Prognostic Covariates Research Articles

Effects of body mass index on worsening of heart failure and all-cause death in patients with heart failure and reduced left ventricular ejection fraction: a 10-year follow-up study

Abstract Background/Introduction Obesity in patients with heart failure (HF) with reduced ejection fraction (HFrEF) is common, and with the emergence of effective anti-obesity drugs, a better understanding of the relation between BMI and clinical outcome in HFrEF is needed. Purpose This study aimed to analyse whether a body mass index (BMI) above 27 kg/m2 (cut-off used in trials) is associated with a greater rate of all-cause death and HF hospitalization in patients with HFrEF. Methods We included 1,017 medically optimized according to existing HF guidelines at the time and clinically stable HF patients with a left ventricular ejection fraction of <45% from the NorthStar study. Patients were included between 2005 and 2009 and followed for 10 years using Danish nationwide registries. The outcomes of interest were all-cause death and hospital discharge for HF (overnight stay). Descriptive statistics were grouped according to tertiles of BMI. The association between BMI as a continuous variable and the outcomes of interest was analysed using restricted cubic splines in Cox proportional-hazards models. Reported were hazard ratios (HR) with 95% confidence intervals (CI) adjusted for relevant prognostic covariates (reference: BMI = 27 kg/m2). Results At enrolment, the median age was 69 years, 75% were men, and the median BMI was 26.3 kg/m2 (Table 1). Patients in the upper 3rd BMI tertile were younger (median age 67), had a lower level of NT-proBNP level (median 737.5 pg/ml) and a higher proportion of diabetes (29.9%). During 10 years of follow-up, HF hospitalization occurred in 683 patients (61.7%), and 623 patients died (56.3%). A BMI above 27 kg/m2 was associated with a higher rate of HF hospitalization (significantly from BMI 35.2 kg/m2: HR 1.30 [CI 1.00-1.68]; Figure 1). Similar findings were observed for all-cause mortality (significantly from BMI 35.7 kg/m2: HR 1.27 [CI 1.00-1.62]) Conclusion In patients with HFrEF, a BMI above 27 kg/m2 was associated with a higher rate of HF hospitalization and all-cause death. Efforts to find effective and safe approaches to reducing weight in obese patients with HFrEF are warranted.Figure 1

Prognostic significance of pre-procedure wall shear stress in the ascending aorta in patients with aortic stenosis undergoing transcatheter aortic valve replacement

Abstract Background Accurate prognostication before the procedure is challenging in patients with aortic stenosis (AS) undergoing transcatheter aortic valve replacement (TAVR). Recently, blood flow dynamics assessed by four-dimensional flow cardiovascular magnetic resonance imaging (4D-flow CMR) showed a significant reduction in average wall shear stress (WSS) in the ascending aorta (AAo) after TAVR. However, the prognostic value of pre-procedure average WSS in the AAo is controversial. Purpose We aimed to investigate whether pre-procedure average WSS was associated with clinical outcomes in patients with AS undergoing TAVR. Methods We prospectively examined 159 consecutive AS patients who underwent TAVR (57 males, mean age 83.6 ± 4.7 years, median left ventricular ejection fraction 63.4%) between May 2018 and May 2022. We assessed average WSS in the AAo before TAVR using 4D-flow CMR. We divided the patients into high WSS (≥6.60 Pa, n = 79) and low WSS (<6.60 Pa, n = 80) groups according to the median value of pre-TAVR WSS. The primary outcome of interest was a composite of all-cause death and hospitalization for worsening heart failure. Results Patients with high WSS had lower age compared to those with low WSS. There were no significant differences on sex, body mass index, systolic blood pressure, hemoglobin, serum albumin, N-terminal pro b-type natriuretic peptide, left ventricular ejection fraction, mean transaortic valvular gradient, annulus area in aortic valve and AAo diameter between the groups. During a median follow-up period of 19.8 months (interquartile range 6.0-37.1), the primary outcome more frequently occurred in patients with low WSS than in those with high WSS (28% vs 5%, P <0.001) (Figure 1). A multivariable Cox regression showed that lower WSS independently associated with increased risk of the primary outcome (hazard ratio 0.69, 95% confidence interval [CI] 0.53-0.91, P <0.001), even after adjustment for significant prognostic covariates including age, sex, serum albumin, history of chronic obstructive pulmonary disease, peripheral artery disease and malignancy, and estimated glomerular filtration rate. Predictive performance for the primary outcome was improved when adding the value of WSS in the AAo to representative prognostic factors (c-index 0.81 95%CI 0.72-0.90 vs. 0.77 95%CI 0.67-0.88) (Figure 2). Conclusions In patients with AS who underwent TAVR, lower average WSS in the AAo before procedure was associated with higher risk of worse clinical outcomes, suggesting that pre-TAVR average WSS in the AAo would be a surrogate marker and useful for the risk stratification.Survival analysis for primary outcomePredictive performance

The Cancer Patient Empowerment Program: A Comprehensive Approach to Reducing Psychological Distress in Cancer Survivors, with Insights from a Mixed-Model Analysis, Including Implications for Breast Cancer Patients.

