Research Protocol for an Observational Health Data Analysis on the Adverse Events of Systemic Treatment in Patients with Metastatic Hormone-sensitive Prostate Cancer: Big Data Analytics Using the PIONEER Platform.

Combination therapies in metastatic hormone-sensitive prostate cancer (mHSPC), which include the addition of an androgen receptor signaling inhibitor and/or docetaxel to androgen deprivation therapy, have been a game changer in the management of this disease stage. However, these therapies come with their fair share of toxicities and side effects. The goal of this observational study is to report drug-related adverse events (AEs), which are correlated with systemic combination therapies for mHSPC. Determining the optimal treatment option requires large cohorts to estimate the tolerability and AEs of these combination therapies in "real-life" patients with mHSPC, as provided in this study. We use a network of databases that includes population-based registries, electronic health records, and insurance claims, containing the overall target population and subgroups of patients defined by unique certain characteristics, demographics, and comorbidities, to compute the incidence of common AEs associated with systemic therapies in the setting of mHSPC. These data sources are standardised using the Observational Medical Outcomes Partnership Common Data Model. We perform the descriptive statistics as well as calculate the AE incidence rate separately for each treatment group, stratified by age groups and index year. The time until the first event is estimated using the Kaplan-Meier method within each age group. In the case of episodic events, the anticipated mean cumulative counts of events are calculated. Our study will allow clinicians to tailor optimal therapies for mHSPC patients, and they will serve as a basis for comparative method studies.

Cardiovascular disease in transgender individuals.

The population of people identifying as transgender has grown rapidly in recent years, resulting in a substantive increase in individuals obtaining gender-affirming medical care to align their secondary sex characteristics with their gender identity. This has established benefits for patients including improvements in gender dysphoria and psychosocial functioning, while reducing adverse mental health outcomes. Despite these potential advantages, recent evidence has suggested that gender-affirming hormone therapy (GAHT) may increase the risk of cardiovascular disease. However, owing to a paucity of research, the mechanisms underpinning these increased risks are poorly understood. Moreover, previous research has been limited by heterogenous methodologies, being underpowered, and lacking appropriate control populations. Consequently, the need for evidence regarding cardiovascular health in LGBTQ + individuals has been recognised as a critical area for future research to facilitate better healthcare and guidance. Recent research investigating the effect of transmasculine (testosterone) GAHT on cardiovascular disease risk points to testosterone effecting the nitric oxide pathway, triggering inflammation, and promoting endothelial dysfunction. Equivalent studies focussing on transfeminine (oestrogen) GAHT are required, representing a crucial area of future research. Furthermore, when examining the effects of GAHT on the vasculature, it cannot be ignored that there are multiple factors that may increase the burden of cardiovascular disease in the transgender population. Such stressors include major psychological stress; increased adverse health behaviours, such as smoking; discrimination; and lowered socioeconomic status; all of which undoubtedly impact upon cardiovascular disease risk and offers the opportunity for intervention.

Whole blood methylome-derived features to discriminate endocrine hypertension.

BACKGROUND: Arterial hypertension represents a worldwide health burden and a major risk factor for cardiovascular morbidity and mortality. Hypertension can be primary (primary hypertension, PHT), or secondary to endocrine disorders (endocrine hypertension, EHT), such as Cushing's syndrome (CS), primary aldosteronism (PA), and pheochromocytoma/paraganglioma (PPGL). Diagnosis of EHT is currently based on hormone assays. Efficient detection remains challenging, but is crucial to properly orientate patients for diagnostic confirmation and specific treatment. More accurate biomarkers would help in the diagnostic pathway. We hypothesized that each type of endocrine hypertension could be associated with a specific blood DNA methylation signature, which could be used for disease discrimination. To identify such markers, we aimed at exploring the methylome profiles in a cohort of 255 patients with hypertension, either PHT (n = 42) or EHT (n = 213), and at identifying specific discriminating signatures using machine learning approaches. RESULTS: Unsupervised classification of samples showed discrimination of PHT from EHT. CS patients clustered separately from all other patients, whereas PA and PPGL showed an overall overlap. Global methylation was decreased in the CS group compared to PHT. Supervised comparison with PHT identified differentially methylated CpG sites for each type of endocrine hypertension, showing a diffuse genomic location. Among the most differentially methylated genes, FKBP5 was identified in the CS group. Using four different machine learning methods-Lasso (Least Absolute Shrinkage and Selection Operator), Logistic Regression, Random Forest, and Support Vector Machine-predictive models for each type of endocrine hypertension were built on training cohorts (80% of samples for each hypertension type) and estimated on validation cohorts (20% of samples for each hypertension type). Balanced accuracies ranged from 0.55 to 0.74 for predicting EHT, 0.85 to 0.95 for predicting CS, 0.66 to 0.88 for predicting PA, and 0.70 to 0.83 for predicting PPGL. CONCLUSIONS: The blood DNA methylome can discriminate endocrine hypertension, with methylation signatures for each type of endocrine disorder.

