The serotonin receptor 3E variant is a risk factor for female IBS-D.

Irritable bowel syndrome (IBS) is a gut-brain disorder of multifactorial origin. Evidence of disturbed serotonergic function in IBS accumulated for the 5-HT3 receptor family. 5-HT3Rs are encoded by HTR3 genes and control GI function, and peristalsis and secretion, in particular. Moreover, 5-HT3R antagonists are beneficial in the treatment of diarrhea predominant IBS (IBS-D). We previously reported on functionally relevant SNPs in HTR3A c.-42C > T (rs1062613), HTR3C p.N163K (rs6766410), and HTR3E c.*76G > A (rs56109847 = rs62625044) being associated with IBS-D, and the HTR3B variant p.Y129S (rs1176744) was also described within the context of IBS. We performed a multi-center study to validate previous results and provide further evidence for the relevance of HTR3 genes in IBS pathogenesis. Therefore, genotype data of 2682 IBS patients and 9650 controls from 14 cohorts (Chile, Germany (2), Greece, Ireland, Spain, Sweden (2), the UK (3), and the USA (3)) were taken into account. Subsequent meta-analysis confirmed HTR3E c.*76G > A (rs56109847 = rs62625044) to be associated with female IBS-D (OR = 1.58; 95% CI (1.18, 2.12)). Complementary expression studies of four GI regions (jejunum, ileum, colon, sigmoid colon) of 66 IBS patients and 42 controls revealed only HTR3E to be robustly expressed. On top, HTR3E transcript levels were significantly reduced in the sigma of IBS patients (p = 0.0187); more specifically, in those diagnosed with IBS-D (p = 0.0145). In conclusion, meta-analysis confirmed rs56109847 = rs62625044 as a risk factor for female IBS-D. Expression analysis revealed reduced HTR3E levels in the sigmoid colon of IBS-D patients, which underlines the relevance of HTR3E in the pathogenesis of IBS-D.

The alternative serotonin transporter promoter P2 impacts gene function in females with irritable bowel syndrome.

Irritable bowel syndrome (IBS) is a gut-brain disorder in which symptoms are shaped by serotonin acting centrally and peripherally. The serotonin transporter gene SLC6A4 has been implicated in IBS pathophysiology, but the underlying genetic mechanisms remain unclear. We sequenced the alternative P2 promoter driving intestinal SLC6A4 expression and identified single nucleotide polymorphisms (SNPs) that were associated with IBS in a discovery sample. Identified SNPs built different haplotypes, and the tagging SNP rs2020938 seems to associate with constipation-predominant IBS (IBS-C) in females. rs2020938 validation was performed in 1978 additional IBS patients and 6,038 controls from eight countries. Meta-analysis on data from 2,175 IBS patients and 6,128 controls confirmed the association with female IBS-C. Expression analyses revealed that the P2 promoter drives SLC6A4 expression primarily in the small intestine. Gene reporter assays showed a functional impact of SNPs in the P2 region. In silico analysis of the polymorphic promoter indicated differential expression regulation. Further follow-up revealed that the major allele of the tagging SNP rs2020938 correlates with differential SLC6A4 expression in the jejunum and with stool consistency, indicating functional relevance. Our data consolidate rs2020938 as a functional SNP associated with IBS-C risk in females, underlining the relevance of SLC6A4 in IBS pathogenesis.

Efficacy and safety of semaglutide compared with liraglutide and placebo for weight loss in patients with obesity: a randomised, double-blind, placebo and active controlled, dose-ranging, phase 2 trial.

