A randomized phase II trial of bevacizumab vs. bevacizumab and erlotinib as first-line consolidation after carboplatin, paclitaxel, and bevacizumab in newly diagnosed patients with mullerian tumors.

BACKGROUND: The combination of paclitaxel to platinum remains the backbone of therapy in patients with advanced Mullerian tumors. In patients with newly diagnosed Mullerian tumors, we investigated the progression-free survival benefit of bevacizumab and bevacizumab and erlotinib as consolidation therapy post-induction therapy. METHODS: Sixty patients were enrolled in a phase II trial of carboplatin, paclitaxel, and bevacizumab (induction therapy). After the completion induction therapy, patients were stratified by response (≥ SD) and then randomized (1:1) to either bevacizumab (A) or bevacizumab and erlotinib (AE.) The primary endpoint was PFS. Secondary endpoints included the response rate of induction and consolidation therapy and toxicity profile of each consolidative arm. Each consolidative arm was compared to the historical control GOG 111. RESULTS: Forty-eight patients advanced to the consolidative phase of the trial. Twelve patients were removed in the induction phase, the majority for toxicity. The most common toxicity (grade ≥ 3) was diarrhea (20%: arm AE; 0%: arm A). One patient in the AE arm had a fatal cardiac arrest deemed unrelated to the study treatment. No gastrointestinal perforations were reported. The median PFS in the AE and A arm was 18.9 months (p < 0.0001) and 13.3 months (p: ns), respectively. The overall rate of grade 3/4 toxicities in the AE arm was 72% and in the A arm 30%. Six patients remain free of disease 10 years after enrollment. CONCLUSION: Combinatorial consolidation therapy with AE was associated with an improved progression-free survival in patients with Mullerian tumors.

Generalizability of Cardiovascular Disease Clinical Prediction Models: 158 Independent External Validations of 104 Unique Models.

BACKGROUND: While clinical prediction models (CPMs) are used increasingly commonly to guide patient care, the performance and clinical utility of these CPMs in new patient cohorts is poorly understood. METHODS: We performed 158 external validations of 104 unique CPMs across 3 domains of cardiovascular disease (primary prevention, acute coronary syndrome, and heart failure). Validations were performed in publicly available clinical trial cohorts and model performance was assessed using measures of discrimination, calibration, and net benefit. To explore potential reasons for poor model performance, CPM-clinical trial cohort pairs were stratified based on relatedness, a domain-specific set of characteristics to qualitatively grade the similarity of derivation and validation patient populations. We also examined the model-based C-statistic to assess whether changes in discrimination were because of differences in case-mix between the derivation and validation samples. The impact of model updating on model performance was also assessed. RESULTS: Discrimination decreased significantly between model derivation (0.76 [interquartile range 0.73-0.78]) and validation (0.64 [interquartile range 0.60-0.67], P<0.001), but approximately half of this decrease was because of narrower case-mix in the validation samples. CPMs had better discrimination when tested in related compared with distantly related trial cohorts. Calibration slope was also significantly higher in related trial cohorts (0.77 [interquartile range, 0.59-0.90]) than distantly related cohorts (0.59 [interquartile range 0.43-0.73], P=0.001). When considering the full range of possible decision thresholds between half and twice the outcome incidence, 91% of models had a risk of harm (net benefit below default strategy) at some threshold; this risk could be reduced substantially via updating model intercept, calibration slope, or complete re-estimation. CONCLUSIONS: There are significant decreases in model performance when applying cardiovascular disease CPMs to new patient populations, resulting in substantial risk of harm. Model updating can mitigate these risks. Care should be taken when using CPMs to guide clinical decision-making.

Clinical Predictive Models of Sudden Cardiac Arrest: A Survey of the Current Science and Analysis of Model Performances.