Machine learning for classification of hypertension subtypes using multi-omics: A multi-centre, retrospective, data-driven study.

BACKGROUND: Arterial hypertension is a major cardiovascular risk factor. Identification of secondary hypertension in its various forms is key to preventing and targeting treatment of cardiovascular complications. Simplified diagnostic tests are urgently required to distinguish primary and secondary hypertension to address the current underdiagnosis of the latter. METHODS: This study uses Machine Learning (ML) to classify subtypes of endocrine hypertension (EHT) in a large cohort of hypertensive patients using multidimensional omics analysis of plasma and urine samples. We measured 409 multi-omics (MOmics) features including plasma miRNAs (PmiRNA: 173), plasma catechol O-methylated metabolites (PMetas: 4), plasma steroids (PSteroids: 16), urinary steroid metabolites (USteroids: 27), and plasma small metabolites (PSmallMB: 189) in primary hypertension (PHT) patients, EHT patients with either primary aldosteronism (PA), pheochromocytoma/functional paraganglioma (PPGL) or Cushing syndrome (CS) and normotensive volunteers (NV). Biomarker discovery involved selection of disease combination, outlier handling, feature reduction, 8 ML classifiers, class balancing and consideration of different age- and sex-based scenarios. Classifications were evaluated using balanced accuracy, sensitivity, specificity, AUC, F1, and Kappa score. FINDINGS: Complete clinical and biological datasets were generated from 307 subjects (PA=113, PPGL=88, CS=41 and PHT=112). The random forest classifier provided ∼92% balanced accuracy (∼11% improvement on the best mono-omics classifier), with 96% specificity and 0.95 AUC to distinguish one of the four conditions in multi-class ALL-ALL comparisons (PPGL vs PA vs CS vs PHT) on an unseen test set, using 57 MOmics features. For discrimination of EHT (PA + PPGL + CS) vs PHT, the simple logistic classifier achieved 0.96 AUC with 90% sensitivity, and ∼86% specificity, using 37 MOmics features. One PmiRNA (hsa-miR-15a-5p) and two PSmallMB (C9 and PC ae C38:1) features were found to be most discriminating for all disease combinations. Overall, the MOmics-based classifiers were able to provide better classification performance in comparison to mono-omics classifiers. INTERPRETATION: We have developed a ML pipeline to distinguish different EHT subtypes from PHT using multi-omics data. This innovative approach to stratification is an advancement towards the development of a diagnostic tool for EHT patients, significantly increasing testing throughput and accelerating administration of appropriate treatment. FUNDING: European Union's Horizon 2020 Research and Innovation Programme under Grant Agreement No. 633983, Clinical Research Priority Program of the University of Zurich for the CRPP HYRENE (to Z.E. and F.B.), and Deutsche Forschungsgemeinschaft (CRC/Transregio 205/1).

Predicting Hypertension Subtypes with Machine Learning Using Targeted Metabolites and Their Ratios.