BACKGROUND: Obesity is a major public health issue, and new pharmaceuticals for weight management are needed. Therefore, we evaluated the efficacy and safety of the glucagon-like peptide-1 (GLP-1) analogue semaglutide in comparison with liraglutide and a placebo in promoting weight loss. METHODS: We did a randomised, double-blind, placebo and active controlled, multicentre, dose-ranging, phase 2 trial. The study was done in eight countries involving 71 clinical sites. Eligible participants were adults (≥18 years) without diabetes and with a body-mass index (BMI) of 30 kg/m2 or more. We randomly assigned participants (6:1) to each active treatment group (ie, semaglutide [0·05 mg, 0·1 mg, 0·2 mg, 0·3 mg, or 0·4 mg; initiated at 0·05 mg per day and incrementally escalated every 4 weeks] or liraglutide [3·0 mg; initiated at 0·6 mg per day and escalated by 0·6 mg per week]) or matching placebo group (equal injection volume and escalation schedule to active treatment group) using a block size of 56. All treatment doses were delivered once-daily via subcutaneous injections. Participants and investigators were masked to the assigned study treatment but not the target dose. The primary endpoint was percentage weight loss at week 52. The primary analysis was done using intention-to-treat ANCOVA estimation with missing data derived from the placebo pool. This study is registered with ClinicalTrials.gov, number NCT02453711. FINDINGS: Between Oct 1, 2015, and Feb 11, 2016, 957 individuals were randomly assigned (102-103 participants per active treatment group and 136 in the pooled placebo group). Mean baseline characteristics included age 47 years, bodyweight 111·5 kg, and BMI 39·3 kg/m2. Bodyweight data were available for 891 (93%) of 957 participants at week 52. Estimated mean weight loss was -2·3% for the placebo group versus -6·0% (0·05 mg), -8·6% (0·1 mg), -11·6% (0·2 mg), -11·2% (0·3 mg), and -13·8% (0·4 mg) for the semaglutide groups. All semaglutide groups versus placebo were significant (unadjusted p≤0·0010), and remained significant after adjustment for multiple testing (p≤0·0055). Mean bodyweight reductions for 0·2 mg or more of semaglutide versus liraglutide were all significant (-13·8% to -11·2% vs -7·8%). Estimated weight loss of 10% or more occurred in 10% of participants receiving placebo compared with 37-65% receiving 0·1 mg or more of semaglutide (p<0·0001 vs placebo). All semaglutide doses were generally well tolerated, with no new safety concerns. The most common adverse events were dose-related gastrointestinal symptoms, primarily nausea, as seen previously with GLP-1 receptor agonists. INTERPRETATION: In combination with dietary and physical activity counselling, semaglutide was well tolerated over 52 weeks and showed clinically relevant weight loss compared with placebo at all doses. FUNDING: Novo Nordisk A/S.

Imputation of missing genotypes within LD-blocks relying on the basic coalescent and beyond: consideration of population growth and structure.

BACKGROUND: Genotypes not directly measured in genetic studies are often imputed to improve statistical power and to increase mapping resolution. The accuracy of standard imputation techniques strongly depends on the similarity of linkage disequilibrium (LD) patterns in the study and reference populations. Here we develop a novel approach for genotype imputation in low-recombination regions that relies on the coalescent and permits to explicitly account for population demographic factors. To test the new method, study and reference haplotypes were simulated and gene trees were inferred under the basic coalescent and also considering population growth and structure. The reference haplotypes that first coalesced with study haplotypes were used as templates for genotype imputation. Computer simulations were complemented with the analysis of real data. Genotype concordance rates were used to compare the accuracies of coalescent-based and standard (IMPUTE2) imputation. RESULTS: Simulations revealed that, in LD-blocks, imputation accuracy relying on the basic coalescent was higher and less variable than with IMPUTE2. Explicit consideration of population growth and structure, even if present, did not practically improve accuracy. The advantage of coalescent-based over standard imputation increased with the minor allele frequency and it decreased with population stratification. Results based on real data indicated that, even in low-recombination regions, further research is needed to incorporate recombination in coalescence inference, in particular for studies with genetically diverse and admixed individuals. CONCLUSIONS: To exploit the full potential of coalescent-based methods for the imputation of missing genotypes in genetic studies, further methodological research is needed to reduce computer time, to take into account recombination, and to implement these methods in user-friendly computer programs. Here we provide reproducible code which takes advantage of publicly available software to facilitate further developments in the field.

TP53-based interaction analysis identifies cis-eQTL variants for TP53BP2, FBXO28, and FAM53A that associate with survival and treatment outcome in breast cancer.

