Availability of results of academic randomized trials involving cooperative groups in oncology in France: A systematic search of clinical trial registries.

BACKGROUND: Cooperative groups' involvement is increasing in academic oncological research. We aimed to assess the impact of sponsoring by cooperative groups in France on the availability of results of academic randomized trials in oncology. METHODS: We performed a systematic search using ClinicalTrials.gov and the European Clinical Trials Register. We searched for all academic randomized trials in oncology conducted in France between January 1, 2005 and January 1, 2015. The inclusion criteria were: completed or terminated, phase 2 or 3 randomized trials with an academic (non-industry) sponsor. The main outcome was the publication of the results of trial (either as a journal article or as posting results in a registry) across each type of sponsor. RESULTS: We included 211 randomized trials, mainly phase 3 (n = 135, 64%) and evaluating pharmacological treatments (n = 149, 71%). French cooperative groups were involved in 69 trials (33%), as part of a collaboration in one third (n = 23) of instances. Seventy-one (34%) trials were run by oncologic hospitals, 50 (23%) by university hospitals, and 21 (10%) by European organizations. Seventy-seven randomized trials (36%) had available results (published n = 73, posted n = 6). Cooperative groups were involved in half of those that have been published (37/73). The cumulative probability of results availability was 57% for cooperative groups, 41% for European organizations, 32% for oncologic hospitals, and 17% for university hospital at 10 years from the beginning of trials (p = 0.0006). In the case of collaboration with cooperative groups, the cumulative probability of results availability achieved 59% for university hospitals and 74% for oncologic hospitals. CONCLUSION: The availability of results of randomized trials in oncology remains limited and almost exclusively through publications, but is higher when cooperative groups are involved. POLICY SUMMARY: Sponsoring by a cooperative group should become the rule in academic trials to increase availability of trial results.

Bayesian analysis from phase III trials was underused and poorly reported: a systematic review.

OBJECTIVES: We assessed the reporting of replicability items with the BayesWatch guidelines and crucial items of Bayesian analyses with the Reporting Of Bayes Used in clinical STudies (ROBUST) guidelines in reports of phase III trials. STUDY DESIGN AND SETTING: A literature search of Cochrane CENTRAL, Ovid MEDLINE, and EMBASE database was conducted to identify phase III trials using Bayesian methods for their primary outcome. Two reviewers performed the study selection process independently. RESULTS: From 5,404 articles retrieved, 49 reports of trials were included. The median [interquartile range] number of correctly reported items was four of seven [3-5] for ROBUST guidelines and seven of 10 [6-8] for BayesWatch guidelines. The proportion of correct reporting widely varied among items. The most frequently reported items from BayesWatch were the least specific (objectives, designs, and reporting of results). Specific Bayesian items (analytic technique and prior specifications) were poorly reported. Priors were given for two-thirds of studies and were justified for 22%. Sensitivity analyses were reported for 57% of trials. CONCLUSION: Bayesian methods are underused in phase III trials. Reports frequently lack descriptions of essential methodological components of the Bayesian analysis, such as the description of priors, which remains a critical key to interpreting Bayesian analyses. PROSPERO: CRD42017054929.

A Methodologic Systematic Review of Mobile Health Behavior Change Randomized Trials.

CONTEXT: Mobile health helps providers offer accessible, affordable, tailored behavior change interventions. However, research assessing mobile health interventions may feature methodologic shortcomings and poor reporting. This review aims to summarize the characteristics, methods, and intervention reporting of RCTs evaluating mobile health behavior change interventions. EVIDENCE ACQUISITION: This was a methodologic systematic review of RCTs assessing mobile health behavior change interventions published in PubMed from January 1, 2014 to January 1, 2018, in journals with the upper half of Impact Factors (Clarivate Analytics). Three reviewers independently extracted sample characteristics. Primary outcomes were classified as patient-important or not using definitions from the literature. Any non-patient-important outcomes were then reclassified by a panel of 3 patients. Intervention reporting was assessed by the mobile health Evidence Reporting and Assessment checklist. Data were analyzed in December 2018. EVIDENCE SYNTHESIS: Most of the 231 included RCTs assessed text messaging (51%) or smartphone app (28%) interventions aiming to change nutrition and physical activity (36%) or treatment adherence (25%). Only 8% of RCTs had a patient-important primary outcome, follow-up of ≥6 months, and intent-to-treat analysis. Most primary outcomes were behavioral measures (60%). Follow-up was <3 months in 29% of RCTs. Regarding reporting, 12 of the 16 checklist items were reported in less than half of RCTs (e.g., usability/content testing, 32%; data security, 13%). CONCLUSIONS: Reports of RCTs assessing mobile health behavior change interventions lack information that would be useful for providers, including reporting of long-term intervention impact on patient-important primary outcomes and information needed for intervention replicability.

