD. [ABSTRACT FROM AUTHOR]

Based on the smoothed partial rank (SPR) loss function, we propose a group LASSO penalized SPR estimator for the varying coefficient nonparametric transformation models, and derive its estimation and model selection consistencies. It not only selects important variables, but is also able to select between varying and constant coefficients. To deal with the computational challenges in the rank loss function, we develop a group forward and backward stagewise algorithm and establish its convergence property. An empirical application of a Boston housing dataset demonstrates the benefit of the proposed estimators. It allows us to capture the heterogeneous marginal effects of high-dimensional covariates and reduce model misspecification simultaneously that otherwise cannot be accomplished by existing approaches. [ABSTRACT FROM AUTHOR]

Competing risks data are commonly encountered in randomized clinical trials and observational studies. This paper considers the situation where the ending statuses of competing events have different clinical interpretations and/or are of simultaneous interest. In clinical trials, often more than one competing event has meaningful clinical interpretations even though the trial effects of different events could be different or even opposite to each other. In this paper, we develop estimation procedures and inferential properties for the joint use of multiple cumulative incidence functions (CIFs). Additionally, by incorporating longitudinal marker information, we develop estimation and inference procedures for weighted CIFs and related metrics. The proposed methods are applied to a COVID‐19 in‐patient treatment clinical trial, where the outcomes of COVID‐19 hospitalization are either death or discharge from the hospital, two competing events with completely different clinical implications. [ABSTRACT FROM AUTHOR]

Measuring the treatment effect on recurrent events like hospitalization in the presence of death has long challenged statisticians and clinicians alike. Traditional inference on the cumulative frequency unjustly penalizes survivorship as longer survivors also tend to experience more adverse events. Expanding a recently suggested idea of the "while‐alive" event rate, we consider a general class of such estimands that adjust for the length of survival without losing causal interpretation. Given a user‐specified loss function that allows for arbitrary weighting, we define as estimand the average loss experienced per unit time alive within a target period and use the ratio of this loss rate to measure the effect size. Scaling the loss rate by the width of the corresponding time window gives us an alternative, and sometimes more photogenic, way of showing the data. To make inferences, we construct a nonparametric estimator for the loss rate through the cumulative loss and the restricted mean survival time and derive its influence function in closed form for variance estimation and testing. As simulations and analysis of real data from a heart failure trial both show, the while‐alive approach corrects for the false attenuation of treatment effect due to patients living longer under treatment, with increased statistical power as a result. The proposed methods are implemented in the R‐package WA, which is publicly available from the Comprehensive R Archive Network (CRAN). [ABSTRACT FROM AUTHOR]

In the context of time‐to‐event analysis, a primary objective is to model the risk of experiencing a particular event in relation to a set of observed predictors. The Concordance Index (C‐Index) is a statistic frequently used in practice to assess how well such models discriminate between various risk levels in a population. However, the properties of conventional C‐Index estimators when applied to left‐truncated time‐to‐event data have not been well studied, despite the fact that left‐truncation is commonly encountered in observational studies. We show that the limiting values of the conventional C‐Index estimators depend on the underlying distribution of truncation times, which is similar to the situation with right‐censoring as discussed in Uno et al. (2011) [On the C‐statistics for evaluating overall adequacy of risk prediction procedures with censored survival data. Statistics in Medicine 30(10), 1105–1117]. We develop a new C‐Index estimator based on inverse probability weighting (IPW) that corrects for this limitation, and we generalize this estimator to settings with left‐truncated and right‐censored data. The proposed IPW estimators are highly robust to the underlying truncation distribution and often outperform the conventional methods in terms of bias, mean squared error, and coverage probability. We apply these estimators to evaluate a predictive survival model for mortality among patients with end‐stage renal disease. [ABSTRACT FROM AUTHOR]