TP53 overexpression is indicative of somatic TP53 mutations and associates with aggressive tumors and poor prognosis in breast cancer. We utilized a two-stage SNP association study to detect variants associated with breast cancer survival in a TP53-dependent manner. Initially, a genome-wide study (n = 575 cases) was conducted to discover candidate SNPs for genotyping and validation in the Breast Cancer Association Consortium (BCAC). The SNPs were then tested for interaction with tumor TP53 status (n = 4,610) and anthracycline treatment (n = 17,828). For SNPs interacting with anthracycline treatment, siRNA knockdown experiments were carried out to validate candidate genes.In the test for interaction between SNP genotype and TP53 status, we identified one locus, represented by rs10916264 (p(interaction) = 3.44 × 10-5; FDR-adjusted p = 0.0011) in estrogen receptor (ER) positive cases. The rs10916264 AA genotype associated with worse survival among cases with ER-positive, TP53-positive tumors (hazard ratio [HR] 2.36, 95% confidence interval [C.I] 1.45 - 3.82). This is a cis-eQTL locus for FBXO28 and TP53BP2; expression levels of these genes were associated with patient survival specifically in ER-positive, TP53-mutated tumors. Additionally, the SNP rs798755 was associated with survival in interaction with anthracycline treatment (p(interaction) = 9.57 × 10-5, FDR-adjusted p = 0.0130). RNAi-based depletion of a predicted regulatory target gene, FAM53A, indicated that this gene can modulate doxorubicin sensitivity in breast cancer cell lines.If confirmed in independent data sets, these results may be of clinical relevance in the development of prognostic and predictive marker panels for breast cancer.

Using next-generation DNA sequence data for genetic association tests based on allele counts with and without consideration of zero inflation.

The relationship between genetic variability and individual phenotypes is usually investigated by testing for association relying on called genotypes. Allele counts obtained from next-generation sequence data could be used for this purpose too. Genetic association can be examined by treating alternative allele counts (AACs) as the response variable in negative binomial regression. AACs from sequence data often contain an excess of zeros, thus motivating the use of Hurdle and zero-inflated models. Here we examine rough type I error rates and the ability to pick out variants with small probability values for 7 different testing approaches that incorporate AACs as an explanatory or as a response variable. Model comparisons relied on chromosome 3 DNA sequence data from 407 Hispanic participants in the Type 2 Diabetes Genetic Exploration by Next-generation sequencing in Ethnic Samples (T2D-GENES) project 1 with complete information on diastolic blood pressure and related medication. Our results suggest that in the investigation of the relationship between AAC as response variable and individual phenotypes as explanatory variable, Hurdle-negative binomial regression has some advantages. This model showed a good ability to discriminate strongly associated variants and controlled overall type I error rates. However, probability values from Hurdle-negative binomial regression were not obtained for approximately 25 % of the investigated variants because of convergence problems, and the mass of the probability value distribution was concentrated around 1.

Genes associated with histopathologic features of triple negative breast tumors predict molecular subtypes.

Distinct subtypes of triple negative (TN) breast cancer have been identified by tumor expression profiling. However, little is known about the relationship between histopathologic features of TN tumors, which reflect aspects of both tumor behavior and tumor microenvironment, and molecular TN subtypes. The histopathologic features of TN tumors were assessed by central review and 593 TN tumors were subjected to whole genome expression profiling using the Illumina Whole Genome DASL array. TN molecular subtypes were defined based on gene expression data associated with histopathologic features of TN tumors. Gene expression analysis yielded signatures for four TN subtypes (basal-like, androgen receptor positive, immune, and stromal) consistent with previous studies. Expression analysis also identified genes significantly associated with the 12 histological features of TN tumors. Development of signatures using these markers of histopathological features resulted in six distinct TN subtype signatures, including an additional basal-like and stromal signature. The additional basal-like subtype was distinguished by elevated expression of cell motility and glucose metabolism genes and reduced expression of immune signaling genes, whereas the additional stromal subtype was distinguished by elevated expression of immunomodulatory pathway genes. Histopathologic features that reflect heterogeneity in tumor architecture, cell structure, and tumor microenvironment are related to TN subtype. Accounting for histopathologic features in the development of gene expression signatures, six major subtypes of TN breast cancer were identified.

Genetic predisposition to ductal carcinoma in situ of the breast.

BACKGROUND: Ductal carcinoma in situ (DCIS) is a non-invasive form of breast cancer. It is often associated with invasive ductal carcinoma (IDC), and is considered to be a non-obligate precursor of IDC. It is not clear to what extent these two forms of cancer share low-risk susceptibility loci, or whether there are differences in the strength of association for shared loci. METHODS: To identify genetic polymorphisms that predispose to DCIS, we pooled data from 38 studies comprising 5,067 cases of DCIS, 24,584 cases of IDC and 37,467 controls, all genotyped using the iCOGS chip. RESULTS: Most (67 %) of the 76 known breast cancer predisposition loci showed an association with DCIS in the same direction as previously reported for invasive breast cancer. Case-only analysis showed no evidence for differences between associations for IDC and DCIS after considering multiple testing. Analysis by estrogen receptor (ER) status confirmed that loci associated with ER positive IDC were also associated with ER positive DCIS. Analysis of DCIS by grade suggested that two independent SNPs at 11q13.3 near CCND1 were specific to low/intermediate grade DCIS (rs75915166, rs554219). These associations with grade remained after adjusting for ER status and were also found in IDC. We found no novel DCIS-specific loci at a genome wide significance level of P < 5.0x10(-8). CONCLUSION: In conclusion, this study provides the strongest evidence to date of a shared genetic susceptibility for IDC and DCIS. Studies with larger numbers of DCIS are needed to determine if IDC or DCIS specific loci exist.