Use of Late-Life Expectancy for Assessing the Long-Term Benefit of Immune Checkpoint Inhibitors.

To grade the long-term benefit of anticancer agents, the American Society of Clinical Oncology Value Framework (ASCO-VF) awards tail-of-the-curve bonus points by using milestone survival at twice the median control survival. Here, we propose an alternative, late-life expectancy that we defined as the area under the Kaplan-Meier curve from median control survival to the end of follow-up. We analyzed all indications of immune checkpoint inhibitors with survival data and found that 9 indications out of 13 (69.2%) qualified for ASCO-VF tail-of-the-curve bonus points either in progression-free or overall survival. Our proposed score recognized a long-term benefit not captured by the ASCO-VF, for example, for CHECKMATE-66 where twice the median overall survival was not reached. We found that nivolumab was associated with an increase of 65.3% (95% CI = 38.9 to 89.5) in overall survival late-life expectancy, which highlights its important long-term benefit. In conclusion, the ASCO-VF could be improved with the use of late-life expectancy.

Rituximab for induction and maintenance therapy of granulomatosis with polyangiitis: a single-centre cohort study on 114 patients.

OBJECTIVES: To assess efficacy and safety of rituximab (RTX) induction and maintenance therapy for granulomatosis with polyangiitis (GPA) in a single-centre cohort study. METHODS: All patients with active GPA, not enrolled in trials, who received ⩾1 RTX infusion(s) for induction were included. At remission, protocolized maintenance RTX infusions were given every 6 months for 18 months. Kaplan-Meier curves were used to estimate survival rates. Univariable analyses identified factors associated with remission failure and relapse, and Cox models retained independent predictors of relapse. RESULTS: One hundred and fourteen adults with relapsing (65%), refractory/grumbling (22%) or new-onset (13%) GPA received RTX for induction; 100 were given ⩾1 RTX maintenance infusion(s) and 90 received 500 mg every 6 months. Median daily prednisone induction dose was 30 mg; 76% of patients were still receiving a median daily prednisone dose of 5 mg at 2 years. Median follow-up was 3.6 years. Respective 2-year relapse-free survival and RTX retention rates were 85 and 78%. Serious infection and serious adverse event rates were 4.9 and 8.1 per 100 patient-years, respectively. Refractory/grumbling vs new-onset and/or relapsing GPA (P < 0.01 for each individually; P < 0.001 vs the latter two taken together), pachymeningitis (P < 0.05), pure granulomatous disease (P < 0.05) or estimated glomerular filtration rate ⩾60 ml/min (P < 0.01) were associated with remission failure. Multivariate analyses retained refractory/grumbling GPA (P = 0.05), subglottic stenosis (P < 0.005), ENT involvement (P = 0.01) and skin involvement (P < 0.0005) as independent predictors of relapse. CONCLUSION: RTX induction and low-dose preemptive maintenance can effectively and safely induce sustained remission in GPA in a real-life setting.

Living network meta-analysis was feasible when considering the pace of evidence generation.

OBJECTIVES: The aim of the study was to assess the feasibility of living network meta-analysis (NMA) taking into account the pace of evidence generation across different medical areas. STUDY DESIGN AND SETTING: We performed a systematic review to identify published NMAs. For each NMA, we calculated the cumulative number of new trials. To assess the feasibility of living NMA, we considered different update frequencies (4, 6, and 12 months), then evaluated the number of new trials to be included at each update in the NMA and the workload percentage for an update relative to the initial NMA. RESULTS: We identified 77 NMAs covering 17 different medical areas; 60 (78%) had fewer than four new trials included per year, on average, and 5 (7%) had more than seven trials. With an update frequency of 4, 6, and 12 months, the median number of new trials to be included in the NMA was 0 (interquartile range, 0-1), 1 (0-2), and 2 (1-4), respectively, with mean of 4%, 5%, and 11% workload per update, respectively. CONCLUSION: The workload associated with updating a living NMA represents about one-tenth of the initial workload; therefore, living NMA is manageable.