Hypertension is a major global health problem with high prevalence and complex associated health risks. Primary hypertension (PHT) is most common and the reasons behind primary hypertension are largely unknown. Endocrine hypertension (EHT) is another complex form of hypertension with an estimated prevalence varying from 3 to 20% depending on the population studied. It occurs due to underlying conditions associated with hormonal excess mainly related to adrenal tumours and sub-categorised: primary aldosteronism (PA), Cushing's syndrome (CS), pheochromocytoma or functional paraganglioma (PPGL). Endocrine hypertension is often misdiagnosed as primary hypertension, causing delays in treatment for the underlying condition, reduced quality of life, and costly antihypertensive treatment that is often ineffective. This study systematically used targeted metabolomics and high-throughput machine learning methods to predict the key biomarkers in classifying and distinguishing the various subtypes of endocrine and primary hypertension. The trained models successfully classified CS from PHT and EHT from PHT with 92% specificity on the test set. The most prominent targeted metabolites and metabolite ratios for hypertension identification for different disease comparisons were C18:1, C18:2, and Orn/Arg. Sex was identified as an important feature in CS vs. PHT classification.

Preanalytical Pitfalls in Untargeted Plasma Nuclear Magnetic Resonance Metabolomics of Endocrine Hypertension.

Despite considerable morbidity and mortality, numerous cases of endocrine hypertension (EHT) forms, including primary aldosteronism (PA), pheochromocytoma and functional paraganglioma (PPGL), and Cushing's syndrome (CS), remain undetected. We aimed to establish signatures for the different forms of EHT, investigate potentially confounding effects and establish unbiased disease biomarkers. Plasma samples were obtained from 13 biobanks across seven countries and analyzed using untargeted NMR metabolomics. We compared unstratified samples of 106 PHT patients to 231 EHT patients, including 104 PA, 94 PPGL and 33 CS patients. Spectra were subjected to a multivariate statistical comparison of PHT to EHT forms and the associated signatures were obtained. Three approaches were applied to investigate and correct confounding effects. Though we found signatures that could separate PHT from EHT forms, there were also key similarities with the signatures of sample center of origin and sample age. The study design restricted the applicability of the corrections employed. With the samples that were available, no biomarkers for PHT vs. EHT could be identified. The complexity of the confounding effects, evidenced by their robustness to correction approaches, highlighted the need for a consensus on how to deal with variabilities probably attributed to preanalytical factors in retrospective, multicenter metabolomics studies.

Preanalytical Considerations and Outpatient Versus Inpatient Tests of Plasma Metanephrines to Diagnose Pheochromocytoma.

CONTEXT: Sampling of blood in the supine position for diagnosis of pheochromocytoma and paraganglioma (PPGL) results in lower rates of false positives for plasma normetanephrine than seated sampling. It is unclear how inpatient vs outpatient testing and other preanalytical factors impact false positives. OBJECTIVE: We aimed to identify preanalytical precautions to minimize false-positive results for plasma metanephrines. METHODS: Impacts of different blood sampling conditions on plasma metanephrines were evaluated, including outpatient vs inpatient testing, sampling of blood in semi- vs fully recumbent positions, use of cannulae vs direct venipuncture, and differences in outside temperature. A total of 3147 patients at 10 tertiary referral centers were tested for PPGL, including 278 with and 2869 without tumors. Rates of false-positive results were analyzed. RESULTS: Outpatient rather than inpatient sampling resulted in 44% higher plasma concentrations and a 3.4-fold increase in false-positive results for normetanephrine. Low temperature, a semi-recumbent position, and direct venipuncture also resulted in significantly higher plasma concentrations and rates of false-positive results for plasma normetanephrine than alternative sampling conditions, although with less impact than outpatient sampling. Higher concentrations and rates of false-positive results for plasma normetanephrine with low compared with warm temperatures were only apparent for outpatient sampling. Preanalytical factors were without impact on plasma metanephrines in patients with PPGL. CONCLUSION: Although inpatient blood sampling is largely impractical for screening patients with suspected PPGL, other preanalytical precautions (eg, cannulae, warm testing conditions) may be useful. Inpatient sampling may be reserved for follow-up of patients with difficult to distinguish true- from false-positive results.

Polygenic risk modeling for prediction of epithelial ovarian cancer risk.

Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, "select and shrink for summary statistics" (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28-1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08-1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21-1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29-1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35-1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs.

Circulating microRNAs as Diagnostic Markers in Primary Aldosteronism.

