SciCombinator

Objective To determine the availability of data on overall survival and quality of life benefits of cancer drugs approved in Europe.Design Retrospective cohort study.Setting Publicly accessible regulatory and scientific reports on cancer approvals by the European Medicines Agency (EMA) from 2009 to 2013.Main outcome measures Pivotal and postmarketing trials of cancer drugs according to their design features (randomisation, crossover, blinding), comparators, and endpoints. Availability and magnitude of benefit on overall survival or quality of life determined at time of approval and after market entry. Validated European Society for Medical Oncology Magnitude of Clinical Benefit Scale (ESMO-MCBS) used to assess the clinical value of the reported gains in published studies of cancer drugs.Results From 2009 to 2013, the EMA approved the use of 48 cancer drugs for 68 indications. Of these, eight indications (12%) were approved on the basis of a single arm study. At the time of market approval, there was significant prolongation of survival in 24 of the 68 (35%). The magnitude of the benefit on overall survival ranged from 1.0 to 5.8 months (median 2.7 months). At the time of market approval, there was an improvement in quality of life in seven of 68 indications (10%). Out of 44 indications for which there was no evidence of a survival gain at the time of market authorisation, in the subsequent postmarketing period there was evidence for extension of life in three (7%) and reported benefit on quality of life in five (11%). Of the 68 cancer indications with EMA approval, and with a median of 5.4 years' follow-up (minimum 3.3 years, maximum 8.1 years), only 35 (51%) had shown a significant improvement in survival or quality of life, while 33 (49%) remained uncertain. Of 23 indications associated with a survival benefit that could be scored with the ESMO-MCBS tool, the benefit was judged to be clinically meaningful in less than half (11/23, 48%).Conclusions This systematic evaluation of oncology approvals by the EMA in 2009-13 shows that most drugs entered the market without evidence of benefit on survival or quality of life. At a minimum of 3.3 years after market entry, there was still no conclusive evidence that these drugs either extended or improved life for most cancer indications. When there were survival gains over existing treatment options or placebo, they were often marginal.

In England between 2010 and 2013, just over one million recipients of the main out-of-work disability benefit had their eligibility reassessed using a new functional checklist-the Work Capability Assessment. Doctors and disability rights organisations have raised concerns that this has had an adverse effect on the mental health of claimants, but there are no population level studies exploring the health effects of this or similar policies.

The ability to measure physical activity through wrist-worn devices provides an opportunity for cardiovascular medicine. However, the accuracy of commercial devices is largely unknown. The aim of this work is to assess the accuracy of seven commercially available wrist-worn devices in estimating heart rate (HR) and energy expenditure (EE) and to propose a wearable sensor evaluation framework. We evaluated the Apple Watch, Basis Peak, Fitbit Surge, Microsoft Band, Mio Alpha 2, PulseOn, and Samsung Gear S2. Participants wore devices while being simultaneously assessed with continuous telemetry and indirect calorimetry while sitting, walking, running, and cycling. Sixty volunteers (29 male, 31 female, age 38 ± 11 years) of diverse age, height, weight, skin tone, and fitness level were selected. Error in HR and EE was computed for each subject/device/activity combination. Devices reported the lowest error for cycling and the highest for walking. Device error was higher for males, greater body mass index, darker skin tone, and walking. Six of the devices achieved a median error for HR below 5% during cycling. No device achieved an error in EE below 20 percent. The Apple Watch achieved the lowest overall error in both HR and EE, while the Samsung Gear S2 reported the highest. In conclusion, most wrist-worn devices adequately measure HR in laboratory-based activities, but poorly estimate EE, suggesting caution in the use of EE measurements as part of health improvement programs. We propose reference standards for the validation of consumer health devices (http://precision.stanford.edu/).

Do patients' reports of their health care experiences reflect the quality of care? Despite the increasing role of such measures in research and policy, there’s no consensus regarding their legitimacy in quality assessment. Indeed, as physician and hospital compensation becomes increasingly tied to patient feedback, health care providers and academics are raising strong objections to the use of patient-experience surveys. These views are fueled by studies indicating that patient-experience measures at best have no relation to the quality of delivered care and at worst are associated with poorer patient outcomes. Conversely, other studies have found that better patient experiences - . . .

Novel interventions are needed to improve lifestyle and prevent noncommunicable diseases, the leading cause of death and disability globally. This study aimed to systematically review, synthesize, and grade scientific evidence on effectiveness of novel information and communication technology to reduce noncommunicable disease risk.

Timely assessment of the burden of HIV/AIDS is essential for policy setting and programme evaluation. In this report from the Global Burden of Disease Study 2015 (GBD 2015), we provide national estimates of levels and trends of HIV/AIDS incidence, prevalence, coverage of antiretroviral therapy (ART), and mortality for 195 countries and territories from 1980 to 2015.

The increasing prevalence of social media means that we often encounter written language characterized by both stylistic variation and outright errors. How does the personality of the reader modulate reactions to non-standard text? Experimental participants read ‘email responses’ to an ad for a housemate that either contained no errors or had been altered to include either typos (e.g., teh) or homophonous grammar errors (grammos, e.g., to/too, it’s/its). Participants completed a 10-item evaluation scale for each message, which measured their impressions of the writer. In addition participants completed a Big Five personality assessment and answered demographic and language attitude questions. Both typos and grammos had a negative impact on the evaluation scale. This negative impact was not modulated by age, education, electronic communication frequency, or pleasure reading time. In contrast, personality traits did modulate assessments, and did so in distinct ways for grammos and typos.

 To assess diagnostic accuracy of screening tests for pre-diabetes and efficacy of interventions (lifestyle or metformin) in preventing onset of type 2 diabetes in people with pre-diabetes.

Excessive alcohol consumption is a leading cause of death and morbidity worldwide and interventions to help people reduce their consumption are needed. Interventions delivered by smartphone apps have the potential to help harmful and hazardous drinkers reduce their consumption of alcohol. However, there has been little evaluation of the effectiveness of existing smartphone interventions. A systematic review, amongst other methodologies, identified promising modular content that could be delivered by an app: self-monitoring and feedback; action planning; normative feedback; cognitive bias re-training; and identity change. This protocol reports a factorial randomised controlled trial to assess the comparative potential of these five intervention modules to reduce excessive alcohol consumption.

Algorithms for predicting recidivism are commonly used to assess a criminal defendant’s likelihood of committing a crime. These predictions are used in pretrial, parole, and sentencing decisions. Proponents of these systems argue that big data and advanced machine learning make these analyses more accurate and less biased than humans. We show, however, that the widely used commercial risk assessment software COMPAS is no more accurate or fair than predictions made by people with little or no criminal justice expertise. We further show that a simple linear predictor provided with only two features is nearly equivalent to COMPAS with its 137 features.