A polymorphism in the base excision repair gene PARP2 is associated with differential prognosis by chemotherapy among postmenopausal breast cancer patients.

BACKGROUND: Personalized therapy considering clinical and genetic patient characteristics will further improve breast cancer survival. Two widely used treatments, chemotherapy and radiotherapy, can induce oxidative DNA damage and, if not repaired, cell death. Since base excision repair (BER) activity is specific for oxidative DNA damage, we hypothesized that germline genetic variation in this pathway will affect breast cancer-specific survival depending on treatment. METHODS: We assessed in 1,408 postmenopausal breast cancer patients from the German MARIE study whether cancer specific survival after adjuvant chemotherapy, anthracycline chemotherapy, and radiotherapy is modulated by 127 Single Nucleotide Polymorphisms (SNPs) in 21 BER genes. For SNPs with interaction terms showing p<0.1 (likelihood ratio test) using multivariable Cox proportional hazard analyses, replication in 6,392 patients from nine studies of the Breast Cancer Association Consortium (BCAC) was performed. RESULTS: rs878156 in PARP2 showed a differential effect by chemotherapy (p=0.093) and was replicated in BCAC studies (p=0.009; combined analysis p=0.002). Compared to non-carriers, carriers of the variant G allele (minor allele frequency=0.07) showed better survival after chemotherapy (combined allelic hazard ratio (HR)=0.75, 95% 0.53-1.07) and poorer survival when not treated with chemotherapy (HR=1.42, 95% 1.08-1.85). A similar effect modification by rs878156 was observed for anthracycline-based chemotherapy in both MARIE and BCAC, with improved survival in carriers (combined allelic HR=0.73, 95% CI 0.40-1.32). None of the SNPs showed significant differential effects by radiotherapy. CONCLUSIONS: Our data suggest for the first time that a SNP in PARP2, rs878156, may together with other genetic variants modulate cancer specific survival in breast cancer patients depending on chemotherapy. These germline SNPs could contribute towards the design of predictive tests for breast cancer patients.

Association between the BsmI Polymorphism in the Vitamin D Receptor Gene and Breast Cancer Risk: Results from a Pakistani Case-Control Study.

BACKGROUND: Vitamin D is postulated to decrease the risk of breast cancer by inhibiting cell proliferation via the vitamin D receptor (VDR). Two common single nucleotide polymorphisms (SNPs) in the VDR gene, rs1544410 (BsmI) and rs2228570 (FokI), are inconsistently associated with breast cancer risk in Caucasian populations, while data for Asians are scarce. Here, we investigated the possible contribution of these SNPs to breast cancer risk in Pakistani breast cancer patients and in controls participating in a hospital-based breast cancer case-control study (PAK-BCCC). METHODS: Genotyping of the BsmI and FokI SNPs was performed by PCR-based restriction fragment length polymorphism (RFLP) analysis of 463 genetically enriched female breast cancer cases with known BRCA1/2 status and in 1,012 controls from Pakistan. The association between SNP genotypes and breast cancer risk was investigated by logistic regression adjusted for potential breast cancer risk factors and stratified by BRCA1/2 status and family history. Odds ratios (ORs) and 95% confidence intervals (CIs) were reported. RESULTS: The b allele of the BsmI was associated with an increased breast cancer risk (per b allele OR 1.28, 95% CI 1.09-1.49, P = 0.003). Subgroup analysis revealed that this effect was restricted to BRCA1/2 non-carriers (per b allele OR 1.33, 95% CI 1.11-1.59, P = 0.002) and was stronger in those who reported a positive family history of breast and/or ovarian cancer (per b allele OR 1.64, 95% CI 1.20-2.22, P = 0.002). No association with breast cancer risk was detected for the FokI SNP. CONCLUSIONS: The BsmI polymorphism in the VDR gene may be associated with an increased breast cancer risk in Pakistani women negative for BRCA1/2 germline mutations.