Background: It is unclear whether pathological staging is significant prognostically and can inform the delivery of adjuvant therapy after pancreatectomy preceded by neoadjuvant therapy. Methods: This multicentre retrospective study included patients who underwent pancreatectomy for pancreatic ductal adenocarcinoma after neoadjuvant treatment at two Italian centres between 2013 and 2017. T and N status were assigned in accordance with the seventh and eighth editions of the AJCC staging system, as well as according to a modified system with T status definition combining extrapancreatic invasion and tumour size. Patients were then stratified by receipt of adjuvant therapy. Survival analysis and multivariable interaction analysis of adjuvant therapy with pathological parameters were performed. The results were validated in an external cohort from the USA. Results: The developmental set consisted of 389 patients, with a median survival of 34.6 months. The modified staging system displayed the best prognostic stratification and the highest discrimination (C-index 0.763; 1-, 2- and 3-year time-dependent area under the curve (AUC) 0.746, 0.722, and 0.705; Uno's AUC 0.710). Overall, 67.0 per cent of patients received adjuvant therapy. There was no survival difference by receipt of adjuvant therapy (35.0 versus 36.0 months; P = 0.772). After multivariable adjustment, interaction analysis suggested a benefit of adjuvant therapy for patients with nodal metastases or with tumours larger than 2 cm with extrapancreatic extension, regardless of nodal status. These results were confirmed in the external cohort of 216 patients. Conclusion: Modified staging with a T status definition combining extrapancreatic invasion and tumour size is associated with better prognostic segregation after postneoadjuvant pancreatectomy. This system allows identification of patients who might benefit from adjuvant therapy. [ABSTRACT FROM AUTHOR]

Background Declines in the prevalence of cigarette smoking, advances in targeted therapies, and implementation of lung cancer screening have changed the clinical landscape for lung cancer. The proportion of lung cancer deaths is increasing in those who have never smoked cigarettes. To better understand contemporary patterns in survival among patients with lung cancer, a comprehensive evaluation of factors associated with survival, including differential associations by smoking status, is needed. Methods Patients diagnosed with lung cancer between January 1, 2010, and September 30, 2019, were identified. We estimated all-cause and lung cancer-specific median, 5-year, and multivariable restricted mean survival time (RMST) to identify demographic, socioeconomic, and clinical factors associated with survival, overall and stratified by smoking status (never, former, and current). Results Analyses included 6813 patients with lung cancer: 13.9% never smoked, 54.2% formerly smoked, and 31.9% currently smoked. All-cause RMST through 5 years for those who never, formerly, and currently smoked was 32.1, 25.9, and 23.3 months, respectively. Lung cancer–specific RMST was 36.3 months, 30.3 months, and 26.0 months, respectively. Across most models, female sex, younger age, higher socioeconomic measures, first-course surgery, histology, and body mass index were positively associated, and higher stage was inversely associated with survival. Relative to White patients, Black patients had increased survival among those who formerly smoked. Conclusions We identify actionable factors associated with survival between those who never, formerly, and currently smoked cigarettes. These findings illuminate opportunities to address underlying mechanisms driving lung cancer progression, including use of first-course treatment, and enhanced implementation of tailored smoking cessation interventions for individuals diagnosed with cancer. [ABSTRACT FROM AUTHOR]