Background More than 500 000 sudden cardiac arrests (SCAs) occur annually in the United States. Clinical predictive models (CPMs) may be helpful tools to differentiate between patients who are likely to survive or have good neurologic recovery and those who are not. However, which CPMs are most reliable for discriminating between outcomes in SCA is not known. Methods and Results We performed a systematic review of the literature using the Tufts PACE (Predictive Analytics and Comparative Effectiveness) CPM Registry through February 1, 2020, and identified 81 unique CPMs of SCA and 62 subsequent external validation studies. Initial cardiac rhythm, age, and duration of cardiopulmonary resuscitation were the 3 most commonly used predictive variables. Only 33 of the 81 novel SCA CPMs (41%) were validated at least once. Of 81 novel SCA CPMs, 56 (69%) and 61 of 62 validation studies (98%) reported discrimination, with median c-statistics of 0.84 and 0.81, respectively. Calibration was reported in only 29 of 62 validation studies (41.9%). For those novel models that both reported discrimination and were validated (26 models), the median percentage change in discrimination was -1.6%. We identified 3 CPMs that had undergone at least 3 external validation studies: the out-of-hospital cardiac arrest score (9 validations; median c-statistic, 0.79), the cardiac arrest hospital prognosis score (6 validations; median c-statistic, 0.83), and the good outcome following attempted resuscitation score (6 validations; median c-statistic, 0.76). Conclusions Although only a small number of SCA CPMs have been rigorously validated, the ones that have been demonstrate good discrimination.

Why clinical trials may not help patients make treatment decisions: results from focus group discussions with 22 patients.

Aim: Despite broad interest in advancing personalized medicine, most evidence is currently derived from average results of clinical trials that may obscure heterogeneity of trial participants. Little is known currently about how patients view heterogeneity in trials and whether they can participate in methodological discussions about this concept. Materials & methods: In structured discussions with three focus groups involving 22 participants, we assessed how representatives of patient communities have used research to guide individual treatment decisions. Discussion themes were organized into a framework describing patient decision-making in four steps: decisions patients make in the course of care; information used to make decisions; sources for information; and quality of information. Results/conclusion: Patients prioritize information that reflects their own characteristics, preferences and values. They struggle applying clinical research to their own case.

Clinical Prediction Models for Valvular Heart Disease.

Background While many clinical prediction models (CPMs) exist to guide valvular heart disease treatment decisions, the relative performance of these CPMs is largely unknown. We systematically describe the CPMs available for patients with valvular heart disease with specific attention to performance in external validations. Methods and Results A systematic review identified 49 CPMs for patients with valvular heart disease treated with surgery (n=34), percutaneous interventions (n=12), or no intervention (n=3). There were 204 external validations of these CPMs. Only 35 (71%) CPMs have been externally validated. Sixty-five percent (n=133) of the external validations were performed on distantly related populations. There was substantial heterogeneity in model performance and a median percentage change in discrimination of -27.1% (interquartile range, -49.4%--5.7%). Nearly two-thirds of validations (n=129) demonstrate at least a 10% relative decline in discrimination. Discriminatory performance of EuroSCORE II and Society of Thoracic Surgeons (2009) models (accounting for 73% of external validations) varied widely: EuroSCORE II validation c-statistic range 0.50 to 0.95; Society of Thoracic Surgeons (2009) Models validation c-statistic range 0.50 to 0.86. These models performed well when tested on related populations (median related validation c-statistics: EuroSCORE II, 0.82 [0.76, 0.85]; Society of Thoracic Surgeons [2009], 0.72 [0.67, 0.79]). There remain few (n=9) external validations of transcatheter aortic valve replacement CPMs. Conclusions Many CPMs for patients with valvular heart disease have never been externally validated and isolated external validations appear insufficient to assess the trustworthiness of predictions. For surgical valve interventions, there are existing predictive models that perform reasonably well on related populations. For transcatheter aortic valve replacement (CPMs additional external validations are needed to broadly understand the trustworthiness of predictions.

Patients' responses to incidentally discovered silent brain infarcts - a qualitative study.

