Interrogating intervention delivery and participants’ emotional states to improve engagement and implementation: A realist informed multiple case study evaluation of Engager

BACKGROUND: 'Engager' is an innovative 'through-the-gate' complex care intervention for male prison-leavers with common mental health problems. In parallel to the randomised-controlled trial of Engager (Trial registration number: ISRCTN11707331), a set of process evaluation analyses were undertaken. This paper reports on the depth multiple case study analysis part of the process evaluation, exploring how a sub-sample of prison-leavers engaged and responded to the intervention offer of one-to-one support during their re-integration into the community. METHODS: To understand intervention delivery and what response it elicited in individuals, we used a realist-informed qualitative multiple 'case' studies approach. We scrutinised how intervention component delivery lead to outcomes by examining underlying causal pathways or 'mechanisms' that promoted or hindered progress towards personal outcomes. 'Cases' (n = 24) were prison-leavers from the intervention arm of the trial. We collected practitioner activity logs and conducted semi-structured interviews with prison-leavers and Engager/other service practitioners. We mapped data for each case against the intervention logic model and then used Bhaskar's (2016) 'DREIC' analytic process to categorise cases according to extent of intervention delivery, outcomes evidenced, and contributing factors behind engagement or disengagement and progress achieved. RESULTS: There were variations in the dose and session focus of the intervention delivery, and how different participants responded. Participants sustaining long-term engagement and sustained change reached a state of 'crises but coping'. We found evidence that several components of the intervention were key to achieving this: trusting relationships, therapeutic work delivered well and over time; and an in-depth shared understanding of needs, concerns, and goals between the practitioner and participants. Those who disengaged were in one of the following states: 'Crises and chaos', 'Resigned acceptance', 'Honeymoon' or 'Wilful withdrawal'. CONCLUSIONS: We demonstrate that the 'implementability' of an intervention can be explained by examining the delivery of core intervention components in relation to the responses elicited in the participants. Core delivery mechanisms often had to be 'triggered' numerous times to produce sustained change. The improvements achieved, sustained, and valued by participants were not always reflected in the quantitative measures recorded in the RCT. The compatibility between the practitioner, participant and setting were continually at risk of being undermined by implementation failure as well as changing external circumstances and participants' own weaknesses. TRIAL REGISTRATION NUMBER: ISRCTN11707331, Wales Research Ethics Committee, Registered 02-04-2016-Retrospectively registered https://doi.org/10.1186/ISRCTN11707331

Development and evaluation of a collaborative care intervention for male prison leavers with mental health problems: the Engager research programme