Psychological distress is a significant concern among cancer patients, negatively affecting their quality of life and adherence to treatment. The Cancer Patient Empowerment Program (CancerPEP) was developed as a comprehensive, home-based intervention aimed at reducing psychological distress by incorporating physical activity, dietary guidance, and social support. This study aimed to evaluate the feasibility, accrual and attrition rates, safety, and effectiveness of the CancerPEP intervention, with and without the biofeedback device, on psychological distress from baseline to 6 months, specifically focusing on the effects of group randomization and the difference between pre- and post-intervention results. This single-site, crossover randomized clinical trial included 104 cancer patients who were randomized to receive the CancerPEP intervention, with or without a Heart Rate Variability (HRV) biofeedback monitor. At 6 months, participants who did not receive the device were allowed to use one until the end of the year, while those who did receive the device were followed up to 12 months. Randomization was stratified by the presence or absence of clinically significant psychological distress and metastatic status. Psychological distress was assessed using the Kessler Psychological Distress Scale (K10) at baseline, 6 months, and 12 months. The primary endpoint was the presence of nonspecific psychological distress, as measured by the K10 scale at 6 months from the trial start, based on group randomization. A secondary exploratory analysis assessed psychological distress at baseline, 6 months, and 12 months for both groups, while controlling for group randomization and prognostic covariates. Prognostic covariates included age; comorbidities; time between diagnosis and randomization; treatment modality; relationship status; and use of prescribed medications for anxiety, depression, or both. An exploratory sub-analysis was conducted for the breast cancer subgroup, based on the sample size available after recruitment. The trial is registered at ClinicalTrials.gov (NCT05508412). The provision of the HRV biofeedback monitor in conjunction with the CancerPEP intervention did not significantly affect the primary outcome in either the full sample or the breast cancer subgroup, indicating that the HRV biofeedback provision was not beneficial in this trial. No self-reported or otherwise discovered adverse events at the 6-month mark were observed. About 10% of participants were lost to follow-up in both the early and late HRV monitor provision groups. Participation in the CancerPEP program led to a significant reduction in psychological distress over time. The odds of psychological distress were significantly higher at the start of the trial than at the end of the intervention (aOR = 2.64, 95% CI: 1.53-4.56) or 6 months after the intervention (aOR = 2.94, 95% CI: 1.62-5.30). Similarly, in the breast cancer subgroup, distress was higher at the trial's start than at 6 months, i.e., after the intervention (aOR = 2.25, 95% CI: 1.24-4.08), or at the end of the trial at 12 months (aOR = 2.73, 95% CI: 1.35-5.52). CancerPEP significantly reduces psychological distress in cancer patients, with consistent improvements noted across various cancer types and stages, including benefits specifically for breast cancer patients. These findings build upon the success of the Prostate Cancer Patient Empowerment Program (PC-PEP), indicating that a similar comprehensive intervention can be advantageous for all cancer patients and may be further tailored to address specific needs. With its holistic approach-encompassing physical, dietary, and psychosocial support-CancerPEP shows promise as a vital component of survivorship care. Ongoing 24-month evaluations will yield critical data on its long-term benefits. Additionally, a randomized trial with a control group (usual care without intervention) for breast cancer patients is currently under way and could potentially guide the integration of CancerPEP into standard oncology care to enhance patient outcomes and quality of life.