The SNP rs6500843 in 16p13.3 is associated with survival specifically among chemotherapy-treated breast cancer patients.

We have utilized a two-stage study design to search for SNPs associated with the survival of breast cancer patients treated with adjuvant chemotherapy. Our initial GWS data set consisted of 805 Finnish breast cancer cases (360 treated with adjuvant chemotherapy). The top 39 SNPs from this stage were analyzed in three independent data sets: iCOGS (n=6720 chemotherapy-treated cases), SUCCESS-A (n=3596), and POSH (n=518). Two SNPs were successfully validated: rs6500843 (any chemotherapy; per-allele HR 1.16, 95% C.I. 1.08-1.26, p=0.0001, p(adjusted)=0.0091), and rs11155012 (anthracycline therapy; per-allele HR 1.21, 95% C.I. 1.08-1.35, p=0.0010, p(adjusted)=0.0270). The SNP rs6500843 was found to specifically interact with adjuvant chemotherapy, independently of standard prognostic markers (p(interaction)=0.0009), with the rs6500843-GG genotype corresponding to the highest hazard among chemotherapy-treated cases (HR 1.47, 95% C.I. 1.20-1.80). Upon trans-eQTL analysis of public microarray data, the rs6500843 locus was found to associate with the expression of a group of genes involved in cell cycle control, notably AURKA, the expression of which also exhibited differential prognostic value between chemotherapy-treated and untreated cases in our analysis of microarray data. Based on previously published information, we propose that the eQTL genes may be connected to the rs6500843 locus via a RBFOX1-FOXM1 -mediated regulatory pathway.

Inherited variants in the inner centromere protein (INCENP) gene of the chromosomal passenger complex contribute to the susceptibility of ER-negative breast cancer.

The chromosomal passenger complex (CPC) plays a pivotal role in the regulation of cell division. Therefore, inherited CPC variability could influence tumor development. The present candidate gene approach investigates the relationship between single nucleotide polymorphisms (SNPs) in genes encoding key CPC components and breast cancer risk. Fifteen SNPs in four CPC genes (INCENP, AURKB, BIRC5 and CDCA8) were genotyped in 88 911 European women from 39 case-control studies of the Breast Cancer Association Consortium. Possible associations were investigated in fixed-effects meta-analyses. The synonymous SNP rs1675126 in exon 7 of INCENP was associated with overall breast cancer risk [per A allele odds ratio (OR) 0.95, 95% confidence interval (CI) 0.92-0.98, P = 0.007] and particularly with estrogen receptor (ER)-negative breast tumors (per A allele OR 0.89, 95% CI 0.83-0.95, P = 0.0005). SNPs not directly genotyped were imputed based on 1000 Genomes. The SNPs rs1047739 in the 3' untranslated region and rs144045115 downstream of INCENP showed the strongest association signals for overall (per T allele OR 1.03, 95% CI 1.00-1.06, P = 0.0009) and ER-negative breast cancer risk (per A allele OR 1.06, 95% CI 1.02-1.10, P = 0.0002). Two genotyped SNPs in BIRC5 were associated with familial breast cancer risk (top SNP rs2071214: per G allele OR 1.12, 95% CI 1.04-1.21, P = 0.002). The data suggest that INCENP in the CPC pathway contributes to ER-negative breast cancer susceptibility in the European population. In spite of a modest contribution of CPC-inherited variants to the total burden of sporadic and familial breast cancer, their potential as novel targets for breast cancer treatment should be further investigated.

Tailored selection of study individuals to be sequenced in order to improve the accuracy of genotype imputation.

The addition of sequence data from own-study individuals to genotypes from external data repositories, for example, the HapMap, has been shown to improve the accuracy of imputed genotypes. Early approaches for reference panel selection favored individuals who best reflect recombination patterns in the study population. By contrast, a maximization of genetic diversity in the reference panel has been recently proposed. We investigate here a novel strategy to select individuals for sequencing that relies on the characterization of the ancestral kernel of the study population. The simulated study scenarios consisted of several combinations of subpopulations from HapMap. HapMap individuals who did not belong to the study population constituted an external reference panel which was complemented with the sequences of study individuals selected according to different strategies. In addition to a random choice, individuals with the largest statistical depth according to the first genetic principal components were selected. In all simulated scenarios the integration of sequences from own-study individuals increased imputation accuracy. The selection of individuals based on the statistical depth resulted in the highest imputation accuracy for European and Asian study scenarios, whereas random selection performed best for an African-study scenario. Present findings indicate that there is no universal 'best strategy' to select individuals for sequencing. We propose to use the methodology described in the manuscript to assess the advantage of focusing on the ancestral kernel under own study characteristics (study size, genetic diversity, availability and properties of external reference panels, frequency of imputed variants…).