BackgroundMany male prison leavers have significant mental health problems. Prison leavers often have a history of trauma, ongoing substance misuse and housing insecurity. Only a minority of prison leavers receive mental health care on release from prison.ObjectivesThe aim of the Engager research programme was to develop and evaluate a theory- and evidence-informed complex intervention designed to support individuals with common mental health problems (e.g. anxiety, depression) and other complex needs, including mental health comorbidity, before and after release from prison.MethodsIn phase 1, the intervention was developed through a set of realist-informed substudies, including a realist review of psychosocial care for individuals with complex needs, case studies within services demonstrating promising intervention features, focus groups with individuals from under-represented groups, a rapid realist review of the intervention implementation literature and a formative process evaluation of the prototype intervention. In a parallel randomised trial, methodological development included selecting outcome measures through reviewing literature, piloting measures and a consensus process, developing ways to quantify intervention receipt, piloting trial procedures and modelling economic outcomes. In phase 2, we conducted an individually randomised superiority trial of the Engager intervention, cost-effectiveness and cost–consequence analyses and an in-depth mixed-methods process evaluation. Patient and public involvement influenced the programme throughout, primarily through a Peer Researcher Group.ResultsIn phase 1, the Engager intervention included multiple components. A practitioner offered participants practical support, emotional help (including mentalisation-based approaches) and liaison with other services in prison on the day of the participant’s release and for 3–5 months post release. An intervention delivery platform (i.e. training, manual, supervision) supported implementation. Outcome measures were selected through testing and stakeholder consensus to represent a broad range of domains, with a general mental health outcome as the primary measure for the trial. Procedures for recruitment and follow-up were tested and included flexible approaches to engagement and retention. In phase 2, the trial was conducted in three prison settings, with 280 participants randomised in a 1 : 1 ratio to receive either Engager plus usual care (n = 140) or usual care only (n = 140). We achieved a follow-up rate of 65% at 6 months post release from prison. We found no difference between the two groups for the Clinical Outcomes in Routine Evaluation – Outcome Measure at 6 months. No differences in secondary measures and sensitivity analyses were found beyond those expected by chance. The cost-effectiveness analysis showed that Engager cost significantly more at £2133 (95% of iterations between £997 and £3374) with no difference in quality-adjusted life-years (–0.017, 95% of iterations between –0.042 and 0.007). The mixed-methods process evaluation demonstrated implementation barriers. These barriers included problems with retention of the intervention team, and the adverse health and criminal justice system context. Seventy-seven per cent (108/140) of individuals had at least one community contact. Significant proportions of participants engaging received day release work and practical support. In contrast, there was evidence that the psychological components, mentalisation and developing a shared understanding were used less consistently. When engagement was positive, these components were associated with positive achievement of goals for individuals. We were also able to identify how to improve the intervention programme theory, including how to support individuals who were unrealistic in their perception of their ability to cope with challenges post release.Strengths and limitationsOur development work provides a worked example of the development of a complex intervention, particularly given little prior evidence or theory specific to male offenders to build on. Our trial methodological development enabled the completion of, to the best of our knowledge, the first fully powered trial of a mental health intervention for prison leavers with common mental health problems. There were potential weaknesses in the trial methodology in terms of follow-up rates and outcome measures, with the latter potentially being insufficiently sensitive to important but highly individual changes in participants who responded to the intervention.ConclusionsDelivering a randomised controlled trial for prison leavers with acceptable levels of follow-up is possible, despite adverse conditions. Full intervention implementation was challenging, but this is to be expected. Some individuals did respond well to the intervention when both practical and psychological support were flexibly deployed as intended, with evidence that most components were experienced as helpful for some individuals. It is recommended that several key components be developed further and tested, along with improved training and supervision, to support delivery of the Engager intervention within existing teams working with prison leavers

Fine-mapping identifies multiple prostate cancer risk loci at 5p15, one of which associates with TERT expression

Associations between single nucleotide polymorphisms (SNPs) at 5p15 and multiple cancer types have been reported. We have previously shown evidence for a strong association between prostate cancer (PrCa) risk and rs2242652 at 5p15, intronic in the telomerase reverse transcriptase (TERT) gene that encodes TERT. To comprehensively evaluate the association between genetic variation across this region and PrCa, we performed a fine-mapping analysis by genotyping 134 SNPs using a custom Illumina iSelect array or Sequenom MassArray iPlex, followed by imputation of 1094 SNPs in 22 301 PrCa cases and 22 320 controls in The PRACTICAL consortium. Multiple stepwise logistic regression analysis identified four signals in the promoter or intronic regions of TERT that independently associated with PrCa risk. Gene expression analysis of normal prostate tissue showed evidence that SNPs within one of these regions also associated with TERT expression, providing a potential mechanism for predisposition to disease

A network analysis to identify mediators of germline-driven differences in breast cancer prognosis.

Identifying the underlying genetic drivers of the heritability of breast cancer prognosis remains elusive. We adapt a network-based approach to handle underpowered complex datasets to provide new insights into the potential function of germline variants in breast cancer prognosis. This network-based analysis studies ~7.3 million variants in 84,457 breast cancer patients in relation to breast cancer survival and confirms the results on 12,381 independent patients. Aggregating the prognostic effects of genetic variants across multiple genes, we identify four gene modules associated with survival in estrogen receptor (ER)-negative and one in ER-positive disease. The modules show biological enrichment for cancer-related processes such as G-alpha signaling, circadian clock, angiogenesis, and Rho-GTPases in apoptosis

Proteomic analysis of the Plasmodium male gamete reveals the key role for glycolysis in flagellar motility.