BACKGROUND: Incidentally discovered silent brain infarcts (id-SBIs) are an understudied condition with probable clinical significance, but it is not known how patients respond to or prioritize this condition. We sought to assess reporting of id-SBIs and how patients approach their diagnosis. METHODS: Patients with id-SBIs were identified from sequential scans between 12/2015-5/2016, were referred by treating clinicians, or self-referred for the study. This study used qualitative semi-structured interviews. Purposeful sampling was used to achieve diversity in acuity, setting, and recruitment strategy. Interviews were audio-recorded and transcribed. A constant comparative method was used to develop a coding schema, find consensus, and iteratively explore emergent themes until thematic saturation was achieved. RESULTS: Only 10 of 102 patients prospectively identified by neuroimaging were informed of the imaging findings. Twelve participants in total were interviewed. Among the study participants, the primary themes were cognitive, emotional, and behavioral responses to diagnostic, prognostic, and therapeutic uncertainty regarding id-SBIs. Clinicians described id-SBIs to participants as an ambiguous condition. Participants feared potential consequences of id-SBIs, including symptomatic stroke, dementia, and disability. Participants attempted to reduce uncertainty with strategies including equating id-SBIs with symptomatic stroke, self-education about stroke, and seeking second opinions. CONCLUSION: Participants considered id-SBIs to be a serious medical condition. Ambiguous counseling by clinicians on id-SBIs provoked or failed to attenuate fear, leading to participants adopting strategies aimed at reducing uncertainty.

Quality of hemodialysis services in a poor population, Sistan and Baluchestan province, Iran: A descriptive, prospective study.

Managing patients with chronic kidney disease causes enormous financial burden on the Ministry of Health and Medical Education. In addition, there is a lack of feedback and adequate information in general. This study aimed at investigating quality-of-care indicators among hemodialysis (HD) patients. This descriptive, prospective study was conducted on 144 HD patients in Zabol and Iranshahr dialysis centers from March 21 to December 22, 2015. Measurement indicators included hemoglobin level, dialysis adequacy, albumin level, vascular access, and calcium and phosphorus levels. The mean hemoglobin and dialysis adequacy level at baseline were 10.58 ± 1.6 g/dL and 1.09 ± 0.18, respectively. At the end of the study, 49.6% of participants achieved target hemoglobin level. However, only 18.6% of patients achieved target dialysis adequacy at the end of the study. Dialysis adequacy was calculated by using an standard software for calculating the KT/V that provided by Iran ministry of health for all dialysis centers. The prevalence rate of use of central venous catheter was 43.2% at the end of the study. The majority of patients (59%) had albumin within normal limits and also achieved target in terms of calcium (52%) and phosphorus (59%) levels at the end of the study. Despite partial improvement in several indicators, none achieved target values which indicate the need for greater attention to quality-of-care indicators for correct planning, cost reduction, and efficiency improvement.

Correction: Clinicians' perspectives on incidentally discovered silent brain infarcts - A qualitative study.

[This corrects the article DOI: 10.1371/journal.pone.0194971.].

Clinicians' perspectives on incidentally discovered silent brain infarcts - A qualitative study.

