Prevalence, Attributes, and Risk Factors of QT-Interval-Prolonging Drugs and Potential Drug-Drug Interactions in Cancer Patients: A Prospective Study in a Tertiary Care Hospital.

Introduction Cancer chemotherapy regimens include multiple classes of adjuvant drugs as supportive therapy. Because of the concurrent intake of other drugs (like antiemetics, antidepressants, analgesics, and antimicrobials), there is a heightened risk for possible QT interval prolongation. There is a dearth of evidence in the literature regarding the usage of QT-prolonging anticancer drugs and associated risk factors that have the propensity to prolong QT interval. The purpose was to explore the extent of the use of QT-interval-prolonging drugs and potential QT-prolonging drug-drug interactions (QT-DDIs) in cancer patients attending OPD in a tertiary-care hospital. Methods This was a hospital-based, cross-sectional, observational study. Risk stratification of QT-prolonging drugs for torsades de pointes (TdP) was done by the Arizona Center for Education and Research on Therapeutics (AzCERT)/CredibleMeds-lists, and potential QT-DDIs were determined with four online DDI-checker-software. Results In 1331 cancer patients, the overall prevalence of potential QT-prolonging drug utilization was 97.3%. Ondansetron, pantoprazole, domperidone, and olanzapine were the most frequent QT-prolonging drugs in cancer patients. The top six antineoplastics with potential QT-prolonging and torsadogenic actions were capecitabine, oxaliplatin, imatinib, bortezomib, 5-fluorouracil, and bendamustine. Evidence-based pragmatic QTc interval prolongation risk assessment tools are imperative for cancer patients. Conclusion This study revealed a high prevalence of QT-prolonging drugs and QT-DDIs among cancer patients who are treated with anticancer and non-anticancer drugs. As a result, it's critical to take precautions, stay vigilant, and avoid QT-prolonging in clinical situations. Evidence-based pragmatic QTc interval prolongation risk assessment tools are needed for cancer patients.

Leading 20 drug-drug interactions, polypharmacy, and analysis of the nature of risk factors due to QT interval prolonging drug use and potentially inappropriate psychotropic use in elderly psychiatry outpatients.

BACKGROUND: Psychotropic medications extend corrected QT (QTc) period in the electrocardiogram (ECG). Psychiatric patients exposed to ⩾1 psychotropic medication(s) represent a group with marked probability of drug-activated QTc-prolongation. Prolonged QTc interval in elderly patients (age > 60 years) is connected to greater risk of all-cause and coronary heart disease deaths. This study aimed at investigating pattern of utilization of QTc-interval protracting medications, QT-extending drug interactions, and prevalence of QTc-interval extending hazard factors in elderly patients. METHODS: This was a cross-sectional, prospective study at the Psychiatry OPD at All India Institute of Medical Sciences (AIIMS), Rishikesh, Uttarakhand, India from 1 October 2017 to 30 August 2019 employing the pertinent prescriptions. RESULTS: A total of 832 elderly patients (age 60 years or more) visiting the Psychiatry OPD during the aforementioned study duration were investigated. About 420 (50.5%) patients were males while 412 (49.5%) were females. Of the 832 patients, 588 (70.7%) were using interacting agents with capacity to produce TdP. Almost 1152 interacting torsadogenic medication pairs were unraveled. As per AzCERT/CredibleMeds Classification, 1016 (48.8%), 724 (34.8%), and 248 (12%) agents with potential to interact were identified with 'known', 'possible', and 'conditional risk of TdP', respectively. The common interacting medications belonged to antidepressant (288), proton pump inhibitor (364), antipsychotic (340), antinausea (184), antimicrobial (156), and H2 receptor antagonist (60) therapeutic categories. The all-inclusive frequency of potentially inappropriate psychotropic (PIP) agents administered was 62% (1343/2166) with Beers Criteria 2019, and 46% (997/2166) with STOPP Criteria 2015. CONCLUSION: Many geriatric patients were administered drugs and drug combinations with heightened proclivity toward QT-interval prolongation. Furthermore, reliable evidence-based online drug knowledge resources, such as AzCERT/CredibleMeds Drug Lists, Medscape Drug Interactions Checker, Epocrates Online Interaction Check, and Drugs.com Drug Interactions Checker, can facilitate clinical professionals in selecting drugs for psychiatric patients. A wise choice of medications is imperative to preclude serious adverse sequelae. Therefore, we need to exigently embrace precautionary safety means, be vigilant, and forestall QT-extension and TdP in clinical environments.