Aims We investigated the prevalence and clinical value of assessing multi-organ congestion by ultrasound in heart failure (HF) outpatients. Methods and results Ultrasound congestion was defined as inferior vena cava of ≥21 mm, highest tertile of lung B-lines, or discontinuous renal venous flow. Associations with clinical characteristics and prognosis were explored. We enrolled 310 HF patients [median age: 77 years, median NT-proBNP: 1037 ng/L, 51% with a left ventricular ejection fraction (LVEF) <50%], and 101 patients without HF. There were no clinical signs of congestion in 224 (72%) patients with HF, of whom 95 (42%) had at least one sign of congestion by ultrasound (P < 0.0001). HF patients with ≥2 ultrasound signs were older, and had greater neurohormonal activation, lower urinary sodium concentration, and larger left atria despite similar LVEF. During a median follow-up of 13 (interquartile range: 6–15) months, 77 patients (19%) died or were hospitalized for HF. HF patients without ultrasound evidence of congestion had a similar outcome to patients without HF [reference; hazard ratio (HR) 1.02, 95% confidence interval (CI) 0.86–1.35], while those with ≥2 ultrasound signs had the worst outcome (HR 26.7, 95% CI 12.4–63.6), even after adjusting for multiple clinical variables and NT-proBNP. Adding multi-organ assessment of congestion by ultrasound to a clinical model, including NT-proBNP, provided a net reclassification improvement of 28% (P = 0.03). Conclusion Simultaneous assessment of pulmonary, venous, and kidney congestion by ultrasound is feasible, fast, and identifies a high prevalence of sub-clinical congestion associated with poor outcomes. [ABSTRACT FROM AUTHOR]

Prediction models are often built and evaluated using data from a population that differs from the target population where model-derived predictions are intended to be used in. In this article, we present methods for evaluating model performance in the target population when some observations are right censored. The methods assume that outcome and covariate data are available from a source population used for model development and covariates, but no outcome data, are available from the target population. We evaluate the finite sample performance of the proposed estimators using simulations and apply the methods to transport a prediction model built using data from a lung cancer screening trial to a nationally representative population of participants eligible for lung cancer screening. [ABSTRACT FROM AUTHOR]

Leveraging large-scale electronic health record (EHR) data to estimate survival curves for clinical events can enable more powerful risk estimation and comparative effectiveness research. However, use of EHR data is hindered by a lack of direct event time observations. Occurrence times of relevant diagnostic codes or target disease mentions in clinical notes are at best a good approximation of the true disease onset time. On the other hand, extracting precise information on the exact event time requires laborious manual chart review and is sometimes altogether infeasible due to a lack of detailed documentation. Current status labels—binary indicators of phenotype status during follow-up—are significantly more efficient and feasible to compile, enabling more precise survival curve estimation given limited resources. Existing survival analysis methods using current status labels focus almost entirely on supervised estimation, and naive incorporation of unlabeled data into these methods may lead to biased estimates. In this article, we propose Semisupervised Calibration of Risk with Noisy Event Times (SCORNET), which yields a consistent and efficient survival function estimator by leveraging a small set of current status labels and a large set of informative features. In addition to providing theoretical justification of SCORNET, we demonstrate in both simulation and real-world EHR settings that SCORNET achieves efficiency akin to the parametric Weibull regression model, while also exhibiting semi-nonparametric flexibility and relatively low empirical bias in a variety of generative settings. [ABSTRACT FROM AUTHOR]

Although vocal signals, including languages and songbird syllables, are composed of a finite number of acoustic elements, diverse vocal sequences are composed of a combination of these elements, which are linked together by syntactic rules. However, the neural basis of syntactic vocalization generation remains poorly understood. Here, we report that inhibition using tetrodotoxin (TTX) and manipulations of gamma-aminobutyric acid (GABA) receptors within the basal ganglia Area X or lateral magnocellular nucleus of the anterior neostriatum (LMAN) alter and prolong repetitive vocalization in Bengalese finches (Lonchura striata var. domestica). These results suggest that repetitive vocalizations are modulated by the basal ganglia and not solely by higher motor cortical neurons. These data highlight the importance of neural circuits, including the basal ganglia, in the production of stereotyped repetitive vocalizations and demonstrate that dynamic disturbances within the basal ganglia circuitry can differentially affect the repetitive temporal features of songs. [ABSTRACT FROM AUTHOR]

