ethionamide and Drug-Related-Side-Effects-and-Adverse-Reactions

Hypothyroidism is one of the adverse drug reactions that associated with Multidrug Resistant Tuberculosis (MDR-TB) medications. Extremely variable magnitude of hypothyroidism in MDR-TB patients has been reported from different parts of the world. However, there is no evidence that tried to estimate the pooled prevalence of hypothyroidism to confirm the rareness of hypothyroidism in MDR-TB patients on treatment. Therefore, we did a systematic review and meta-analysis to estimate the prevalence of hypothyroidism in MDR-TB patients on treatment, and to summarize the demographic and clinical characteristics of the patients.. We conducted a systematic review and meta-analysis on studies reported around the world on the prevalence of hypothyroidism in MDR-TB patients on treatment. We searched electronic databases: PubMed/Medline, EMBASE, CINAHL, Science Direct, Academic Search Complete and Google scholar for English language articles without limiting publication year. We also reviewed the bibliographies of relevant studies and conducted an electronic search for relevant conference abstracts. Eligible studies were cross-sectional and cohort studies that included at least five participants. We used a random-effects model to estimate the pooled prevalence of hypothyroidism. The registration number of this review study protocol is CRD42018109237.. We included 30 studies and pooled data on a total of 6,241 MDR-TB patients. The crude prevalence of hypothyroidism was extremely heterogeneous. The pooled prevalence of hypothyroidism in MDR-TB patients on treatment was 17.0% (95% CI: 13.0-20.0). Ethionamide and para-aminosalicylic acid (PAS) were the most frequently reported drugs that associated with the occurrence of hypothyroidism.. This review revealed that hypothyroidism is not a rare adverse drug reaction in MDR-TB patients on treatment. Ethionamide and PAS were the most frequently reported drugs that associated with the occurrence of hypothyroidism. Screening of hypothyroidism in MDR-TB patients on treatment is important while targeting patients on Ethionamide and PAS based treatment regimen.

Topics: Aminosalicylic Acid; Antitubercular Agents; Cross-Sectional Studies; Drug-Related Side Effects and Adverse Reactions; Ethionamide; Humans; Hypothyroidism; Risk Factors; Tuberculosis, Multidrug-Resistant

Isoniazid and ethionamide are important first- and second-line anti-TB drugs (FLDs and SLDs), respectively. Ethionamide is a structural analogue of isoniazid and the two drugs share other similarities, including their metabolism, therapeutic targets, hepato-toxicity patterns and drug resistance. As a result, there has always been concern about possible cross-reactivity between them.. Among 69 patients with drug rash with eosinophilia and systemic symptoms (DRESS), Stevens-Johnson syndrome (SJS) or toxic epidermal necrolysis (TEN) to FLDs, FLDs were stopped and SLDs added when the skin and laboratory parameters had settled. This was followed by sequential and additive rechallenge with FLDs. We report 25 consecutive cases that developed confirmed cutaneous adverse drug reactions (CADRs) to isoniazid or ethionamide used as FLD and SLD, respectively.. Sixty-nine participants who developed CADRs on FLDs were enrolled in the study. Twenty developed a rechallenge reaction to isoniazid and five reacted to ethionamide. Four of the 20 isoniazid cases were patch test positive, 3/20 were skin prick test positive and 13/20 reacted to oral rechallenge. All seven cases that were patch and skin prick test positive were associated with systemic reactions. Twenty of the 25 cases had DRESS and 5 had SJS/TEN. Twenty-three of the 25 cases with rechallenge reactions were HIV infected. Importantly, none of the cases that reacted to ethionamide during the rechallenge reacted to isoniazid and none who subsequently reacted to isoniazid reacted to ethionamide.. Our findings strongly suggest that the risk of cross-reactivity of isoniazid and ethionamide in DRESS syndrome and SJS/TEN is low. These findings have implications for clinical management.

Topics: Adolescent; Adult; Antitubercular Agents; Drug Interactions; Drug-Related Side Effects and Adverse Reactions; Ethionamide; Female; Humans; Isoniazid; Male; Skin Diseases; Young Adult