Promise of the NLRP3 Inflammasome Inhibitors in In Vivo Disease Models.

Nucleotide-binding oligomerization domain NOD-like receptors (NLRs) are conserved cytosolic pattern recognition receptors (PRRs) that track the intracellular milieu for the existence of infection, disease-causing microbes, as well as metabolic distresses. The NLRP3 inflammasome agglomerates are consequent to sensing a wide spectrum of pathogen-associated molecular patterns (PAMPs) and danger-associated molecular patterns (DAMPs). Certain members of the NLR family have been documented to lump into multimolecular conglomerates called inflammasomes, which are inherently linked to stimulation of the cysteine protease caspase-1. Following activation, caspase-1 severs the proinflammatory cytokines interleukin (IL)-1ß and IL-18 to their biologically active forms, with consequent commencement of caspase-1-associated pyroptosis. This type of cell death by pyroptosis epitomizes a leading pathway of inflammation. Accumulating scientific documentation has recorded overstimulation of NLRP3 (NOD-like receptor protein 3) inflammasome involvement in a wide array of inflammatory conditions. IL-1ß is an archetypic inflammatory cytokine implicated in multiple types of inflammatory maladies. Approaches to impede IL-1ß's actions are possible, and their therapeutic effects have been clinically demonstrated; nevertheless, such strategies are associated with certain constraints. For instance, treatments that focus on systemically negating IL-1ß (i.e., anakinra, rilonacept, and canakinumab) have been reported to result in an escalated peril of infections. Therefore, given the therapeutic promise of an NLRP3 inhibitor, the concerted escalated venture of the scientific sorority in the advancement of small molecules focusing on direct NLRP3 inflammasome inhibition is quite predictable.

Prevalence, severity, and nature of risk factors associated with drug-drug interactions in geriatric patients receiving cancer chemotherapy: A prospective study in a tertiary care teaching hospital.

INTRODUCTION: Polypharmacy increases hazard of drug-drug interactions(DDIs), hospitalization, treatment toxicity, and mortality in elderly individuals with cancer. The present study explores and analyzes prevalence and severity of DDIs in geriatric cancer patients subjected to anticancer chemotherapy, their mechanisms, stratification of severity, and correlation between DDI risk and number of medications taken. METHODS: This was a cross-sectional study conducted between January-July 2019 at the Medical Oncology/Hematology and Radiation-Oncology Departments, All India Institute of Medical Sciences(AIIMS) Rishikesh. The study included a convenience sampling of 126 geriatric cancer patients. RESULTS: 126 patients were enrolled in present study. DDIs were identified in 97.6% of elderly cancer patients, and 88.9% had at least one DDI with antineoplastic medications. Highest number of DDIs involving antineoplastic medications in any given patient was 12. DDIs involving medications used for treatment of non-cancerous diseases were observed in 83.3% of patients; highest number of interactions identified in any given patient was 15. Out of 473 interactions, 237(50.1%) DDIs were attributable to pharmacodynamic mechanisms of action. 126(27%) of DDIs involved pharmacokinetic mechanisms and 110(23.6%) involved unknown mechanisms. In this present study, total number of DDIs could be positively correlated with total number of medications and number of health problems. CONCLUSIONS: Geriatric cancer patients are at high risk of DDIs ascribable to polypharmacy. Physicians may utilize online DDI checking softwares to alert themselves, characterize potential DDIs, and modify medications judiciously. An integrative and algorithmic approach with inclusion of geriatricians, oncologists, cardiologists, general practitioners, and clinical pharmacologists/ pharmacists is imperative to optimize drug therapy.