Hip fractures are common in patients of advanced age and are associated with excess mortality. Rapid and accurate prediction of the prognosis using information that can be easily obtained before surgery would be advantageous to clinical management. We performed a population‐based retrospective cohort study using an 8.5‐year Japanese claims database (April 2012–September 2020) to develop and validate a predictive model for long‐term mortality after hip fracture. The study included 43,529 patients (34,499 [79.3%] women) aged ≥65 years with first‐onset hip fracture. During the observation period, 43% of the patients died. Cox regression analysis identified the following prognostic predictors: sex, age, fracture site, nursing care certification, and several comorbidities (any malignancy, renal disease, congestive heart failure, chronic pulmonary disease, liver disease, metastatic solid tumor, and deficiency anemia). We then developed a scoring system called the Shizuoka Hip Fracture Prognostic Score (SHiPS); this system was established by scoring based on each hazard ratio and classifying the degree of mortality risk into four categories based on decision tree analysis. The area under the receiver operating characteristic (ROC) curve (AUC) (95% confidence interval [CI]) of 1‐year, 3‐year, and 5‐year mortality based on the SHiPS was 0.718 (95% CI, 0.706–0.729), 0.736 (95% CI, 0.728–0.745), and 0.758 (95% CI, 0.747–0.769), respectively, indicating good predictive performance of the SHiPS for as long as 5 years after fracture onset. Even when the SHiPS was individually applied to patients with or without surgery after fracture, the prediction performance by the AUC was >0.7. These results indicate that the SHiPS can predict long‐term mortality using preoperative information regardless of whether surgery is performed after hip fracture. [ABSTRACT FROM AUTHOR]

The restricted mean survival time (RMST) evaluates the expectation of survival time truncated by a prespecified time point, because the mean survival time in the presence of censoring is typically not estimable. The frequentist inference procedure for RMST has been widely advocated for comparison of two survival curves, while research from the Bayesian perspective is rather limited. For the RMST of both right‐ and interval‐censored data, we propose Bayesian nonparametric estimation and inference procedures. By assigning a mixture of Dirichlet processes (MDP) prior to the distribution function, we can estimate the posterior distribution of RMST. We also explore another Bayesian nonparametric approach using the Dirichlet process mixture model and make comparisons with the frequentist nonparametric method. Simulation studies demonstrate that the Bayesian nonparametric RMST under diffuse MDP priors leads to robust estimation and under informative priors it can incorporate prior knowledge into the nonparametric estimator. Analysis of real trial examples demonstrates the flexibility and interpretability of the Bayesian nonparametric RMST for both right‐ and interval‐censored data. [ABSTRACT FROM AUTHOR]

Screening mammography aims to identify breast cancer early and secondarily measures breast density to classify women at higher or lower than average risk for future breast cancer in the general population. Despite the strong association of individual mammography features to breast cancer risk, the statistical literature on mammogram imaging data is limited. While functional principal component analysis (FPCA) has been studied in the literature for extracting image‐based features, it is conducted independently of the time‐to‐event response variable. With the consideration of building a prognostic model for precision prevention, we present a set of flexible methods, supervised FPCA (sFPCA) and functional partial least squares (FPLS), to extract image‐based features associated with the failure time while accommodating the added complication from right censoring. Throughout the article, we hope to demonstrate that one method is favored over the other under different clinical setups. The proposed methods are applied to the motivating data set from the Joanne Knight Breast Health cohort at Siteman Cancer Center. Our approaches not only obtain the best prediction performance compared to the benchmark model, but also reveal different risk patterns within the mammograms. [ABSTRACT FROM AUTHOR]