Geniculate ganglion diverticulum: a potential imaging marker in patients with idiopathic intracranial hypertension

PurposeThe diagnosis of idiopathic intracranial hypertension (IIH) is often challenging in patients who do not present with classic symptoms. Brain MRI can play a pivotal role, as several imaging findings, such as an empty sella appearance (ESA), have been shown to be associated with IIH. Yet, none of the MRI signs have been shown to have a high sensitivity and specificity. In this study, we tested the hypothesis that presence of a geniculate ganglion diverticulum (GGD) is a potential imaging marker for the detection of IIH. Materials and methodsThis is an IRB-approved, single-institution, retrospective, observational study. Brain MRI examinations of patients referred to Radiology by Otology clinic over a period of 10 years were reviewed. 244 MRI exams fulfilling inclusion and exclusion criteria were independently screened for the presence of GGD and ESA by two Neuroradiology fellows. Electronic medical records (EMR) of patients in this study were reviewed for presence of clinical manifestations of IIH. Receiver operator characteristic (ROC) curves were generated to estimate the accuracy of each covariate in diagnosing IIH. The area under each ROC curve (AUC) was calculated to identify an accurate prognostic covariate. Statistical analysis was done using R programming language V 4.2.2. ResultsGGD was identified in MRI exams of 51 patients. A 2:1 propensity score (PS) matching for age, gender, and Body Mass Index (BMI) was used to select non-GGD control group for comparison with the GGD group. There was strong agreement between the 2 reviewers (kappa = 0.81, agreement = 95 %). Twelve patients in this study were diagnosed with IIH. There was a high incidence of GGD (OR = 12.19, 95 % CI (2.56, 58.10)) and ESA (OR = 4.97, 95 % CI (1.47, 16.74)) in IIH patients. The AUC observed in GGD for predicting IIH was 0.771 (0.655–0.888), specificity = 0.709 (0.638–0.780), and sensitivity = 0.833 (0.583–1). The AUC observed for ESA in predicting IIH was 0.682 (0.532–0.831), specificity = 0.780 (0.709–0.844), and sensitivity = 0.583 (0.333–0.833). ConclusionGGD is potentially a novel imaging marker of IIH with sensitivity higher than and specificity comparable to that of ESA. Clinical relevance statementPresence of GGD should raise the possibility of IIH.

The reality of rurality: Understanding the impact of remoteness on out-of-hospital cardiac arrest in Western Australia - A retrospective cohort study.

Western Australia (WA) spans a large, sparsely-populated area of Australia, presenting a challenge for the provision of Emergency Medical Service (EMS), particularly for time-critical emergencies such as out-of-hospital cardiac arrest (OHCA). To assess the impact of rurality on the epidemiology, incidence and survival of OHCA in WA. We conducted a retrospective cohort study of EMS-attended OHCA in WA from 2015 to 2022. Incidence was calculated on all OHCAs, but the study cohort for the multivariable regression analysis of rurality on survival outcomes consisted of OHCAs of medical aetiology with EMS resuscitation attempted. Rurality was categorised into four categories, derived from the Australian Standard Geographic Classification - Remoteness Areas. The age-standardised incidence of EMS-attended OHCA per 100 000 population increased with increasing remoteness: Major Cities = 104.9, Inner Regional = 123.3, Outer Regional = 138.0 and Remote = 103.9. Compared to Major Cities, the adjusted odds for return of spontaneous circulation (ROSC) at hospital were lower in Inner Regional (aOR = 0.71, 95%CI 0.53-0.95), Outer Regional (aOR = 0.62, 95%CI 0.45-0.86) and Remote areas (aOR = 0.52, 95%CI 0.35-0.77) but there was no statistically significant difference for 30-day survival. Relative to Major Cities, Regional and Remote areas had longer response times, shorter transport-to-hospital times, and higher rates of bystander CPR and automated external defibrillator use. Out-of-hospital cardiac arrest in rural areas had lower odds of ROSC at hospital compared to metropolitan areas, despite adjustment for known prognostic covariates. Despite WA's highly sparse regional population, these differences in ROSC are consistent with those reported in other international studies.

Increasing Power in Phase III Oncology Trials With Multivariable Regression: An Empirical Assessment of 535 Primary End Point Analyses.

A previous study demonstrated that power against the (unobserved) true effect for the primary end point (PEP) of most phase III oncology trials is low, suggesting an increased risk of false-negative findings in the field of late-phase oncology. Fitting models with prognostic covariates is a potential solution to improve power; however, the extent to which trials leverage this approach, and its impact on trial interpretation at scale, is unknown. To that end, we hypothesized that phase III trials using multivariable PEP analyses are more likely to demonstrate superiority versus trials with univariable analyses. PEP analyses were reviewed from trials registered on ClinicalTrials.gov. Adjusted odds ratios (aORs) were calculated by logistic regressions. Of the 535 trials enrolling 454,824 patients, 69% (n = 368) used a multivariable PEP analysis. Trials with multivariable PEP analyses were more likely to demonstrate PEP superiority (57% [209 of 368] v 42% [70 of 167]; aOR, 1.78 [95% CI, 1.18 to 2.72]; P = .007). Among trials with a multivariable PEP model, 16 conditioned on covariates and 352 stratified by covariates. However, 108 (35%) of 312 trials with stratified analyses lost power by categorizing a continuous variable, which was especially common among immunotherapy trials (aOR, 2.45 [95% CI, 1.23 to 4.92]; P = .01). Trials increasing power by fitting multivariable models were more likely to demonstrate PEP superiority than trials with unadjusted analysis. Underutilization of conditioning models and empirical power loss associated with covariate categorization required by stratification were identified as barriers to power gains. These findings underscore the opportunity to increase power in phase III trials with conventional methodology and improve patient access to effective novel therapies.