Impact of post-warming culture duration on clinical outcomes of vitrified good-quality blastocyst transfers: a prospective randomized study.

OBJECTIVE: To determine whether post-warming culture duration (1 hour vs. 18 hours) influences implantation rates (IRs) of good-quality blastocysts (GQB) in a good-prognosis population. DESIGN: Prospective interventional randomized study. SETTING: University hospital. PATIENT(S): One hundred sixty-two GQB transfers. INTERVENTION(S): Patients' vitrified blastocysts were randomly allocated to group A, warming on the day before transfer (n = 81), or B, warming on the day of transfer (n = 81). MAIN OUTCOME MEASURE(S): IR, live birth rate, reexpansion degree, and quality after warming and immediately before transfer. RESULT(S): Quality of the warmed and transferred blastocysts was similar (respectively, 39.1% and 32.7% top quality [≥B4AA/AB/BA] in group A vs. 41.7 and 42.2% in group B). In group A, 14 of 102 blastocysts (12.2%) appeared to be unsuitable for transfer, versus only 1 of 103 (0.9%) in group B, thus leading to an additional warming. As expected, reexpansion degree just before transfer was higher in group A (0.90 vs. 0.70). Likewise, the proportion of hatched blastocysts before transfer was higher after a longer culture period (38.6% in group A vs. 12.7% in group B). IRs were similar (38.0% in group A vs. 36% in group B), as were live birth rates (35.8% in group A vs. 34.6% in group B). CONCLUSION(S): IRs were not different, whatever the duration of post-warming culture of GQB. Both warming strategies could be applied to good-prognosis patients to optimize the laboratory workflow without any detrimental effect.

Impact of Biomarker-based Design Strategies on the Risk of False-Positive Findings in Targeted Therapy Evaluation.

PURPOSE: When there is more than one potentially predictive biomarker for a new drug, the drug is often evaluated in different subpopulations defined by different biomarkers. We aim to (i) estimate the risk of false-positive findings with this approach and (ii) evaluate the cross-validated adaptive signature design (CVASD) as a potential alternative. EXPERIMENTAL DESIGN: By using numerically simulated data, we compare the current approach and the CVASD across different settings and scenarios. We consider three strategies for CVASD. The first two CVASD strategies are different in terms of the partitioning of the overall significance level (between the population test and the subgroup test). In the third CVASD strategy, the order of the two tests is reversed, that is, the population test is realized when the prioritized subgroup test is not statistically significant. RESULTS: The current approach results in a high risk of false-positive findings, whereas this risk is close to the nominal level of 5% once applying the CVASD, regardless of the strategy. When the treatment is equally effective to all patients, only the CVASD strategies could specify correctly the absence of a sensitive subgroup. When the treatment is only effective for some sensitive responders, the third CVASD strategy stands out by its ability to correctly identify the predictive biomarker(s). CONCLUSIONS: The drug-biomarker coevaluation based on a series of independent enrichment trials can result in a high risk of false-positive findings. CVASD with some appropriate adjustments can be a good alternative to overcome this multiplicity issue.

Mapping of Crowdsourcing in Health: Systematic Review.

