Avoiding philosophy as a trump-card in sociological writing. A study from the discourse of evidence-based healthcare

In this article I explore a situation where health sociologists encounter pure-philosophical reasoning in the fabric of social life. Accounts of the relationship between philosophy and sociology tend to be framed in abstract theory, so there is a need for practical ways to anchor philosophical reasoning in sociological writing. I consider the use of philosophies as strategic tools for socially grounded understanding, rather than rhetorical trump-cards which bypass socio-political questions. I present my understanding in two stages: first, I discuss my example topic of Evidence-Based Healthcare (EBHC), reviewing some philosophical contributions by writers in that discourse. These niche-writings I contextualise briefly in relation to other academic meetings between philosophy and sociology. Second, I offer three philosophical perspectives on the topic of EBHC, and outline their significance for understanding it sociologically. I conclude that to navigate the difficult ground where philosophy and sociology meet, sociologists can entrain pure-philosophical argumentation to the purpose of critical, socially situated understandings.PostprintPeer reviewe

Comparative Effectiveness Research: An Empirical Study of Trials Registered in ClinicalTrials.gov

Background The $1.1 billion investment in comparative effectiveness research will reshape the evidence-base supporting decisions about treatment effectiveness, safety, and cost. Defining the current prevalence and characteristics of comparative effectiveness (CE) research will enable future assessments of the impact of this program. Methods We conducted an observational study of clinical trials addressing priority research topics defined by the Institute of Medicine and conducted in the US between 2007 and 2010. Trials were identified in ClinicalTrials.gov. Main outcome measures were the prevalence of comparative effectiveness research, nature of comparators selected, funding sources, and impact of these factors on results. Results 231 (22.3%; 95% CI 19.8%–24.9%) studies were CE studies and 804 (77.7%; 95% CI, 75.1%–80.2%) were non-CE studies, with 379 (36.6%; 95% CI, 33.7%–39.6%) employing a placebo control and 425 (41.1%; 95% CI, 38.1%–44.1%) no control. The most common treatments examined in CE studies were drug interventions (37.2%), behavioral interventions (28.6%), and procedures (15.6%). Study findings were favorable for the experimental treatment in 34.8% of CE studies and greater than twice as many (78.6%) non-CE studies (P<0.001). CE studies were more likely to receive government funding (P = 0.003) and less likely to receive industry funding (P = 0.01), with 71.8% of CE studies primarily funded by a noncommercial source. The types of interventions studied differed based on funding source, with 95.4% of industry trials studying a drug or device. In addition, industry-funded CE studies were associated with the fewest pediatric subjects (P<0.001), the largest anticipated sample size (P<0.001), and the shortest study duration (P<0.001). Conclusions In this sample of studies examining high priority areas for CE research, less than a quarter are CE studies and the majority is supported by government and nonprofits. The low prevalence of CE research exists across CE studies with a broad array of interventions and characteristics.National Library of Medicine (U.S.) (5G08LM009778)National Institutes of Health (U.S.

Screening for prostate cancer: systematic review and meta-analysis of randomised controlled trials

Objective To examine the evidence on the benefits and harms of screening for prostate cancer

Financial considerations in the conduct of multi-centre randomised controlled trials: evidence from a qualitative study.

National Coordinating Centre for Research Methodology; Medical Research Council, UK Department of Health; Chief Scientist OfficeNot peer reviewedPublisher PD

The concordance between the volume hotspot and the grade hotspot: a 3-D reconstructive model using the pathology outputs from the PROMIS trial.