Primary aldosteronism (PA) is a common and highly treatable condition, usually resulting from adrenocortical tumorous growth or hyperplasia. PA is currently underdiagnosed owing to its complex and protracted diagnostic procedures. A simplified biomarker-based test would be highly valuable in reducing cardiovascular morbidity and mortality. Circulating microRNAs are emerging as potential biomarkers for a number of conditions due to their stability and accessibility. PA is known to alter microRNA expression in adrenocortical tissue; if these changes or their effects are mirrored in the circulating miRNA profile, then this could be exploited by a diagnostic test. However, the reproducibility of studies to identify biomarker-circulating microRNAs has proved difficult for other conditions due to a series of technical challenges. Therefore, any studies seeking to definitively identify circulating microRNA biomarkers of PA must address this in their design. To this end, we are currently conducting the circulating microRNA arm of the ongoing ENS@T-HT study. In this review article, we present evidence to support the utility of circulating microRNAs as PA biomarkers, describe the practical challenges to this approach and, using ENS@T-HT as an example, discuss how these might be overcome.

Vertical rectus abdominis flap (VRAM) for perineal reconstruction following pelvic surgery: A systematic review.

BACKGROUND: The vertical rectus abdominis myocutaneous (VRAM) flap is an established technique employed to reconstruct pelvic and perineal defects not amenable to primary closure. The aim of this study was to systematically review the morbidity of VRAM flap reconstruction following exenterative pelvic surgery. MATERIALS AND METHODS: A systematic literature search was conducted by using Medline, EMBASE, and Cochrane databases. Abstracts of all studies published from inception to November 2019 were identified. Search terms used included 'vertical rectus abdominis myocutaneous', 'vertical rectus abdominis musculocutaneous' and 'VRAM'. Only studies that described outcomes when a VRAM flap was used during exenterative pelvic surgery were included; case reports were excluded. The primary outcome measure was VRAM flap morbidity. Secondary outcome measures included donor site morbidity and hospital length of stay. RESULTS: Sixty-five studies with a total of 1827 patients were identified and included. Perineal reconstruction was most commonly performed following abdominal perineal excision of the rectum (APER) (n = 636 and 34.8%). Median patient age at surgery ranged from 38 to 78 years. Mean perineal flap morbidity was 27%, with a complete flap loss rate of 1.8% and a perineal hernia rate of 0.2%. Mean donor site morbidity was 15%, with an abdominal dehiscence rate of 5.5% and an incisional hernia rate of 3.3%. CONCLUSIONS: While overall morbidity after VRAM flap reconstruction in pelvic visceral surgery is high; the risk of major complications remains low. These data are important when counselling patients for surgery.

Regulation of Corticosteroidogenic Genes by MicroRNAs.

The loss of normal regulation of corticosteroid secretion is important in the development of cardiovascular disease. We previously showed that microRNAs regulate the terminal stages of corticosteroid biosynthesis. Here, we assess microRNA regulation across the whole corticosteroid pathway. Knockdown of microRNA using Dicer1 siRNA in H295R adrenocortical cells increased levels of CYP11A1, CYP21A1, and CYP17A1 mRNA and the secretion of cortisol, corticosterone, 11-deoxycorticosterone, 18-hydroxycorticosterone, and aldosterone. Bioinformatic analysis of genes involved in corticosteroid biosynthesis or metabolism identified many putative microRNA-binding sites, and some were selected for further study. Manipulation of individual microRNA levels demonstrated a direct effect of miR-125a-5p and miR-125b-5p on CYP11B2 and of miR-320a-3p levels on CYP11A1 and CYP17A1 mRNA. Finally, comparison of microRNA expression profiles from human aldosterone-producing adenoma and normal adrenal tissue showed levels of various microRNAs, including miR-125a-5p to be significantly different. This study demonstrates that corticosteroidogenesis is regulated at multiple points by several microRNAs and that certain of these microRNAs are differentially expressed in tumorous adrenal tissue, which may contribute to dysregulation of corticosteroid secretion. These findings provide new insights into the regulation of corticosteroid production and have implications for understanding the pathology of disease states where abnormal hormone secretion is a feature.

MicroRNA-24 is a novel regulator of aldosterone and cortisol production in the human adrenal cortex.