BACKGROUND: Gametogenesis and fertilization play crucial roles in malaria transmission. While male gametes are thought to be amongst the simplest eukaryotic cells and are proven targets of transmission blocking immunity, little is known about their molecular organization. For example, the pathway of energy metabolism that power motility, a feature that facilitates gamete encounter and fertilization, is unknown. METHODS: Plasmodium berghei microgametes were purified and analysed by whole-cell proteomic analysis for the first time. Data are available via ProteomeXchange with identifier PXD001163. RESULTS: 615 proteins were recovered, they included all male gamete proteins described thus far. Amongst them were the 11 enzymes of the glycolytic pathway. The hexose transporter was localized to the gamete plasma membrane and it was shown that microgamete motility can be suppressed effectively by inhibitors of this transporter and of the glycolytic pathway. CONCLUSIONS: This study describes the first whole-cell proteomic analysis of the malaria male gamete. It identifies glycolysis as the likely exclusive source of energy for flagellar beat, and provides new insights in original features of Plasmodium flagellar organization

Characterizing prostate cancer risk through multi-ancestry genome-wide discovery of 187 novel risk variants

The transferability and clinical value of genetic risk scores (GRSs) across populations remain limited due to an imbalance in genetic studies across ancestrally diverse populations. Here we conducted a multi-ancestry genome-wide association study of 156,319 prostate cancer cases and 788,443 controls of European, African, Asian and Hispanic men, reflecting a 57% increase in the number of non-European cases over previous prostate cancer genome-wide association studies. We identified 187 novel risk variants for prostate cancer, increasing the total number of risk variants to 451. An externally replicated multi-ancestry GRS was associated with risk that ranged from 1.8 (per standard deviation) in African ancestry men to 2.2 in European ancestry men. The GRS was associated with a greater risk of aggressive versus non-aggressive disease in men of African ancestry (P = 0.03). Our study presents novel prostate cancer susceptibility loci and a GRS with effective risk stratification across ancestry groups

Characterizing Associations and SNP-Environment Interactions for GWAS-Identified Prostate Cancer Risk Markers—Results from BPC3

Genome-wide association studies (GWAS) have identified multiple single nucleotide polymorphisms (SNPs) associated with prostate cancer risk. However, whether these associations can be consistently replicated, vary with disease aggressiveness (tumor stage and grade) and/or interact with non-genetic potential risk factors or other SNPs is unknown. We therefore genotyped 39 SNPs from regions identified by several prostate cancer GWAS in 10,501 prostate cancer cases and 10,831 controls from the NCI Breast and Prostate Cancer Cohort Consortium (BPC3). We replicated 36 out of 39 SNPs (P-values ranging from 0.01 to 10−28). Two SNPs located near KLK3 associated with PSA levels showed differential association with Gleason grade (rs2735839, P = 0.0001 and rs266849, P = 0.0004; case-only test), where the alleles associated with decreasing PSA levels were inversely associated with low-grade (as defined by Gleason grade <8) tumors but positively associated with high-grade tumors. No other SNP showed differential associations according to disease stage or grade. We observed no effect modification by SNP for association with age at diagnosis, family history of prostate cancer, diabetes, BMI, height, smoking or alcohol intake. Moreover, we found no evidence of pair-wise SNP-SNP interactions. While these SNPs represent new independent risk factors for prostate cancer, we saw little evidence for effect modification by other SNPs or by the environmental factors examined

Telomere structure and maintenance gene variants and risk of five cancer types.