Multimorbidity and adverse outcomes following emergency department attendance: population based cohort study

ObjectivesTo describe the effect of multimorbidity on adverse patient centred outcomes in people attending emergency department.DesignPopulation based cohort study.SettingEmergency departments in NHS Lothian in Scotland, from 1 January 2012 to...

Avelumab first-line maintenance in advanced urothelial carcinoma: Complete screening for prognostic and predictive factors using machine learning in the JAVELIN Bladder 100 phase 3 trial.

Avelumab first-line (1 L) maintenance is a standard of care for advanced urothelial carcinoma (aUC) based on the JAVELIN Bladder 100 phase 3 trial, which showed that avelumab 1 L maintenance + best supportive care (BSC) significantly prolonged overall survival (OS) and progression-free survival (PFS) vs BSC alone in patients who were progression free after receiving 1 L platinum-containing chemotherapy. Here, we comprehensively screened JAVELIN Bladder 100 trial datasets to identify prognostic factors that define subpopulations of patients with longer or shorter OS irrespective of treatment, and predictive factors that select patients who could obtain a greater OS benefit from avelumab 1 L maintenance treatment. We performed machine learning analyses to screen a large set of baseline covariates, including patient demographics, disease characteristics, laboratory values, molecular biomarkers, and patient-reported outcomes. Covariates were identified from previously reported analyses and established prognostic and predictive markers. Variables selected from random survival forest models were processed further in univariate Cox models with treatment interaction and visually inspected using correlation analysis and Kaplan-Meier curves. Results were summarized in a multivariable Cox model. Prognostic baseline covariates associated with OS included in the final model were assignment to avelumab 1 L maintenance treatment, Eastern Cooperative Oncology Group performance status, site of metastasis, sum of longest target lesion diameters, levels of C-reactive protein and alkaline phosphatase in blood, lymphocyte proportion in intratumoral stroma, tumor mutational burden, and tumor CD8+ T-cell infiltration. Potential predictive factors included site of metastasis, tumor mutation burden, and tumor CD8+ T-cell infiltration. An analysis in patients with PD-L1+ tumors had similar findings to those in the overall population. Machine learning analyses of data from the JAVELIN Bladder 100 trial identified potential prognostic and predictive factors for avelumab 1 L maintenance treatment in patients with aUC, which warrant further evaluation in other clinical datasets.

Covariate adjustment and estimation of difference in proportions in randomized clinical trials.

Difference in proportions is frequently used to measure treatment effect for binary outcomes in randomized clinical trials. The estimation of difference in proportions can be assisted by adjusting for prognostic baseline covariates to enhance precision and bolster statistical power. Standardization or g-computation is a widely used method for covariate adjustment in estimating unconditional difference in proportions, because of its robustness to model misspecification. Various inference methods have been proposed to quantify the uncertainty and confidence intervals based on large-sample theories. However, their performances under small sample sizes and model misspecification have not been comprehensively evaluated. We propose an alternative approach to estimate the unconditional variance of the standardization estimator based on the robust sandwich estimator to further enhance the finite sample performance. Extensive simulations are provided to demonstrate the performances of the proposed method, spanning a wide range of sample sizes, randomization ratios, and model specification. We apply the proposed method in a real data example to illustrate the practical utility.