Dysregulation of aldosterone or cortisol production can predispose to hypertension, as seen in aldosterone-producing adenoma, a form of primary aldosteronism. We investigated the role of microRNA (miRNA) in their production, with particular emphasis on the CYP11B1 (11ß-hydroxylase) and CYP11B2 (aldosterone synthase) genes, which produce the enzymes responsible for the final stages of cortisol and aldosterone biosynthesis, respectively. Knockdown of Dicer1, a key enzyme in miRNA maturation, significantly altered CYP11B1 and CYP11B2 expression in a human adrenocortical cell line. Screening of nondiseased human adrenal and aldosterone-producing adenoma samples yielded reproducible but distinctive miRNA expression signatures for each tissue type, with levels of certain miRNA, including microRNA-24 (miR-24), differing significantly between the 2. Bioinformatic analysis identified putative binding sites for several miRNA, including miR-24, in the 3' untranslated region of CYP11B1 and CYP11B2 mRNAs. In vitro manipulation of miR-24 confirmed its ability to modulate CYP11B1 and CYP11B2 expression, as well as cortisol and aldosterone production. This study demonstrates that Dicer-dependent miRNA, including miR-24, can post-transcriptionally regulate expression of the CYP11B1 and CYP11B2 genes. Normal adrenal tissue and aldosterone-producing adenoma differ significantly and reproducibly in their miRNA expression profiles, with miR-24 significantly downregulated in the latter. Adrenal miRNA may, therefore, be a novel and valid target for the therapeutic manipulation of corticosteroid biosynthesis.

Bile acids modulate glucocorticoid metabolism and the hypothalamic-pituitary-adrenal axis in obstructive jaundice.

BACKGROUND & AIMS: Suppression of the hypothalamic-pituitary-adrenal axis occurs in cirrhosis and cholestasis and is associated with increased concentrations of bile acids. We investigated whether this was mediated through bile acids acting to impair steroid clearance by inhibiting glucocorticoid metabolism by 5beta-reductase. METHODS: The effect of bile acids on glucocorticoid metabolism was studied in vitro in hepatic subcellular fractions and hepatoma cells, allowing quantitation of the kinetics and transcript abundance of 5beta-reductase. Metabolism was subsequently examined in vivo in rats following dietary manipulation or bile duct ligation. Finally, glucocorticoid metabolism was assessed in humans with obstructive jaundice. RESULTS: In rat hepatic cytosol, chenodeoxycholic acid competitively inhibited 5beta-reductase (K(i) 9.19+/-0.40 microM) and reduced its transcript abundance (in H4iiE cells) and promoter activity (reporter system, HepG2 cells). In Wistar rats, dietary chenodeoxycholic acid (1% w/w chow) inhibited hepatic 5beta-reductase activity, reduced urinary excretion of 3alpha,5beta-tetrahydrocorticosterone and reduced adrenal weight. Conversely, a fat-free diet suppressed bile acid levels and increased hepatic 5beta-reductase activity, supplementation of the fat-free diet with CDCA reduced 5beta-reductase activity, and urinary 3alpha,5beta-reduced corticosterone. Cholestasis in rats suppressed hepatic 5beta-reductase activity and transcript abundance. In eight women with obstructive jaundice, relative urinary excretion of 3alpha,5beta-tetrahydrocortisol was significantly lower than in healthy controls. CONCLUSION: These data suggest a novel role for bile acids in inhibiting hepatic glucocorticoid clearance, of sufficient magnitude to suppress hypothalamic-pituitary-adrenal axis activity. Elevated hepatic bile acids may account for adrenal insufficiency in liver disease.

A lifetime of aldosterone excess: long-term consequences of altered regulation of aldosterone production for cardiovascular function.