BACKGROUND: Crowdsourcing involves obtaining ideas, needed services, or content by soliciting Web-based contributions from a crowd. The 4 types of crowdsourced tasks (problem solving, data processing, surveillance or monitoring, and surveying) can be applied in the 3 categories of health (promotion, research, and care). OBJECTIVE: This study aimed to map the different applications of crowdsourcing in health to assess the fields of health that are using crowdsourcing and the crowdsourced tasks used. We also describe the logistics of crowdsourcing and the characteristics of crowd workers. METHODS: MEDLINE, EMBASE, and ClinicalTrials.gov were searched for available reports from inception to March 30, 2016, with no restriction on language or publication status. RESULTS: We identified 202 relevant studies that used crowdsourcing, including 9 randomized controlled trials, of which only one had posted results at ClinicalTrials.gov. Crowdsourcing was used in health promotion (91/202, 45.0%), research (73/202, 36.1%), and care (38/202, 18.8%). The 4 most frequent areas of application were public health (67/202, 33.2%), psychiatry (32/202, 15.8%), surgery (22/202, 10.9%), and oncology (14/202, 6.9%). Half of the reports (99/202, 49.0%) referred to data processing, 34.6% (70/202) referred to surveying, 10.4% (21/202) referred to surveillance or monitoring, and 5.9% (12/202) referred to problem-solving. Labor market platforms (eg, Amazon Mechanical Turk) were used in most studies (190/202, 94%). The crowd workers' characteristics were poorly reported, and crowdsourcing logistics were missing from two-thirds of the reports. When reported, the median size of the crowd was 424 (first and third quartiles: 167-802); crowd workers' median age was 34 years (32-36). Crowd workers were mainly recruited nationally, particularly in the United States. For many studies (58.9%, 119/202), previous experience in crowdsourcing was required, and passing a qualification test or training was seldom needed (11.9% of studies; 24/202). For half of the studies, monetary incentives were mentioned, with mainly less than US $1 to perform the task. The time needed to perform the task was mostly less than 10 min (58.9% of studies; 119/202). Data quality validation was used in 54/202 studies (26.7%), mainly by attention check questions or by replicating the task with several crowd workers. CONCLUSIONS: The use of crowdsourcing, which allows access to a large pool of participants as well as saving time in data collection, lowering costs, and speeding up innovations, is increasing in health promotion, research, and care. However, the description of crowdsourcing logistics and crowd workers' characteristics is frequently missing in study reports and needs to be precisely reported to better interpret the study findings and replicate them.

Factors Associated With Postmarketing Research for Approved Indications for Novel Medicines Approved by Both the FDA and EMA Between 2005 and 2010: A Multivariable Analysis.

We examined whether drug-related characteristics-conditions, development, manufacturers, revenues-were associated with postmarketing research in terms of the number of trials and total population to be enrolled. We included 63 drugs, corresponding to 3,867 postmarketing trials of approved indications. On multivariable analysis, both the number of postmarketing trials and population to be enrolled were associated with expected length of treatment (ratio of means (RoM) = 2.35 and RoM = 8.65) and number of patients in pivotal trials (RoM = 1.11 and RoM = 1.25 per thousand patients). The number of postmarketing trials was increased for drugs approved with surrogate endpoints (RoM = 2.19), generating high revenues (RoM = 1.08 per billion dollars) and addressing greater disease burden (RoM = 1.90 per hundred million disability-adjusted life years). The population to be included was increased for drugs approved after an increased number of pivotal trials (RoM = 1.82) and those unaffected by safety concerns (RoM = 2.63). Postmarketing trials seem to be driven both by medical and market factors.

Post-marketing research and its outcome for novel anticancer agents approved by both the FDA and EMA between 2005 and 2010: A cross-sectional study.

Post-marketing research in oncology has rarely been described. We aimed to characterize post-marketing trials for a consistent set of anticancer agents over a long period. We performed a cross-sectional analysis of post-marketing trials registered at ClinicalTrials.gov through September 2014 for novel anticancer agents approved by both the US Food and Drug Administration and the European Medicines Agency between 2005 and 2010. All relevant post-marketing trials were classified according to indication, primary outcome, starting date, sponsors, and planned enrollment. Supplemental indications were retrieved from regulatory documents and publication rate was assessed by two different methods. Ten novel anticancer agents were eligible: five were indicated for hematologic malignancies and the remaining five for solid cancers (three for kidney cancer). We identified 2,345 post-marketing trials; 1,362 (58.1%) targeted an indication other than the originally approved one. We observed extreme variations among drugs in both number of post-marketing trials (range 8-530) and overall population to be enrolled per trial (1-8,381). Post-marketing trials assessed almost all types of cancers, the three most frequently studied cancers being leukemia, kidney cancer and myeloma. In all, 6.6% of post-marketing trials had a clinical endpoint as a primary outcome, and 35.9% and 54.1% had a safety or surrogate endpoint, respectively, as a primary outcome. Nine drugs obtained approval for supplemental indications. The publication rate at 10 years was 12.3 to 26.1% depending on the analysis method. In conclusion, we found that post-marketing research in oncology is highly heterogeneous and the publication rate of launched trials is low.

Postmarketing studies for novel drugs approved by both the FDA and EMA between 2005 and 2010: a cross-sectional study.

