Centre selection for clinical trials and the generalisability of results: a mixed methods study.

BACKGROUND: The rationale for centre selection in randomised controlled trials (RCTs) is often unclear but may have important implications for the generalisability of trial results. The aims of this study were to evaluate the factors which currently influence centre selection in RCTs and consider how generalisability considerations inform current and optimal practice. METHODS AND FINDINGS: Mixed methods approach consisting of a systematic review and meta-summary of centre selection criteria reported in RCT protocols funded by the UK National Institute of Health Research (NIHR) initiated between January 2005-January 2012; and an online survey on the topic of current and optimal centre selection, distributed to professionals in the 48 UK Clinical Trials Units and 10 NIHR Research Design Services. The survey design was informed by the systematic review and by two focus groups conducted with trialists at the Birmingham Centre for Clinical Trials. 129 trial protocols were included in the systematic review, with a total target sample size in excess of 317,000 participants. The meta-summary identified 53 unique centre selection criteria. 78 protocols (60%) provided at least one criterion for centre selection, but only 31 (24%) protocols explicitly acknowledged generalisability. This is consistent with the survey findings (n = 70), where less than a third of participants reported generalisability as a key driver of centre selection in current practice. This contrasts with trialists' views on optimal practice, where generalisability in terms of clinical practice, population characteristics and economic results were prime considerations for 60% (n = 42), 57% (n = 40) and 46% (n = 32) of respondents, respectively. CONCLUSIONS: Centres are rarely enrolled in RCTs with an explicit view to external validity, although trialists acknowledge that incorporating generalisability in centre selection should ideally be more prominent. There is a need to operationalize 'generalisability' and incorporate it at the design stage of RCTs so that results are readily transferable to 'real world' practice

Ophthalmic features of HIV associated cryptococcal meningitis in Malawian Adults: an observational study [version 1; peer review: awaiting peer review]

BACKGROUND: Cryptococcal meningitis (CM) is the commonest neurological complication in patients with advanced HIV. Visual disturbance is a frequent presenting symptom. Papilloedema is commonly reported but other ophthalmic findings are not well described. METHODS: We performed an observational study comparing severely immunocompromised HIV-infected patients with and without CM to determine the nature and prevalence of retinal pathology attributable to CM. 70 adult patients were enrolled in Blantyre Malawi, 35 with CM and 35 HIV-infected patients without CM. RESULTS: 79% (19/24) of CM patients examined on day one had evidence of retinal abnormalities compared to 17% (6/35) of HIV-infected controls (p <0.001). In the CM group, retinal whitening was the commonest abnormality (50%), followed by optic disc swelling (29%), haemorrhage (25%) and vascular abnormalities (7%). Retinal whitening was the only abnormality observed in the comparator group (17%). In CM, there was no significant difference between those with and without retinal abnormalities in fungal burden (13,550 cfu/ml vs. 9,150 cfu/ml; p = 0.65), CD4 count (28 cells/µl vs. 76 cells/µl; p = 0.79) or CSF opening pressure (21cm H20 vs. 27cm H20; p = 0.5). There was no association between presence/absence of retinal abnormalities and death (40% 10-week mortality vs. 26%; p = 0.6). CONCLUSIONS: Whether the presence of CM retinopathy could be used as a marker of disease severity warrants further investigation. The observed ophthalmic findings provide a descriptive framework for CM retinopathy to be utilised in future CM studies. TRIAL REGISTRATION: ISRCTN (ISRCTN45035509) 19/06/2012

Genomic Variation across a Clinical Cryptococcus Population Linked to Disease Outcome.

Cryptococcus neoformans is the causative agent of cryptococcosis, a disease with poor patient outcomes that accounts for approximately 180,000 deaths each year. Patient outcomes may be impacted by the underlying genetics of the infecting isolate; however, our current understanding of how genetic diversity contributes to clinical outcomes is limited. Here, we leverage clinical, in vitro growth and genomic data for 284 C. neoformans isolates to identify clinically relevant pathogen variants within a population of clinical isolates from patients with human immunodeficiency virus (HIV)-associated cryptococcosis in Malawi. Through a genome-wide association study (GWAS) approach, we identify variants associated with the fungal burden and the growth rate. We also find both small and large-scale variation, including aneuploidy, associated with alternate growth phenotypes, which may impact the course of infection. Genes impacted by these variants are involved in transcriptional regulation, signal transduction, glycosylation, sugar transport, and glycolysis. We show that growth within the central nervous system (CNS) is reliant upon glycolysis in an animal model and likely impacts patient mortality, as the CNS yeast burden likely modulates patient outcome. Additionally, we find that genes with roles in sugar transport are enriched in regions under selection in specific lineages of this clinical population. Further, we demonstrate that genomic variants in two genes identified by GWAS impact virulence in animal models. Our approach identifies links between the genetic variation in C. neoformans and clinically relevant phenotypes and animal model pathogenesis, thereby shedding light on specific survival mechanisms within the CNS and identifying the pathways involved in yeast persistence. IMPORTANCE Infection outcomes for cryptococcosis, most commonly caused by C. neoformans, are influenced by host immune responses as well as by host and pathogen genetics. Infecting yeast isolates are genetically diverse; however, we lack a deep understanding of how this diversity impacts patient outcomes. To better understand both clinical isolate diversity and how diversity contributes to infection outcomes, we utilize a large collection of clinical C. neoformans samples that were isolated from patients enrolled in a clinical trial across 3 hospitals in Malawi. By combining whole-genome sequence data, clinical data, and in vitro growth data, we utilize genome-wide association approaches to examine the genetic basis of virulence. Genes with significant associations display virulence attributes in both murine and rabbit models, demonstrating that our approach can identify potential links between genetic variants and patho-biologically significant phenotypes