Objective: Pituitary adenomas and their consequences impact mortality and morbidity. We studied the healthcare costs, survival, and cost-effectiveness of growth hormone (GH) vs no GH replacement in patients with non-functioning pituitary adenoma (NFPA). Design and methods: A cohort study including all NFPA patients followed from 1987 or the date of diagnosis until the time of death or December 31, 2019, in the Västra Gotaland region, Sweden. Data to assess resource use, costs, survival, and cost-effectiveness were collected from patient records and regional/national healthcare registries. Results: A total of 426 patients with NFPA (274 men) with a follow-up of 13.6 ± 6.8 years (mean ± SD) were included. The total annual healthcare cost was higher in patients receiving GH (€9287) than those without GH (€6770), mainly driven by a higher pharmaceutical cost. Glucocorticoid replacement therapy (P = .02), diabetes insipidus (P = .04), body mass index (BMI) (P < .01), and hypertension (P < .01) were all individually associated with a higher total annual cost. The survival rate was higher in the GH group (HR [hazard ratio] 0.60; P = .01) and reduced in patients with glucocorticoid replacement (HR 2.02; P< .01) or diabetes insipidus (HR 1.67; P = .04). The cost per gained life-year for GH vs no GH replacement was about €37 000. Conclusions: This healthcare utilization study identified several factors driving the cost of care in NFPA patients, such as GH replacement, adrenal insufficiency, and diabetes insipidus. Life expectancy was increased in those with GH replacement and reduced in patients with B adrenal insufficiency and diabetes insipidus. [ABSTRACT FROM AUTHOR]

Objective The purpose of this systematic review was to identify and appraise externally validated prognostic models to predict a patient's health outcomes relevant to physical rehabilitation of musculoskeletal (MSK) conditions. Methods We systematically reviewed 8 databases and reported our findings according to Preferred Reporting Items for Systematic Reviews and Meta-Analysis 2020. An information specialist designed a search strategy to identify externally validated prognostic models for MSK conditions. Paired reviewers independently screened the title, abstract, and full text and conducted data extraction. We extracted characteristics of included studies (eg, country and study design), prognostic models (eg, performance measures and type of model) and predicted clinical outcomes (eg, pain and disability). We assessed the risk of bias and concerns of applicability using the prediction model risk of bias assessment tool. We proposed and used a 5-step method to determine which prognostic models were clinically valuable. Results We found 4896 citations, read 300 full-text articles, and included 46 papers (37 distinct models). Prognostic models were externally validated for the spine, upper limb, lower limb conditions, and MSK trauma, injuries, and pain. All studies presented a high risk of bias. Half of the models showed low concerns for applicability. Reporting of calibration and discrimination performance measures was often lacking. We found 6 externally validated models with adequate measures, which could be deemed clinically valuable [ie, (1) STart Back Screening Tool, (2) Wallis Occupational Rehabilitation RisK model, (3) Da Silva model, (4) PICKUP model, (5) Schellingerhout rule, and (6) Keene model]. Despite having a high risk of bias, which is mostly explained by the very conservative properties of the PROBAST tool, the 6 models remain clinically relevant. Conclusion We found 6 externally validated prognostic models developed to predict patients' health outcomes that were clinically relevant to the physical rehabilitation of MSK conditions. Impact Our results provide clinicians with externally validated prognostic models to help them better predict patients' clinical outcomes and facilitate personalized treatment plans. Incorporating clinically valuable prognostic models could inherently improve the value of care provided by physical therapists. [ABSTRACT FROM AUTHOR]

In the last decade, studies in persons with HIV (PWH) on antiretroviral therapy (ART) have shed light on the significance of persistently high CD8 counts and low CD4/CD8 ratios. A low CD4/CD8 ratio reflects increased immune activation and is associated with an increased risk of severe non-AIDS events. As a result, many clinicians now believe that the CD4/CD8 ratio can help in HIV monitoring, and many researchers now report it as an efficacy marker in interventional studies. However, the topic is more complex. Recent studies have not yielded unanimous conclusions on the ability of the CD4/CD8 ratio to predict adverse outcomes, and only some clinical guidelines recommend monitoring it. Knowledge gaps remain on the best cutoff points, associated clinical events, effects of treatments, and how the CD4/CD8 ratio could improve decision making in the clinic. Here, we critically review the literature, identify knowledge gaps, and discuss the role of the CD4/CD8 ratio as a marker for HIV monitoring. [ABSTRACT FROM AUTHOR]