Programmatic management of MDR-TB using a standardized treatment regimen (STR) is being implemented under the Revised National Tuberculosis Control Programme (RNTCP) in India. This study was undertaken to analyse the outcomes of MDR-TB patients treated at the Tuberculosis Research Centre, Chennai, with the RNTCP recommended 24 months STR, under programmatic conditions.. Patients failed to the category II re-treatment regimen and confirmed to have MDR-TB, were treated with the RNTCP's STR in a prospective field trial on a predominantly ambulatory basis. Thirty eight patients were enrolled to the trial from June 2006 to September 2007.. Time to culture conversion was two months or less for 82 per cent of patients. Culture conversion rates at 3 and 6 months were 84 and 87 per cent respectively. At the end of treatment, 25 (66%) were cured, 5 defaulted, 3 died and 5 failed. At 24 months, 30 (79%) patients, including 5 defaulters, remained culture negative for more than 18 months. Twenty two (58%) patients reported adverse drug reactions (ADRs) which required dose reduction or termination of the offending drug. No patient had XDR-TB initially, but 2 failure cases emerged as XDR-TB during treatment.. Outcomes of this small group of MDR-TB patients treated with the RNTCP's STR is encouraging in this setting. Close attention needs to be paid to ensure adherence, and to the timely recognition and treatment of ADRs.

Topics: Adult; Antibiotics, Antitubercular; Communicable Disease Control; Cycloserine; Directly Observed Therapy; Drug-Related Side Effects and Adverse Reactions; Ethambutol; Ethionamide; Female; Humans; India; Kanamycin; Male; Middle Aged; Ofloxacin; Prospective Studies; Pyrazinamide; Sputum; Time Factors; Treatment Outcome; Tuberculosis, Multidrug-Resistant

Drug-induced liver injury (DILI) is a significant concern in drug development due to the poor concordance between preclinical and clinical findings of liver toxicity. We hypothesized that the DILI types (hepatotoxic side effects) seen in the clinic can be translated into the development of predictive in silico models for use in the drug discovery phase. We identified 13 hepatotoxic side effects with high accuracy for classifying marketed drugs for their DILI potential. We then developed in silico predictive models for each of these 13 side effects, which were further combined to construct a DILI prediction system (DILIps). The DILIps yielded 60-70% prediction accuracy for three independent validation sets. To enhance the confidence for identification of drugs that cause severe DILI in humans, the "Rule of Three" was developed in DILIps by using a consensus strategy based on 13 models. This gave high positive predictive value (91%) when applied to an external dataset containing 206 drugs from three independent literature datasets. Using the DILIps, we screened all the drugs in DrugBank and investigated their DILI potential in terms of protein targets and therapeutic categories through network modeling. We demonstrated that two therapeutic categories, anti-infectives for systemic use and musculoskeletal system drugs, were enriched for DILI, which is consistent with current knowledge. We also identified protein targets and pathways that are related to drugs that cause DILI by using pathway analysis and co-occurrence text mining. While marketed drugs were the focus of this study, the DILIps has a potential as an evaluation tool to screen and prioritize new drug candidates or chemicals, such as environmental chemicals, to avoid those that might cause liver toxicity. We expect that the methodology can be also applied to other drug safety endpoints, such as renal or cardiovascular toxicity.

Topics: Animals; Anti-Infective Agents; Anti-Inflammatory Agents; Chemical and Drug Induced Liver Injury; Databases, Factual; Drug-Related Side Effects and Adverse Reactions; Humans; Liver; Models, Biological; Predictive Value of Tests

The FDA's Spontaneous Reporting System (SRS) database contains over 1.5 million adverse drug reaction (ADR) reports for 8620 drugs/biologics that are listed for 1191 Coding Symbols for Thesaurus of Adverse Reaction (COSTAR) terms of adverse effects. We have linked the trade names of the drugs to 1861 generic names and retrieved molecular structures for each chemical to obtain a set of 1515 organic chemicals that are suitable for modeling with commercially available QSAR software packages. ADR report data for 631 of these compounds were extracted and pooled for the first five years that each drug was marketed. Patient exposure was estimated during this period using pharmaceutical shipping units obtained from IMS Health. Significant drug effects were identified using a Reporting Index (RI), where RI = (# ADR reports / # shipping units) x 1,000,000. MCASE/MC4PC software was used to identify the optimal conditions for defining a significant adverse effect finding. Results suggest that a significant effect in our database is characterized by > or = 4 ADR reports and > or = 20,000 shipping units during five years of marketing, and an RI > or = 4.0. Furthermore, for a test chemical to be evaluated as active it must contain a statistically significant molecular structural alert, called a decision alert, in two or more toxicologically related endpoints. We also report the use of a composite module, which pools observations from two or more toxicologically related COSTAR term endpoints to provide signal enhancement for detecting adverse effects.

Topics: Adverse Drug Reaction Reporting Systems; Artificial Intelligence; Computers; Databases, Factual; Drug Prescriptions; Drug-Related Side Effects and Adverse Reactions; Endpoint Determination; Models, Molecular; Quantitative Structure-Activity Relationship; Software; United States; United States Food and Drug Administration