Telomeres cap chromosome ends, protecting them from degradation, double-strand breaks, and end-to-end fusions. Telomeres are maintained by telomerase, a reverse transcriptase encoded by TERT, and an RNA template encoded by TERC. Loci in the TERT and adjoining CLPTM1L region are associated with risk of multiple cancers. We therefore investigated associations between variants in 22 telomere structure and maintenance gene regions and colorectal, breast, prostate, ovarian, and lung cancer risk. We performed subset-based meta-analyses of 204,993 directly-measured and imputed SNPs among 61,851 cancer cases and 74,457 controls of European descent. Independent associations for SNP minor alleles were identified using sequential conditional analysis (with gene-level p value cutoffs ≤3.08 × 10-5 ). Of the thirteen independent SNPs observed to be associated with cancer risk, novel findings were observed for seven loci. Across the DCLRE1B region, rs974494 and rs12144215 were inversely associated with prostate and lung cancers, and colorectal, breast, and prostate cancers, respectively. Across the TERC region, rs75316749 was positively associated with colorectal, breast, ovarian, and lung cancers. Across the DCLRE1B region, rs974404 and rs12144215 were inversely associated with prostate and lung cancers, and colorectal, breast, and prostate cancers, respectively. Near POT1, rs116895242 was inversely associated with colorectal, ovarian, and lung cancers, and RTEL1 rs34978822 was inversely associated with prostate and lung cancers. The complex association patterns in telomere-related genes across cancer types may provide insight into mechanisms through which telomere dysfunction in different tissues influences cancer risk.Funding for the iCOGS infrastructure came from: the European Community’s Seventh Framework Programme under grant agreement n° 223175 (HEALTH-F2-2009-223175) (COGS), Cancer Research UK (C1287/A10118, C1287/A 10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/A10692, C8197/A16565), the National Institutes of Health (CA128978) and Post-Cancer GWAS initiative (1U19 CA148537, 1U19 CA148065 and 1U19 CA148112 – the GAME-ON initiative), the Department of Defense (W81XWH-10-1-0341), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer, Komen Foundation for the Cure, the Breast Cancer Research Foundation, and the Ovarian Cancer Research Fund.This is the author accepted manuscript. The final version is available from Wiley via http://dx.doi.org/10.1002/ijc.3028

Fine-mapping the HOXB region detects common variants tagging a rare coding allele: evidence for synthetic association in prostate cancer.

The HOXB13 gene has been implicated in prostate cancer (PrCa) susceptibility. We performed a high resolution fine-mapping analysis to comprehensively evaluate the association between common genetic variation across the HOXB genetic locus at 17q21 and PrCa risk. This involved genotyping 700 SNPs using a custom Illumina iSelect array (iCOGS) followed by imputation of 3195 SNPs in 20,440 PrCa cases and 21,469 controls in The PRACTICAL consortium. We identified a cluster of highly correlated common variants situated within or closely upstream of HOXB13 that were significantly associated with PrCa risk, described by rs117576373 (OR 1.30, P = 2.62×10(-14)). Additional genotyping, conditional regression and haplotype analyses indicated that the newly identified common variants tag a rare, partially correlated coding variant in the HOXB13 gene (G84E, rs138213197), which has been identified recently as a moderate penetrance PrCa susceptibility allele. The potential for GWAS associations detected through common SNPs to be driven by rare causal variants with higher relative risks has long been proposed; however, to our knowledge this is the first experimental evidence for this phenomenon of synthetic association contributing to cancer susceptibility

Atlas of prostate cancer heritability in European and African-American men pinpoints tissue-specific regulation.