With the emergence of hypoxia inducible factor–prolyl hydroxylase inhibitors (HIF-PHIs) came the hope that using these oral drugs could improve the treatment of the anemia of kidney disease. In this editorial we discuss the accumulated knowledge on these agents and the clinical context for use. [ABSTRACT FROM AUTHOR]

Background In the I CARE study, colon cancer patients were randomly assigned to receive follow-up care from either a general practitioner (GP) or a surgeon. Here, we address a secondary outcome, namely, detection of recurrences and effect on time to detection of transferring care from surgeon to GP. Methods Pattern, stage, and treatment of recurrences were described after 3 years. Time to event was defined as date of surgery, until date of recurrence or last follow-up, with death as competing event. Effects on time to recurrence and death were estimated as hazard ratios (HRs) using Cox regression. Restricted mean survival times were estimated. Results Of 303 patients, 141 were randomly assigned to the GP and 162 to the surgeon. Patients were male (67%) with a mean age of 68.0 (8.4) years. During follow-up, 46 recurrences were detected; 18 (13%) in the GP vs 28 (17%) in the surgeon group. Most recurrences were detected via abnormal follow-up tests (74%) and treated with curative intent (59%). Hazard ratio for recurrence was 0.75 (95% confidence interval [CI] = 0.41 to 1.36) in GP vs surgeon group. Patients in the GP group remained in the disease-free state slightly longer (2.76 vs 2.71 years). Of the patients, 38 died during follow-up; 15 (11%) in the GP vs 23 (14%) in the surgeon group. Of these, 21 (55%) deaths were related to colon cancer. There were no differences in overall deaths between the groups (HR = 0.76, 95% CI = 0.39 to 1.46). Conclusion Follow-up provided by GPs vs surgeons leads to similar detection of recurrences. Also, no differences in mortality were found. [ABSTRACT FROM AUTHOR]

To grade the long-term benefit of anticancer agents, the American Society of Clinical Oncology Value Framework (ASCO-VF) awards tail-of-the-curve bonus points by using milestone survival at twice the median control survival. Here, we propose an alternative, late-life expectancy that we defined as the area under the Kaplan-Meier curve from median control survival to the end of follow-up. We analyzed all indications of immune checkpoint inhibitors with survival data and found that 9 indications out of 13 (69.2%) qualified for ASCO-VF tail-of-the-curve bonus points either in progression-free or overall survival. Our proposed score recognized a long-term benefit not captured by the ASCO-VF, for example, for CHECKMATE-66 where twice the median overall survival was not reached. We found that nivolumab was associated with an increase of 65.3% (95% CI = 38.9 to 89.5) in overall survival late-life expectancy, which highlights its important long-term benefit. In conclusion, the ASCO-VF could be improved with the use of late-life expectancy. [ABSTRACT FROM AUTHOR]

With mammography being the primary breast cancer screening strategy, it is essential to make full use of the mammogram imaging data to better identify women who are at higher and lower than average risk. Our primary goal in this study is to extract mammogram-based features that augment the well-established breast cancer risk factors to improve prediction accuracy. In this article, we propose a supervised functional principal component analysis (sFPCA) over triangulations method for extracting features that are ordered by the magnitude of association with the failure time outcome. The proposed method accommodates the irregular boundary issue posed by the breast area within the mammogram imaging data with flexible bivariate splines over triangulations. We also provide an eigenvalue decomposition algorithm that is computationally efficient. Compared to the conventional unsupervised FPCA method, the proposed method results in a lower Brier Score and higher area under the ROC curve (AUC) in simulation studies. We apply our method to data from the Joanne Knight Breast Health Cohort at Siteman Cancer Center. Our approach not only obtains the best prediction performance comparing to unsupervised FPCA and benchmark models but also reveals important risk patterns within the mammogram images. This demonstrates the importance of utilizing additional supervised image-based features to clarify breast cancer risk. [ABSTRACT FROM AUTHOR]