BACKGROUND: While silent brain infarcts (SBIs) in screened cohorts are associated with risk of symptomatic stroke and dementia, the clinical significance of incidentally discovered SBIs (id-SBIs) is unknown. Detection may offer an opportunity to initiate prevention measures, but uncertainties about id-SBIs may impede clinicians from addressing them and complicate further study of this condition. METHODS AND RESULTS: This study used semi-structured interviews of practicing clinicians. Interviews were audio recorded, transcribed, and analyzed using a grounded theory approach. A constant comparative method was used to organize emergent themes and examine new themes. Purposeful sampling was employed to achieve participant diversity. Fifteen clinicians were interviewed. Emergent themes centered on uncertainty about id-SBIs, clinical decision making in response to uncertainty, and evidence needed to resolve uncertainty. All clinicians reported uncertainty about id-SBIs: diagnostic, prognostic, or therapeutic. Differential responses to uncertainties resulted in practice variation within and between specialties. Diagnostic and prognostic uncertainty discouraged disclosure of imaging findings to patients. Vascular neurologists viewed the prognostic significance of id-SBIs as similar to symptomatic stroke. Therapeutic uncertainty was common, but most participants endorsed using stroke secondary prevention strategies. Regarding future research, all internists indicated they would consider changing practices in response to observational studies, whereas half of the neurologists expressed reluctance to modify practices based on non-randomized data. Several expressed concerns about clinical trial feasibility and lack of equipoise. CONCLUSIONS: id-SBIs are a focus of uncertainty for clinicians, leading to practice variation. Future studies must address diagnostic and prognostic uncertainty to facilitate implementation of prevention strategies.

Patient Variability Seldom Assessed in Cost-effectiveness Studies.

BACKGROUND: Cost-effectiveness analysis (CEA) estimates can vary substantially across patient subgroups when patient characteristics influence preferences, outcome risks, treatment effectiveness, life expectancy, or associated costs. However, no systematic review has reported the frequency of subgroup analysis in CEA, what type of heterogeneity they address, and how often heterogeneity influences whether cost-effectiveness ratios exceed or fall below conventional thresholds. METHODS: We reviewed the CEA literature cataloged in the Tufts Medical Center CEA Registry, a repository describing cost-utility analyses published through 2016. After randomly selecting 200 of 642 articles published in 2014, we ascertained whether each study reported subgroup results and collected data on the defining characteristics of these subgroups. We identified whether any of the CEA subgroup results crossed conventional cost-effectiveness benchmarks (e.g., $100,000 per QALY) and compared characteristics of studies with and without subgroup-specific findings. RESULTS: Thirty-eight studies (19%) reported patient subgroup results. Articles reporting subgroup analyses were more likely to be US-based, government funded (v. drug industry- or nonprofit foundation-funded) studies, with a focus on primary or secondary (v. tertiary) prevention (P < 0.05 for comparisons). One or more patient characteristics were used to stratify CEA results 68 times within the 38 studies, with most stratifications using one characteristic (n = 47), most commonly age (n = 35). Among the 23 stratifications reported alongside average ratios in US studies, 13 produced subgroup ratios that crossed a conventional CEA ratio benchmark. CONCLUSIONS: Most CEAs do not report any subgroup results, and those that do most often stratify only by patient age. Over half of the subgroup analyses reported could lead to different value-based decision making for at least some patients.

Tufts PACE Clinical Predictive Model Registry: update 1990 through 2015.

BACKGROUND: Clinical predictive models (CPMs) estimate the probability of clinical outcomes and hold the potential to improve decision-making and individualize care. The Tufts Predictive Analytics and Comparative Effectiveness (PACE) CPM Registry is a comprehensive database of cardiovascular disease (CVD) CPMs. The Registry was last updated in 2012, and there continues to be substantial growth in the number of available CPMs. METHODS: We updated a systematic review of CPMs for CVD to include articles published from January 1990 to March 2015. CVD includes coronary artery disease (CAD), congestive heart failure (CHF), arrhythmias, stroke, venous thromboembolism (VTE), and peripheral vascular disease (PVD). The updated Registry characterizes CPMs based on population under study, model performance, covariates, and predicted outcomes. RESULTS: The Registry includes 747 articles presenting 1083 models, including both prognostic (n = 1060) and diagnostic (n = 23) CPMs representing 183 distinct index condition/outcome pairs. There was a threefold increase in the number of CPMs published between 2005 and 2014, compared to the prior 10-year interval from 1995 to 2004. The majority of CPMs were derived from either North American (n = 455, 42%) or European (n = 344, 32%) populations. The database contains 265 CPMs predicting outcomes for patients with coronary artery disease, 196 CPMs for population samples at risk for incident CVD, and 158 models for patients with stroke. Approximately two thirds (n = 701, 65%) of CPMs report a c-statistic, with a median reported c-statistic of 0.77 (IQR, 0.05). Of the CPMs reporting validations, only 333 (57%) report some measure of model calibration. Reporting of discrimination but not calibration is improving over time (p for trend < 0.0001 and 0.39 respectively). CONCLUSIONS: There is substantial redundancy of CPMs for a wide spectrum of CVD conditions. While the number of CPMs continues to increase, model performance is often inadequately reported and calibration is infrequently assessed. More work is needed to understand the potential impact of this literature.