The rationale for directing targeted biopsy towards the centre of lesions has been questioned in light of prostate cancer grade heterogeneity. In this study, we assess the assumption that the maximum cancer Gleason grade (Gleason grade hotspot) lies within the maximum dimension (volume hotspot) of a prostate cancer lesion. 3-D histopathological models were reconstructed using the outputs of the 5-mm transperineal mapping (TPM) biopsies used as the reference test in the pilot phase of Prostate Mri Imaging Study (PROMIS), a paired validating cohort study investigating the performance of multi-parametric magnetic resonance imaging (MRI) against transrectal ultrasound (TRUS) biopsies. The prostate was fully sampled with 5 mm intervals; each core was separately labelled, inked and orientated in space to register 3-D cancer lesions location. The data from the histopathology results were used to create a 3-D interpolated reconstruction of each lesion and identify the spatial coordinates of the largest dimension (volume hot spot) and highest Gleason grade (Gleason grade hotspot) and assess their concordance. Ninety-four men, with median age 62 years (interquartile range, IQR= 58-68) and median PSA 6.5 ng ml(-1) (4.6-8.8), had a median of 80 (I69-89) cores each with a median of 4.5 positive cores (0-12). In the primary analysis, the prevalence of homogeneous lesions was 148 (76%; 95% confidence interval (CI) ±6.0%). In all, 184 (94±3.2%) lesions showed concordant hotspots and 11/47 (23±12.1%) of heterogeneous lesions showed discordant hotspots. The median 3-D distance between discordant hotspots was 12.8 mm (9.9-15.5). These figures remained stable on secondary analyses using alternative reconstructive assumptions. Limitations include a certain degree of error within reconstructed models. Guiding one biopsy needle to the maximum cancer diameter would lead to correct Gleason grade attribution in 94% of all lesions and 79% of heterogeneous ones if a true hit was obtained. Further correlation of histological lesions, their MRI appearance and the detectability of these hotspots on MRI will be undertaken once PROMIS results are released

Use of re-randomized data in meta-analysis

BACKGROUND: Outcomes collected in randomized clinical trials are observations of random variables that should be independent and identically distributed. However, in some trials, the patients are randomized more than once thus violating both of these assumptions. The probability of an event is not always the same when a patient is re-randomized; there is probably a non-zero covariance coming from observations on the same patient. This is of particular importance to the meta-analysts. METHODS: We developed a method to estimate the relative error in the risk differences with and without re-randomization of the patients. The relative error can be estimated by an expression depending on the percentage of the patients who were re-randomized, multipliers (how many times more likely it is to repeat an event) for the probability of reoccurrences, and the ratio of the total events reported and the initial number of patients entering the trial. RESULTS: We illustrate our methods using two randomized trials testing growth factors in febrile neutropenia. We showed that under some circumstances the relative error of taking into account re-randomized patients was sufficiently small to allow using the results in the meta-analysis. Our findings indicate that if the study in question is of similar size to other studies included in the meta-analysis, the error introduced by re-randomization will only minimally affect meta-analytic summary point estimate. We also show that in our model the risk ratio remains constant during the re-randomization, and therefore, if a meta-analyst is concerned about the effect of re-randomization on the meta-analysis, one way to sidestep the issue and still obtain reliable results is to use risk ratio as the measure of interest. CONCLUSION: Our method should be helpful in the understanding of the results of clinical trials and particularly helpful to the meta-analysts to assess if re-randomized patient data can be used in their analyses

Quality and methods of developing practice guidelines

BACKGROUND: It is not known whether there are differences in the quality and recommendations between evidence-based (EB) and consensus-based (CB) guidelines. We used breast cancer guidelines as a case study to assess for these differences. METHODS: Five different instruments to evaluate the quality of guidelines were identified by a literature search. We also searched MEDLINE and the Internet to locate 8 breast cancer guidelines. These guidelines were classified in three categories: evidence based, consensus based and consensus based with no explicit consideration of evidence (CB-EB). Each guideline was evaluated by three of the authors using each of the instruments. For each guideline we assessed the agreement among 14 decision points which were selected from the NCCN (National Cancer Comprehensive Network) guidelines algorithm. For each decision point we recorded the level of the quality of the information used to support it. A regression analysis was performed to assess if the percentage of high quality evidence used in the guidelines development was related to the overall quality of the guidelines. RESULTS: Three guidelines were classified as EB, three as CB-EB and two as CB. The EB guidelines scored better than CB, with the CB-EB scoring in the middle among all instruments for guidelines quality assessment. No major disagreement in recommendations was detected among the guidelines regardless of the method used for development, but the EB guidelines had a better agreement with the benchmark guideline for any decision point. When the source of evidence used to support decision were of high quality, we found a higher level of full agreement among the guidelines' recommendations. Up to 94% of variation in the quality score among guidelines could be explained by the quality of evidence used for guidelines development. CONCLUSION: EB guidelines have a better quality than CB guidelines and CB-EB guidelines. Explicit use of high quality evidence can lead to a better agreement among recommendations. However, no major disagreement among guidelines was noted regardless of the method for their development