Practical investigation of the performance of robust logistic regression to predict the genetic risk of hypertension.

Logistic regression is usually applied to investigate the association between inherited genetic variants and a binary disease phenotype. A limitation of standard methods used to estimate the parameters of logistic regression models is their strong dependence on a few observations deviating from the majority of the data. We used data from the Genetic Analysis Workshop 18 to explore the possible benefit of robust logistic regression to estimate the genetic risk of hypertension. The comparison between standard and robust methods relied on the influence of departing hypertension profiles (outliers) on the estimated odds ratios, areas under the receiver operating characteristic curves, and clinical net benefit. Our results confirmed that single outliers may substantially affect the estimated genotype relative risks. The ranking of variants by probability values was different in standard and in robust logistic regression. For cutoff probabilities between 0.2 and 0.6, the clinical net benefit estimated by leave-one-out cross-validation in the investigated sample was slightly larger under robust regression, but the overall area under the receiver operating characteristic curve was larger for standard logistic regression. The potential advantage of robust statistics in the context of genetic association studies should be investigated in future analyses based on real and simulated data.

Exploring the association between genetic variation in the SUMO isopeptidase gene USPL1 and breast cancer through integration of data from the population-based GENICA study and external genetic databases.

Small ubiquitin-like modifier (SUMO) proteins are covalently attached to target proteins to modify their function. SUMO conjugation participates in processes tightly linked to tumorigenesis. Recently USPL1 (ubiquitin-specific peptidase-like (1) was identified as a SUMO isopeptidase. We report here on the first exploratory study investigating the relationship between genetic variability in USPL1 and breast cancer. Three potentially functional nonsynonymous coding SNPs (rs3742303, rs17609459, rs7984952) were genotyped in 1,021 breast cancer cases and 1,015 controls from the population-based GENICA study. We took advantage of multiple genotype imputation based on HapMap and the 1000 Genomes Project data to refine the association screening in the investigated region. Public genetic databases were also used to investigate the relationship with USPL1 expression in lymphoblastoid cell lines and breast tissue. Women homozygous for the minor C allele of rs7984952 showed a lower risk of Grade 3 breast tumors compared to TT homozygotes (OR 0.50, 95% CI 0.30-0.81). Case-only analyses confirmed the association between rs7984952 and tumor grade (OR 0.60, 95% CI 0.39-0.93). Imputation results in a 238 kb region around rs7984952 based on HapMap and the 1000 Genomes Project data were similar. No imputed variant showed an association signal stronger than rs7984952. USPL1 expression in tumor breast tissue increased with the number of C alleles. The present study illustrates the contribution of multiple imputation of genotypes using public data repositories to standard genotyping laboratory. The provided information may facilitate the design of independent studies to validate the association between USPL1 rs7984952 and risk of Grade 3 breast tumors.

Randomized controlled trials: part 17 of a series on evaluation of scientific publications.

BACKGROUND: In clinical research, randomized controlled trials (RCTs) are the best way to study the safety and efficacy of new treatments. RCTs are used to answer patient-related questions and are required by governmental regulatory bodies as the basis for approval decisions. METHODS: To help readers understand and evaluate RCTs, we discuss the methods and qualitative requirements of RCTs with reference to the literature and an illustrative case study. The discussion here corresponds to expositions of the subject that can be found in many textbooks but also reflects the authors' personal experience in planning, conducting and analyzing RCTs. RESULTS: The quality of an RCT depends on an appropriate study question and study design, the prevention of systematic errors, and the use of proper analytical techniques. All of these aspects must be attended to in the planning, conductance, analysis, and reporting of RCTs. RCTs must also meet ethical and legal requirements. CONCLUSION: RCTs cannot yield reliable data unless they are planned, conducted, analyzed, and reported in ways that are methodologically sound and appropriate to the question being asked. The quality of any RCT must be critically evaluated before its relevance to patient care can be considered.