Field Synopsis of the Role of Sex in Stroke Prediction Models.

BACKGROUND: Guidelines for stroke prevention recommend development of sex-specific stroke risk scores. Incorporating sex in Clinical Prediction Models (CPMs) may support sex-specific clinical decision making. To better understand their potential to guide sex-specific care, we conducted a field synopsis of the role of sex in stroke-related CPMs. METHODS AND RESULTS: We identified stroke-related CPMs in the Tufts Predictive Analytics and Comparative Effectiveness CPM Database, a systematic summary of cardiovascular CPMs published from January 1990 to May 2012. We report the proportion of models including the effect of sex on stroke incidence or prognosis, summarize the directionality of the predictive effects of sex, and explore factors influencing the inclusion of sex. Of 92 stroke-related CPMs, 30 (33%) contained a coefficient for sex or presented sex-stratified models. Only 12/58 (21%) CPMs predicting outcomes in patients included sex, compared to 18/30 (60%) models predicting first stroke (P<0.0001). Sex was most commonly included in models predicting stroke among a general population (69%). Female sex was consistently associated with reduced mortality after ischemic stroke (n=4) and higher risk of stroke from arrhythmias or coronary revascularization (n=5). Models predicting first stroke versus outcomes among patients with stroke (odds ratio=5.75, 95% CI 2.18-15.14, P<0.001) and those developed from larger versus smaller sample sizes (odds ratio=4.58, 95% CI 1.73-12.13, P=0.002) were significantly more likely to include sex. CONCLUSIONS: Sex is included in a minority of published CPMs, but more frequently in models predicting incidence of first stroke. The importance of sex-specific care may be especially well established for primary prevention.

Field Synopsis of Sex in Clinical Prediction Models for Cardiovascular Disease.

BACKGROUND: Several widely used risk scores for cardiovascular disease (CVD) incorporate sex effects, yet there has been no systematic summary of the role of sex in clinical prediction models (CPMs). To better understand the potential of these models to support sex-specific care, we conducted a field synopsis of sex effects in CPMs for CVD. METHODS AND RESULTS: We identified CPMs in the Tufts Predictive Analytics and Comparative Effectiveness CPM Registry, a comprehensive database of CVD CPMs published from January 1990 to May 2012. We report the proportion of models including sex effects on CVD incidence or prognosis, summarize the directionality of the predictive effects of sex, and explore factors influencing the inclusion of sex. Of 592 CVD-related CPMs, 193 (33%) included sex as a predictor or presented sex-stratified models. Sex effects were included in 78% (53/68) of models predicting incidence of CVD in a general population, versus only 35% (59/171), 21% (12/58), and 17% (12/72) of models predicting outcomes in patients with coronary artery disease, stroke, and heart failure, respectively. Among sex-including CPMs, women with heart failure were at lower mortality risk in 8 of 8 models; women undergoing revascularization for coronary artery disease were at higher mortality risk in 10 of 12 models. Factors associated with the inclusion of sex effects included the number of outcome events and using cohorts at-risk for CVD (rather than with established CVD). CONCLUSIONS: Although CPMs hold promise for supporting sex-specific decision making in CVD clinical care, sex effects are included in only one third of published CPMs.