Nutritional status as independent prognostic factor of outcome and mortality until five years after hip fracture: a comprehensive prospective study

SummaryWe determined the prognostic value of nutritional status for outcome after hip fracture. Nutritional status was a strong independent prognostic factor for clinical outcome and 5-year mortality. Physical function showed incomplete recovery. Elderly care should focus on prevention already before hip fracture.PurposeTo determine the prognostic value of nutritional status in hip fracture patients for multiple clinical and functional outcomes over 6 months, and for new fractures and survival over 5 years post-fracture.MethodsWe included 152 well-characterized subjects (age 55+ years) with a hip fracture from a previously published randomized controlled trial. Nutritional status was appraised using the Mini Nutritional Assessment (MNA). Multivariable linear, logistic and Cox regression models were fitted, adjusted for age, sex, ASA score, group and additional prognostic covariates identified in backward regression models.ResultsAt baseline, impaired nutritional status was significantly associated with physical disability, depression, impaired cognition and lower quality of life. Prospective analyses showed that impaired baseline nutritional status was an independent prognostic factor for postoperative complications (OR 2.00, 95%CI 1.01–3.98, p = 0.047), discharge location from hospital (home vs. rehabilitation clinic, OR 0.41, 95%CI 0.18–0.98, p = 0.044), hospital readmission (OR 4.59, 95%CI 1.70–12.4, p = 0.003) and total length of hospital stay (HR of being discharged: 0.63, 96%CI 0.44–0.89, p = 0.008), as well as for 5-year mortality (HR 3.94, 95%CI 1.53–10.2, p = 0.005), but not for risk of new fractures (5y-HR 0.87, 95%CI 0.34–2.24, p = 0.769). Curves of physical disability over time showed that the three nutritional status categories followed almost parallel trajectories from baseline until 6 months after hip fracture, without complete recovery and even with further deterioration in malnourished subjects from 3 to 6 months post-fracture.ConclusionAs baselline nutritional status is a strong independent prognostic factor for clinical outcome after hip fracture, affecting even five-year survival, elderly health care should focus on prevention and identification of at-risk individuals already before hip fracture.

Concordance between SARS-CoV-2 index individuals and their household contacts on index individual COVID-19 transmission cofactors: a comparison of self-reported and contact-reported information

BackgroundFollowing the outbreak of the COVID-19 pandemic, several clinical trials have evaluated postexposure prophylaxis (PEP) among close contacts of an index individual with a confirmed SARS-CoV-2 infection. Because index individuals do not directly inform the efficacy of prevention interventions, they are seldom enrolled in COVID-19 PEP studies. However, adjusting for prognostic covariates such as an index individual’s COVID-19 illness and risk behaviors can increase precision in PEP efficacy estimates, so approaches to accurately collecting this information about the index individual are needed. This analysis aimed to assess whether surveying household contacts captures the same information as surveying the index individual directly.MethodsREGN 2069/CoVPN 3502, a randomized controlled trial of COVID-19 PEP, enrolled household contacts of SARS-CoV-2 index individuals. CoVPN 3502-01 retrospectively enrolled and surveyed the index individuals. We compared responses to seven similar questions about the index individuals’ transmission cofactors that were asked in both studies. We estimated the percent concordance between index individuals and their household contacts on each question, with 50% concordance considered equivalent to random chance.ResultsConcordance between index individuals and contacts was high on the most objective questions, approximately 97% (95% CI: 90–99%) for index individual age group and 96% (88–98%) for hospitalization. Concordance was moderate for symptoms, approximately 85% (75–91%). Concordance on questions related to the index individual’s behavior was only slightly better or no better than random: approximately 62% (51–72%) for whether they received COVID-19 treatment, 68% (57–77%) for sharing a bedroom, 70% (59–79%) for sharing a common room, and 49% (39–60%) for mask wearing at home. However, while contacts were surveyed within 96 h of the index individual testing positive for SARS-CoV-2, the median time to enrollment in CoVPN 3502-01 was 240 days, which may have caused recall bias in our results.ConclusionsOur results suggest a need to survey index individuals directly in order to accurately capture their transmission cofactors, rather than relying on their household contacts to report on their behavior. The lag in enrolling participants into CoVPN 3502-01 also highlights the importance of timely enrollment to minimize recall bias.

Clinical Outcomes of Urgent or Emergency Transcatheter Aortic Valve Implantation - Insights From the Nationwide Registry of Japan Transcatheter Valve Therapies.

