Publications by authors named "Viswam Subeesh"

13 Publications

  • Page 1 of 1

Existence of Notoriety Bias in FDA Adverse Event Reporting System Database and Its Impact on Signal Strength.

Hosp Pharm 2021 Jun 18;56(3):152-158. Epub 2019 Oct 18.

Department of Pharmacy Practice, M. S. Ramaiah University of Applied Sciences, Bengaluru, India.

Notoriety bias is defined as "a selection bias in which a case has a greater chance of being reported if the subject is exposed to the studied factor known to cause, thought to cause, or likely to cause the event of interest." This study aimed to determine the existence of notoriety bias in the FDA Adverse Event Reporting System (FAERS) database and estimate the impact of potential notoriety bias induced by safety alerts on signal estimation using disproportionality analysis. Publicly available FAERS data were downloaded and used for analysis. Thirty-one drugs which had label change/safety alert issued by FDA from 2009 to 2013 were considered. These drugs were reviewed 4 quarters before and after the safety alert notification for the existence of notoriety bias. The impact of notoriety bias induced by safety alerts was analyzed by comparing the signal strength using reporting odds ratio (ROR) and proportional reporting ratio (PRR), 2 years before and after the safety alert. Wilcoxon signed rank test was used to determine whether there were a statistically significant difference before and after the safety alert. There was increased reporting for 11 drugs after the safety alert/label change by the FDA. The reporting of 20 drugs decreased or remained unchanged after the safety alert/label change by the FDA. Wilcoxon signed rank test showed that there is no statistically significant difference with respect to the number of reports before and after the safety alert ( = .330, Z = -0.974). Fourteen (45.16%) drugs had an increase in ROR, while 17 (54.83%) drugs had a decrease in ROR after safety alert issued by FDA ( = .953, Z = -0.059). Fourteen (45.16%) drugs had an increase in PRR, while 17 (54.83%) drugs had a decrease in PRR after safety alert issued by the FDA ( = .914, Z = -0.108). Although few FDA safety alert/warnings had a strong and immediate impact, many had no impact on reporting of AE and signal strength. This study found that overreporting due to notoriety bias does not exist in the FAERS database and the overall disproportionality in signal estimates is not altered by the safety alert.
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http://dx.doi.org/10.1177/0018578719882323DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8114300PMC
June 2021

Assessment of sleep quality and its predictors among newly diagnosed psychiatric patients.

J Basic Clin Physiol Pharmacol 2021 Apr 19. Epub 2021 Apr 19.

Department of Pharmacy Practice, Faculty of Pharmacy, M.S. Ramaiah University of Applied Sciences, Bengaluru, India.

Objectives: Poor sleep is a vital symptom observed in many psychiatric conditions and is the most neglected and underdiagnosed. The current study aims at assessment of sleep quality among psychiatric patients using the Pittsburgh Sleep Quality Index (PSQI) scale and to identify the predictors of sleep quality.

Methods: A hospital-based cross-sectional observational study conducted in the Psychiatry department with a sample size of 256 patients for six months. PSQI scale was used to assess sleep quality and multiple logistic regression was used (to identify) the predictors for poor sleep quality.

Results: The mean age of the study population was 37.95 ± 14.11 years, with 148 (58%) male study participants. 192 (75%) of the study population had poor sleep quality with respect to PSQI scale with a mean score of 9.05 ± 4.65 that was well above the expected range (0-5) suggestive of compromised quality of sleep (p=0.001). Poor sleep satisfaction, waking up after the sleep onset, anorexia, day time drowsiness and at least one completely sleepless night in the past one week of admission were identified as good predictors for poor sleep quality.

Conclusions: Our study addresses the importance of assessing sleep quality regardless of the psychiatric conditions. We recommend screening patients if they have Poor sleep satisfaction, waking up after the sleep onset, anorexia, day time drowsiness or at least one completely sleepless night in the past one week of admission predictors for comorbid sleep disorders.
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http://dx.doi.org/10.1515/jbcpp-2020-0319DOI Listing
April 2021

Finding Early Improvement Threshold to Predict Response After 8 Weeks of Treatment Using Risperidone in First-Episode Psychosis.

J Clin Psychopharmacol 2021 Jan/Feb 01;41(1):58-61

A Unit of Clinical Pharmacology, Department of Biomedical and Clinical Sciences L. Sacco, "Luigi Sacco" University Hospital, Università Di Milano, Milan, Italy.

Purpose/background: The study aims to assess whether the early response can predict the outcome at the endpoint for the treatment of first-episode psychosis with risperidone and identify the relationship between initial symptom reduction and late response.

Methods/procedures: A prospective observational study with 4 points follow-up (weeks 2, 3, 4, and 8) was conducted in 48 adult first-episode psychosis patients. Symptoms were quantified by the Positive and Negative Syndrome Scale (PANSS) score. The initial recommended dose was 2 mg of risperidone once daily before sleep. The PANSS score on day 1 (before initiation of drug therapy) was considered as the baseline score. Treatment responses were considered as a reduction of more than 20%, 25%, 30% and 50% from the baseline score on first, second, third, and final follow-up, respectively. Receiver operating characteristic curves were generated for predicting response at the endpoint.