OBJECTIVES: To characterise postmarketing studies for drugs that were newly approved by the US Food and Drug Administration and the European Medicines Agency. DESIGN AND SETTING: Cross-sectional analysis of postmarketing studies registered in ClinicalTrials.gov until September 2014 for all novel drugs approved by both regulators between 2005 and 2010. Regulatory documents from both agencies were used. PRIMARY AND SECONDARY OUTCOME MEASURES: All identified postmarketing studies were classified according to planned enrolment, funding, status and geographical location, and we determined whether studies studied the originally approved indication. RESULTS: Overall, 69 novel drugs approved between 2005 and 2010 were eligible for inclusion. A total of 6679 relevant postmarketing studies were identified; 5972 were interventional (89.4%). The median number of studies per drug was 55 (IQR 33-119) and median number of patients to be enrolled per study was 60 (IQR 28-183). Industry was the primary sponsor of 2713 studies (40.6%) and was a primary or secondary sponsor in 4176 studies (62.5%). In all, 2901 studies (43.4%) were completed, 487 (7.3%) terminated, 1013 (15.2%) active yet not recruiting, 1895 (28.4%) recruiting and 319 (4.8%) not yet recruiting. A total of 80% of studies were conducted in only one country and 84.4% took place in Europe and/or North America; 2441 (36.5%) studied another indication than the originally approved indication. Studies designed in the originally approved indication were found to be more industry-sponsored than others 68.7%vs53.7%; P<0.0001. CONCLUSIONS: Postmarketing pharmaceutical research was highly variable and predominantly located in North America and Europe. Postmarketing studies were frequently designed to study indications other than the originally approved one. Although some findings were reassuring, others question the lack of coordination of postmarketing research.

Should we consider day-2 and day-3 embryo morphology before day-5 transfer when blastocysts reach a similar good quality?

Clinical outcomes of 291 day-5 blastocyst transfers carried out between January 2012 and March 2016 were retrospectively compared according to their quality at day 2 and 3. Inclusion criteria were female age younger than 37 years; first or second IVF and intracytoplasmic sperm injection cycle; quality of the transferred blastocyst: blastocoele B3 or higher; inner-cell-mass A/B; trophectoderm A/B; and known implantation outcome for each transferred blastocyst. Blastocysts were classified into good-quality and poor-quality embryo groups at day 2 and 3. Implantation (38.7% versus 41.4), clinical pregnancy (40.3% versus 45.9%), miscarriage (22.2% versus 26.7%;) and live birth rates (37.4% versus 38.8%) were comparable in day 2 good and poor-quality embryo groups. No signficiant differences in morphology of transferred blastocysts at day 3 were found. Multivariable analysis highlighted that poor or good embryo quality at day 2 and day 3 were not predictive of the implantation of good-quality blastocysts (at day 2: adjusted odds ratio = 0.82 CI 95% 0.49 to 1.38; at day 3: adjusted odds ratio = 1.39; CI 95% 0.77 to 2.52). Good-quality blastocyst transfer should, therefore, be carried out irrespective of embryo quality at cleavage stage, as it may not compromise success rates in a good-prognosis population.

Evidence for Treatment-by-Biomarker interaction for FDA-approved Oncology Drugs with Required Pharmacogenomic Biomarker Testing.

For oncology drugs that were approved by the US Food and Drug Administration (FDA) and required pharmacogenomic biomarker testing, we describe 1) the use of enrichment (biomarker-positive patients) and a randomized controlled design by pre-approval trials and 2) the treatment-by-biomarker interaction. From the 137 drugs included in the FDA table, we selected the 22 oncology drugs with required genetic testing in their labels. These drugs corresponded to 35 approvals supported by 80 clinical studies included in the FDA medical officer reviews of efficacy. For two thirds of approvals (24/35, 69%), all clinical studies were restricted to biomarker-positive patients (enriched). Among the 11 remaining approvals with at least one non-enriched trial, for five approvals, the non-enriched studies were non-randomized. The treatment-by-biomarker interaction was statistically significant for three approvals and missing for two. Among the six approvals with a non-enriched randomized controlled trial, three featured a statistically significant treatment-by-biomarker interaction (p < 0.10), for an enhanced treatment effect in the biomarker-positive subgroup. For two thirds of FDA approvals of anticancer agents, the requirement for predictive biomarker testing was based on clinical development restricted to biomarker-positive patients. We found only few cases with clinical evidence that biomarker-negative patients would not benefit from treatment.