Tumor-induced osteomalacia (TIO) is an ultrarare paraneoplastic syndrome due to overproduction of fibroblast growth factor 23 (FGF23), with profound effects on patient morbidity. TIO is an underdiagnosed disease, whose awareness should be increased among physicians for timely and proper management of patients. Symptoms reported by patients with TIO are usually nonspecific, thus rendering the diagnosis elusive, with an initial misdiagnosis rate of more than 95%. Biochemical features of TIO are represented by hypophosphatemia, increased or inappropriately normal levels of FGF23, and low to low normal circulating 1,25-dihydroxyvitamin D (1,25(OH)2D). Phosphaturic mesenchymal tumors are the pathological entities underlying TIO in most affected patients. There is now evidence that FN1-FGFR1 and FN1-FGF1 fusion genes are present in about half of tumors causing this paraneoplastic syndrome. Tumors causing TIO are small and grow slowly. They can occur in all parts of the body from head to toe with similar prevalence in soft tissue and bone. There are a number of functional and anatomical imaging techniques used for tumor localization; 68Ga DOTA-based technologies have better sensitivity. Surgery is the treatment of choice; several medical treatments are now available in case of inability to locate the tumor or in case of incomplete excision. [ABSTRACT FROM AUTHOR]

Deer have been a major resource for human populations for thousands of years. Anthropogenic activities, such as hunting, have influenced the genetic structure and distribution of deer populations. In Japan, wild Japanese sika deer (Cervus nippon) have been hunted since ancient times but have also been historically protected as sacred animals in several sanctuaries. Sika deer have been protected for over a thousand years in the religious sanctuary around the Kasuga Taisha Shrine on the Kii Peninsula, located in the center of Japan. Here, we used short sequence repeats (SSR) and mitochondrial DNA (mtDNA) to investigate the genetic diversity, population structure, and demography of Japanese sika deer inhabiting the Kii Peninsula, Japan, and discuss possible anthropogenic influences. Using SSR, three distinct genetic groups were distinguished on the Kii Peninsula: an Eastern genetic group, a Western genetic group, and an isolated genetic group with individuals in the religious sanctuary of Kasuga Taisha Shrine in Nara city. The isolated genetic sanctuary group had only the mtDNA haplotype S4. The SSR genotype data suggested a newer divergence time of the genetic groups of the religious sanctuary than would have occurred as a result of Late Quaternary climate change. This time scale coincided with the establishment of the sanctuary with Kasuga Taisha Shrine. Thus, the religious protection conserved genetic variation over a thousand years. [ABSTRACT FROM AUTHOR]

Readily available proxies for the time of disease onset such as the time of the first diagnostic code can lead to substantial risk prediction error if performing analyses based on poor proxies. Due to the lack of detailed documentation and labor intensiveness of manual annotation, it is often only feasible to ascertain for a small subset the current status of the disease by a follow‐up time rather than the exact time. In this paper, we aim to develop risk prediction models for the onset time efficiently leveraging both a small number of labels on the current status and a large number of unlabeled observations on imperfect proxies. Under a semiparametric transformation model for onset and a highly flexible measurement error model for proxy onset time, we propose the semisupervised risk prediction method by combining information from proxies and limited labels efficiently. From an initially estimator solely based on the labeled subset, we perform a one‐step correction with the full data augmenting against a mean zero rank correlation score derived from the proxies. We establish the consistency and asymptotic normality of the proposed semisupervised estimator and provide a resampling procedure for interval estimation. Simulation studies demonstrate that the proposed estimator performs well in a finite sample. We illustrate the proposed estimator by developing a genetic risk prediction model for obesity using data from Mass General Brigham Healthcare Biobank. [ABSTRACT FROM AUTHOR]