Up to 15% of patients with essential hypertension have inappropriate regulation of aldosterone; although only a minority have distinct adrenal tumors, recent evidence shows that mineralocorticoid receptor activation contributes to the age-related blood pressure rise and illustrates the importance of aldosterone in determining cardiovascular risk. Aldosterone also has a major role in progression and outcome of ischemic heart disease. These data highlight the need to understand better the regulation of aldosterone synthesis and its action. Aldosterone effects are mediated mainly through classical nuclear receptors that alter gene transcription. In classic epithelial target tissues, signaling mechanisms are relatively well defined. However, aldosterone has major effects in nonepithelial tissues that include increased synthesis of proinflammatory molecules and reactive oxygen species; it remains unclear how these effects are controlled and how receptor specificity is maintained. Variation in aldosterone production reflects interaction of genetic and environmental factors. Although the environmental factors are well understood, the genetic control of aldosterone synthesis is still the subject of debate. Aldosterone synthase (encoded by the CYP11B2 gene) controls conversion of deoxycorticosterone to aldosterone. Polymorphic variation in CYP11B2 is associated with increased risk of hypertension, but the molecular mechanism that accounts for this is not known. Altered 11beta-hydroxylase efficiency (conversion of deoxycortisol to cortisol) as a consequence of variation in the neighboring gene (CYP11B1) may be important in contributing to altered control of aldosterone synthesis, so that the risk of hypertension may reflect a digenic effect, a concept that is discussed further. There is evidence that a long-term increase in aldosterone production from early life is determined by an interaction of genetic and environmental factors, leading to the eventual phenotypes of aldosterone-associated hypertension and cardiovascular damage in middle age and beyond. The importance of aldosterone has generated interest in its therapeutic modulation. Disadvantages associated with spironolactone (altered libido, gynecomastia) have led to a search for alternative mineralocorticoid receptor antagonists. Of these, eplerenone has been shown to reduce cardiovascular risk after myocardial infarction. The benefits and disadvantages of this therapeutic approach are discussed.

The new biology of aldosterone.

Classically, aldosterone is synthesised in the adrenal zona glomerulosa and binds to specific mineralocorticoid receptors located in the cytosol of target epithelial cells. Translocation of the resulting steroid receptor complex to the cell nucleus modulates gene expression and translation of specific 'aldosterone-induced' proteins that regulate electrolyte and fluid balance. However, non-epithelial and rapid non-genomic actions of aldosterone have also been described that account for a variety of actions of aldosterone that contribute to blood pressure homeostasis. These include key actions on endothelial cells and on cardiac tissue. There is also evidence that aldosterone can be synthesised in other tissues; the most convincing evidence relates to the central nervous system. However, suggestions that aldosterone is produced in the heart remain controversial, and adrenal derived aldosterone is the principal source of circulating and locally available hormone. Recent studies have shown major therapeutic benefits of mineralocorticoid receptor antagonism in cardiac failure, which emphasise the importance of aldosterone in causing adverse cardiovascular pathophysiological effects. Additional evidence demonstrates that aldosterone levels predict development of high blood pressure in normotensive subjects, while it is now clear that increased aldosterone action contributes to hypertension and cardiovascular damage in approximately 10% of patients with established hypertension. These new findings highlight the role of aldosterone as a key cardiovascular hormone and extend our understanding of its role in determining adverse cardiovascular outcomes.

Is oral fluid analysis as accurate as urinalysis in detecting drug use in a treatment setting?

BACKGROUND: Technology for testing oral fluid (OF) for the presence of drugs is available for treatment services and is more attractive than urinalysis: its validity is not well established. AIMS: Compare the accuracy of methods of on-site testing of OF and urine. DESIGN: Comparison of the sensitivity and specificity of on-site testing of samples of OF and urine collected on the same occasion, using subsequent blind laboratory analysis of the same urine samples as the standard. SETTING: British addiction treatment service. PARTICIPANTS: 157 drug dependent persons, 89% with evidence of opiates, 73% male, and 85% aged between 20 and 35 years. MEASUREMENTS: Assessment of presence of four drugs using SYVA ETS urinalysis and Cozart Rapiscan OF Drug Test systems. Laboratory urinalysis using microplate enzyme-immunoassay technique. RESULTS: The sensitivity of OF tests and urinalysis were, respectively, for opiates 91 and 91%, methadone 91 and 94%, and benzodiazepines 6 and 72%. The specificity of OF tests and urinalysis were, respectively, for opiates 78 and 67%, methadone 90 and 95%, and benzodiazepines 95 and 96%. Amphetamine usage was rare. CONCLUSIONS: OF testing is as accurate as urinalysis in detecting the presence of opiates and methadone, and the absence of methadone and benzodiazepines.