Jump, Hop, or Skip: Modeling Practice Effects in Studies of Determinants of Cognitive Change in Older Adults.

Improvements in cognitive test scores upon repeated assessment due to practice effects (PEs) are well documented, but there is no empirical evidence on whether alternative specifications of PEs result in different estimated associations between exposure and rate of cognitive change. If alternative PE specifications produce different estimates of association between an exposure and rate of cognitive change, this would be a challenge for nearly all longitudinal research on determinants of cognitive aging. Using data from 3 cohort studies-the Three-City Study-Dijon (Dijon, France, 1999-2010), the Normative Aging Study (Greater Boston, Massachusetts, 1993-2007), and the Washington Heights-Inwood Community Aging Project (New York, New York, 1999-2012)-for 2 exposures (diabetes and depression) and 3 cognitive outcomes, we compared results from longitudinal models using alternative PE specifications: no PEs; use of an indicator for the first cognitive visit; number of prior testing occasions; and square root of the number of prior testing occasions. Alternative specifications led to large differences in the estimated rates of cognitive change but minimal differences in estimated associations of exposure with cognitive level or change. Based on model fit, using an indicator for the first visit was often (but not always) the preferred model. PE specification can lead to substantial differences in estimated rates of cognitive change, but in these diverse examples and study samples it did not substantively affect estimated associations of risk factors with change.

Using an Alzheimer Disease Polygenic Risk Score to Predict Memory Decline in Black and White Americans Over 14 Years of Follow-up.

Evidence on whether genetic predictors of Alzheimer disease (AD) also predict memory decline is inconsistent, and limited data are available for African ancestry populations. For 8253 non-Hispanic white (NHW) and non-Hispanic black (NHB) Health and Retirement Study participants with memory scores measured 1 to 8 times between 1998 and 2012 (average baseline age=62), we calculated weighted polygenic risk scores [AD Genetic Risk Score (AD-GRS)] using the top 22 AD-associated loci, and an alternative score excluding apolipoprotein E (APOE) (AD-GRSexAPOE). We used generalized linear models with AD-GRS-by-age and AD-GRS-by-age interactions (age centered at 70) to predict memory decline. Average NHB decline was 26% faster than NHW decline (P<0.001). Among NHW, 10% higher AD-GRS predicted faster memory decline (linear ß=-0.058 unit decrease over 10 y; 95% confidence interval,-0.074 to -0.043). AD-GRSexAPOE also predicted faster decline for NHW, although less strongly. Among NHB, AD-GRS predicted faster memory decline (linear ß=-0.050; 95% confidence interval, -0.106 to 0.006), but AD-GRSexAPOE did not. Our nonsignificant estimate among NHB may reflect insufficient statistical power or a misspecified AD-GRS among NHB as an overwhelming majority of genome-wide association studies are conducted in NHW. A polygenic score based on previously identified AD loci predicts memory loss in US blacks and whites.

Pharmacogenomic biomarkers as inclusion criteria in clinical trials of oncology-targeted drugs: a mapping of ClinicalTrials.gov.

PURPOSE: The aim of this study was to describe pharmacogenomics-based inclusion criteria (enrichment) and the main characteristics of clinical trials involving oncology-targeted therapies. METHODS: Clinical trials of oncology-targeted therapies approved after 2005 with pharmacogenomic testing required or recommended in their label were retrieved from a mapping of the ClinicalTrials.gov database. RESULTS: We examined information for 12 drugs and 858 trials. Overall, 434 trials (51%) were enriched on the biomarker first mentioned in the label and 145 (17%) were enriched on another biomarker, whereas 270 trials (31%) included all patients. The median proportion of trials corresponding to both the drug's indication and drug's target was 35%. Of the 361 trials that tested drugs in another disease than the first one in the label, 219 (61%) were without enrichment and 87 (24%) were actually enriched but on another biomarker than the first one in the label. CONCLUSION: Several drugs have been tested in trials enriched on many different biomarkers. Nonetheless, most targeted therapies have been developed only using biomarker-positive patients; therefore, exclusion of biomarker-negative patients from treatment relies on only preclinical data and on biological understanding of the disease and target.Genet Med 18 8, 796-805.