Limited data are available for clinical outcomes in patients who underwent urgent or emergency transcatheter aortic valve implantation (TAVI). This study investigated in-hospital and 1-year outcomes and explored prognostic covariates in urgent/emergency TAVI using nationwide registry data.Methods and Results: Among 26,775 patients who underwent TAVI between August 2013 and December 2019, 25,495 with 1-year follow-up information were analyzed in this study. Baseline and procedural characteristics, as well as clinical adverse events, were compared between the urgent/emergency and elective TAVI groups. The primary outcome was all-cause mortality within 1 year after TAVI. Multivariable Cox regression models were constructed to identify independent predictors after urgent or emergency TAVI. Urgent or emergency TAVI was performed in 578 (2.3%) patients. The Society of Thoracic Surgeons score was significantly higher in the urgent/emergency than elective TAVI group (13.3% vs. 6.0%; P<0.001). Device success rate was comparable between the 2 groups. All-cause death-free survival within 1 year was lower in the urgent/emergency than elective TAVI group (77.2% vs. 92.2%; log rank P<0.001). Malignancy, albumin and creatinine concentrations, ejection fraction, and mean pressure gradient were associated with 1-year mortality in the urgent/emergency TAVI group. Despite higher surgical risk and more comorbidities, the procedure was successfully performed in patients undergoing urgent/emergency TAVI, although it should be noted that prognosis was worse than for elective TAVI.

Comparative prognostic importance of measures of left atrial structure and function in non-ischaemic dilated cardiomyopathy.

To compare the association between measures of left atrial (LA) structure and function, derived from cardiovascular magnetic resonance (CMR), with cardiovascular (CV) death or non-fatal heart failure (HF) events in patients with non-ischaemic dilated cardiomyopathy (DCM). CMR studies of 580 prospectively recruited patients with DCM in sinus rhythm (median age 54 [interquartile range 44-64] years, 61% men, median LVEF 42% [30-51%]) were analysed for measures of LA structure (left atrial maximum volume index [LAVImax], left atrial minimum volume index [LAVImin]) and function (left atrial emptying fraction [LAEF], left atrial reservoir strain [LARS], left atrial conduit strain [LACS] and left atrial booster strain [LABS]). Over median follow-up of 7.4 years, 103 patients (18%) met the primary endpoint. Apart from LACS, each measure of LA structure and function was associated with the primary endpoint after adjusting for other important prognostic variables. The addition of each LA metric to a baseline model containing the same important prognostic covariates improved model discrimination, with LAVImin providing the greatest improvement (C-statistic improvement: 0.702 to 0.738; χ2 test comparing likelihood ratio p < 0.0001; categorical net reclassification index: 0.210 (95% CI 0.023-0.392)). Patients in the highest tercile of LAVImin had similar event rates to those with persistent atrial fibrillation. Measures of LA strain did not enhance model discrimination above LA volumetric measures. Measure of left atrial structure and function offer important prognostic information in patients with DCM and enhance prediction of adverse outcomes. LA strain was not incremental to volumetric analysis for risk prediction.

Evaluating pharmacological THRomboprophylaxis in Individuals undergoing superficial endoVEnous treatment across NHS and private clinics in the UK: a multi-centre, assessor-blind, randomised controlled trial—THRIVE trial

IntroductionEndovenous therapy is the first choice management for symptomatic varicose veins in NICE guidelines, with 56–70 000 procedures performed annually in the UK. Venous thromboembolism (VTE), including deep vein thrombosis...

Transcatheter aortic valve replacement in heart failure.

Patients with severe aortic stenosis (AS) may develop heart failure (HF), the presence of which has traditionally been deemed as a final stage in AS progression with poor outcomes. The use of transcatheter aortic valve replacement (TAVR) has become the preferred therapy for most patients with AS and concomitant HF. With its instant afterload reduction, TAVR offers patients with HF significant haemodynamic benefits, with corresponding changes in left ventricular structure and improved mortality and quality of life. The prognostic covariates and optimal timing of TAVR in patients with less than severe AS remain unclear. The purpose of this review is to describe the association between TAVR and outcomes in patients with HF, particularly in the setting of left ventricular systolic dysfunction, acute HF, and right ventricular systolic dysfunction, and to highlight areas for future research.

Use of conditional estimates of effect in cancer epidemiology: An application to lung cancer treatment

BackgroundIn oncology clinical trials, there is the assumption that randomization sufficiently balances confounding covariates and therefore average treatment effects are usually reported. This paper explores the wider benefits provided by conditioning on covariates for reasons other than mitigation of confounding. MethodsWe reanalyzed the data from primary randomized controlled trials listed in two meta-analyses to explore the significance of conditioning on smoking status in terms of the effect magnitude of treatment on progression free survival in non-small cell lung cancer. ResultsThe reanalysis revealed that conditioning on smoking status using sub-group analyses provided the closest empiric estimate of individual treatment effect based on smoking status and significantly reduced the heterogeneity of treatment effect observed across studies. In addition, smoking status was determined to be a modifier of the effect of treatment. ConclusionConditioning on prognostic covariates in randomized trials in oncology helps generate the closest empiric estimates of individual treatment benefit, addresses heterogeneity due to varying covariate distributions across trials and facilitates future decision making as well as evidence synthesis. Conditioning using sub-group analyses also allows examination for effect modification in meta-analysis.