Although genome-wide association studies have identified over 100 risk loci that explain ∼33% of familial risk for prostate cancer (PrCa), their functional effects on risk remain largely unknown. Here we use genotype data from 59,089 men of European and African American ancestries combined with cell-type-specific epigenetic data to build a genomic atlas of single-nucleotide polymorphism (SNP) heritability in PrCa. We find significant differences in heritability between variants in prostate-relevant epigenetic marks defined in normal versus tumour tissue as well as between tissue and cell lines. The majority of SNP heritability lies in regions marked by H3k27 acetylation in prostate adenoc7arcinoma cell line (LNCaP) or by DNaseI hypersensitive sites in cancer cell lines. We find a high degree of similarity between European and African American ancestries suggesting a similar genetic architecture from common variation underlying PrCa risk. Our findings showcase the power of integrating functional annotation with genetic data to understand the genetic basis of PrCa.This work was supported by NIH fellowship F32 GM106584 (AG), NIH grants R01 MH101244(A.G.), R01 CA188392 (B.P.), U01 CA194393(B.P.), R01 GM107427 (M.L.F.), R01 CA193910 (M.L.F./M.P.) and Prostate Cancer Foundation Challenge Award (M.L.F./M.P.). This study makes use of data generated by the Wellcome Trust Case Control Consortium and the Wellcome Trust Sanger Institute. A full list of the investigators who contributed to the generation of the Wellcome Trust Case Control Consortium data is available on www.wtccc.org.uk. Funding for the Wellcome Trust Case Control Consortium project was provided by the Wellcome Trust under award 076113. This study makes use of data generated by the UK10K Consortium. A full list of the investigators who contributed to the generation of the data is available online (http://www.UK10K.org). The PRACTICAL consortium was supported by the following grants: European Commission's Seventh Framework Programme grant agreement n° 223175 (HEALTH-F2-2009-223175), Cancer Research UK Grants C5047/A7357, C1287/A10118, C5047/A3354, C5047/A10692, C16913/A6135 and The National Institute of Health (NIH) Cancer Post-Cancer GWAS initiative Grant: no. 1 U19 CA 148537-01 (the GAME-ON initiative); Cancer Research UK (C1287/A10118, C1287/A 10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007 and C5047/A10692), the National Institutes of Health (CA128978) and Post-Cancer GWAS initiative (1U19 CA148537, 1U19 CA148065 and 1U19 CA148112—the GAME-ON initiative), the Department of Defense (W81XWH-10-1-0341), A Linneus Centre (Contract ID 70867902), Swedish Research Council (grant no K2010-70X-20430-04-3), the Swedish Cancer Foundation (grant no 09-0677), grants RO1CA056678, RO1CA082664 and RO1CA092579 from the US National Cancer Institute, National Institutes of Health; US National Cancer Institute (R01CA72818); support from The National Health and Medical Research Council, Australia (126402, 209057, 251533, 396414, 450104, 504700, 504702, 504715, 623204, 940394 and 614296); NIH grants CA63464, CA54281 and CA098758; US National Cancer Institute (R01CA128813, PI: J.Y. Park); Bulgarian National Science Fund, Ministry of Education and Science (contract DOO-119/2009; DUNK01/2–2009; DFNI-B01/28/2012); Cancer Research UK grants [C8197/A10123] and [C8197/A10865]; grant code G0500966/75466; NIHR Health Technology Assessment Programme (projects 96/20/06 and 96/20/99); Cancer Research UK grant number C522/A8649, Medical Research Council of England grant number G0500966, ID 75466 and The NCRI, UK; The US Dept of Defense award W81XWH-04-1-0280; Australia Project Grant [390130, 1009458] and Enabling Grant [614296 to APCB]; the Prostate Cancer Foundation of Australia (Project Grant [PG7] and Research infrastructure grant [to APCB]); NIH grant R01 CA092447; Vanderbilt-Ingram Cancer Center (P30 CA68485); Cancer Research UK [C490/A10124] and supported by the UK National Institute for Health Research Biomedical Research Centre at the University of Cambridge; Competitive Research Funding of the Tampere University Hospital (9N069 and X51003); Award Number P30CA042014 from the National Cancer Institute.This is the final version of the article. It first appeared from Nature Publishing Group via http://dx.doi.org/0.1038/ncomms1097