Unanchored Population-Adjusted Indirect Comparison Methods for Time-to-Event Outcomes Using Inverse Odds Weighting, Regression Adjustment, and Doubly Robust Methods With Either Individual Patient or Aggregate Data

ObjectivesSeveral methods for unanchored population-adjusted indirect comparisons (PAICs) are available. Exploring alternative adjustment methods, depending on the available individual patient data (IPD) and the aggregate data (AD) in the external study, may help minimize bias in unanchored indirect comparisons. However, methods for time-to-event outcomes are not well understood. This study provides an overview and comparison of methods using a case study to increase familiarity. A recent method is applied to marginalize conditional hazard ratios, which allows for the comparisons of methods, and a doubly robust method is proposed. MethodsThe following PAIC methods were compared through a case study in third-line small cell lung cancer, comparing nivolumab with standard of care based on a single-arm phase II trial (CheckMate 032) and real-world study (Flatiron) in terms of overall survival: IPD-IPD analyses using inverse odds weighting, regression adjustment, and a doubly robust method; IPD-AD analyses using matching-adjusted indirect comparison, simulated treatment comparison, and a doubly robust method. ResultsNivolumab extended survival versus standard of care with hazard ratios ranging from 0.63 (95% CI 0.44-0.90) in naive comparisons (identical estimates for IPD-IPD and IPD-AD analyses) to 0.69 (95% CI 0.44-0.98) in the IPD-IPD analyses using regression adjustment. Regression-based and doubly robust estimates yielded slightly wider confidence intervals versus the propensity score-based analyses. ConclusionsThe proposed doubly robust approach for time-to-event outcomes may help to minimize bias due to model misspecification. However, all methods for unanchored PAIC rely on the strong assumption that all prognostic covariates have been included.

Machine learning-based gait analysis to predict clinical frailty scale in elderly patients with heart failure.

Although frailty assessment is recommended for guiding treatment strategies and outcome prediction in elderly patients with heart failure (HF), most frailty scales are subjective, and the scores vary among raters. We sought to develop a machine learning-based automatic rating method/system/model of the clinical frailty scale (CFS) for patients with HF. We prospectively examined 417 elderly (≥75 years) with symptomatic chronic HF patients from 7 centres between January 2019 and October 2023. The patients were divided into derivation (n = 194) and validation (n = 223) cohorts. We obtained body-tracking motion data using a deep learning-based pose estimation library, on a smartphone camera. Predicted CFS was calculated from 128 key features, including gait parameters, using the light gradient boosting machine (LightGBM) model. To evaluate the performance of this model, we calculated Cohen's weighted kappa (CWK) and intraclass correlation coefficient (ICC) between the predicted and actual CFSs. In the derivation and validation datasets, the LightGBM models showed excellent agreements between the actual and predicted CFSs [CWK 0.866, 95% confidence interval (CI) 0.807-0.911; ICC 0.866, 95% CI 0.827-0.898; CWK 0.812, 95% CI 0.752-0.868; ICC 0.813, 95% CI 0.761-0.854, respectively]. During a median follow-up period of 391 (inter-quartile range 273-617) days, the higher predicted CFS was independently associated with a higher risk of all-cause death (hazard ratio 1.60, 95% CI 1.02-2.50) after adjusting for significant prognostic covariates. Machine learning-based algorithms of automatically CFS rating are feasible, and the predicted CFS is associated with the risk of all-cause death in elderly patients with HF.

Synergistic effects of immune checkpoint inhibitors in combination with stereotactic radiosurgery for patients with lung cancer and brain metastases: a propensity score-matched analysis.

Stereotactic radiosurgery (SRS) is the mainstay treatment for brain metastases (BMs) from lung cancer. In recent years, immune checkpoint inhibitors (ICIs) have been applied to metastatic lung cancer and have contributed to improved outcomes. The authors investigated whether SRS with concurrent ICIs for lung cancer BMs prolongs overall survival (OS), improves intracranial disease control, and raises safety concerns. Patients who underwent SRS for lung cancer BMs at Aizawa Hospital between January 2015 and December 2021 were included. Concurrent use of ICIs was defined as no more than 3 months between SRS and ICI administration. The two treatment groups, which had a similar likelihood of receiving concurrent ICIs, were generated by propensity score matching (PSM; match ratio 1:1) based on 11 potential prognostic covariates. Patient survival and intracranial disease control were compared between the groups with and without concurrent ICIs (ICI + SRS vs SRS) by time-dependent analyses, taking into account competing events. Five hundred eighty-five patients with lung cancer BM (494 with non-small cell lung cancer and 91 with small cell lung cancer) were eligible. Of those patients, 93 (16%) received concurrent ICIs. Two groups, each with 89 patients (ICI + SRS group and SRS group), were generated by PSM. The 1-year survival rates of the ICI + SRS and SRS groups after the initial SRS were 65% and 50% and the median survival times were 16.9 and 12.0 months, respectively (HR 0.62, 95% CI 0.44-0.87, p = 0.006). The 2-year cumulative neurological mortality rates were 12% and 16%, respectively (HR 0.55, 95% CI 0.28-1.10, p = 0.091). The 1-year intracranial progression-free survival rates were 35% and 26% (HR 0.73, 95% CI 0.53-0.99, p = 0.047). The 2-year local failure rates were 12% and 18% (HR 0.72, 95% CI 0.32-1.61, p = 0.43) and the 2-year distant recurrence rates were 51% and 60% (HR 0.82, 95% CI 0.55-1.23, p = 0.34). Severe adverse radiation events (Common Terminology Criteria for Adverse Events [CTCAE] grade 4) occurred in 1 patient in each group, and CTCAE grade 3 toxicities were observed in 3 patients in the ICI + SRS group and in 5 in the SRS group (OR 1.53, 95% CI 0.35-7.7, p = 0.75). The present study found that SRS with concurrent ICIs for patients with lung cancer BMs was associated with longer survival and durable intracranial disease control, with no apparent increase in treatment-related adverse events.

A Prognostic Nomogram Survival Model for Newly Diagnosed Patients with AIDS-Related Diffuse Large B-Cell Lymphoma: A Multicenter Cohort Study in China

BACKGROUND The prognosis of patients with AIDS-related diffuse large B-cell lymphoma(AR-DLBCL) becomes very poor when the lymphoma relapses or is refractory to first line immunochemotherapy. We aimed to develop a novel ARDPI nomogram prognostic model for risk stratification so as to guide individualized treatment to achieve sustained remission and improve the overall prognosis for newly-diagnosed AR-DLBCL patients. METHODS We interrogated data from 306 patients with newly-diagnosed AR-DLBCL. We filtered variables using LASSO regression and Cox regression to identify prognostic co-variates and develop a survival model, we termed AR-DLBCL Prognostic Index (ARDPI). We evaluated model discrimination, calibration and clinical benefit by Area Under the Receiver-Operator Characteristic (AUROC), calibration plots and decision curve analysis (DCA). Next, we compared the ARDPI model discrimination, calibration and clinical benefit with the IPI and NCCN-IPI models using the same methods. Lastly, we stratified patients into three survival risk cohorts based on ARDPI model by X-tile selecting cutoff point. RESULTS 7 co-variates were independently correlated with survival and were used to develop the ARDPI model including age, lymphocyte monocyte ratio (LMR), CD5 expression on lymphoma cells, blood EBV-DNA copy number, CD4/CD8 ratio, central nervous system (CNS) involvement and anti-HIV therapy (ART). AUROCs of ARDPI model for 1-, 3-, and 5-year were 0.80 (95% Confidence Interval [CI], 0.72, 0.88), 0.78 (0.69, 0.87) and 0.77 (0.63, 0.91). Predicted and calibrated values were concordant. The DCA curve had higher net benefit using the ARDPI model. Prediction accuracy of the ARDPI model was better compared with the IPI and NCCN-IPI models. For example, 3-year survival AUROC in the ARDPI model was 0.78 (0.69, 0.87) compared with the IPI (0.53 [0.43, 0.63] P&amp;lt; 0.001) and the NCCN-IPI (0.52 [0.42, 0.62] P&amp;lt; 0.001). Using the ARDPI model, we identified 3 survival risk cohorts with 3-year survivals of 0.80 , 0.38 and 0.09 ( P&amp;lt;0.001). CONCLUSION The ARDPI has good survival prediction accuracy in newly-diagnosed persons with AIDS-related DLBCL and using it has clinical benefit.Accuracy is better than the IPI and NCCN-IPI models. Validation of our conclusions is needed.