Findings/results: Thirty-one (65%) patients achieved more than 50% reduction (responders) in PANSS score. The mean total PANSS score of the study population after 8 weeks of therapy was found to be 49.77 (95% confidence interval, 46.10-53.43). The mean percentage reduction in PANSS score after 8 weeks of therapy was found to be 52.92% (95% confidence interval, 48.83-57.01). Week 2 response can be taken as the early response (area under the curve = 81.9, P < 0.001). However, the more accurate prediction was possible with week 4 response (area under the curve = 88.7%, P < 0.001).

Implications/conclusions: Our study suggests that patients with an early response at week 2 are likely to achieve positive response after 8 weeks.
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http://dx.doi.org/10.1097/JCP.0000000000001331DOI Listing
December 2020

Evaluation of prescribing practices and drug-related problems in chronic kidney disease patients: A cross-sectional study.

Perspect Clin Res 2020 Apr-Jun;11(2):70-74. Epub 2020 May 6.

Department of Pharmacy Practice, Faculty of Pharmacy, M. S. Ramaiah University of Applied Sciences, Bengaluru, Karnataka, India.

Aim: The primary intent of the study is to analyze the prescribing pattern and to identify the various drug-related problems (DRPs) associated with the therapy in chronic kidney disease (CKD) patients.

Subjects And Methods: A prospective observational study was conducted in 160 patients diagnosed with any stages of CKD. The prescribing pattern was studied and DRPs were identified, reported, and categorized as per the Pharmaceutical Care Network Europe classification V 5.01. The association between categorical variables was analyzed using the Chi-square test. The predictors of DRPs were identified using binary logistic regression analysis.

Results: The mean age of the study population was 50.08 ± 15.32 years with male predominance (71%). The average number of drugs per prescription was found to be 9.16 ± 3.01. The most prescribed drug category was antihypertensives and the most commonly prescribed drugs were diuretics. A total of 337 DRPs were identified, out of which the most common DRP was drug interactions (60%), followed by frequency errors (11.6%). Logistic regression analysis identified comorbidities more than three (odds ratio 2.09), antihypertensives more than two (odds ratio 1.9), alcoholism (odds ratio 1.5), and polypharmacy (odds ratio 1.2) as the predictors of DRPs even though they were not statistically significant at = 0.01.

Conclusion: DRPs increase the risk of deterioration of the disease state and increase the length of hospital stay. Identification and resolving of the DRPs will lead to better patient care and proper treatment. Early identification and modification of the above-mentioned predictors could possibly prevent/reduce DRPs.
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http://dx.doi.org/10.4103/picr.PICR_110_18DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7342333PMC
May 2020

Vemurafenib Induced Drug Reaction with Eosinophilia and Systemic Symptoms (DRESS): A Disproportionality Analysis in FAERS Database.

Curr Clin Pharmacol 2020 Jun 28. Epub 2020 Jun 28.

Department of Pharmacy Practice, Faculty of Pharmacy, M S Ramaiah University of Applied Sciences, Bengaluru. India.

Background: Signal strength for any drug event combination can be determined using disproportionality analysis. Vemurafenib is a BRAF inhibitor approved by the US Food and Drug Administration (FDA) in 2011 for the treatment of metastatic melanoma. This study aims to identify the signal strength of Drug Reaction with Eosinophilia and Systemic Symptoms (DRESS) associated with vemurafenib using disproportionality analysis in FDA database of Adverse Event Reporting System (FAERS).

Methods: Data were obtained from the public release of data in FAERS. Case/non-case method was adopted for the analysis of association between vemurafenib use and DRESS. The data mining algorithm used for the analysis was Reporting Odds Ratio (ROR) and Proportional Reporting Ratio (PRR). A value of ROR-1.96SE>1, PRR≥2 were considered as positive signal strength.

Results: A total of 7,171 reports for DRESS have been reported in the FDA database. Amongst which 125 reports were associated with vemurafenib. A cumulative ROR of 17.72 (95% CI 14.83; 21.18) and PRR of 17.46 (95% CI 14.65; 20.81) were observed. Combination treatment of vemurafenib with cobimetinib had higher number of reports (100) with ROR of 103.42 (84.13- 127.14) and PRR of 94.52 (78.26- 114.15). Four deaths were reported and the non-death serious reports included hospitalization, life-threatening, disability, and other serious events with 61, 11, 2 and 39 reports respectively.

Conclusion: Positive signal strength was observed for vemurafenib associated DRESS. The signal strength was higher for vemurafenib in combination with cobimetinib than vemurafenib alone. Health care professionals should be cautious about encountering serious adverse events and should be reported to the regulatory authorities.
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http://dx.doi.org/10.2174/1574884715666200628113508DOI Listing
June 2020

Early prediction of clinical response in first episode schizophrenia (FES) patients receiving olanzapine.

Int J Psychiatry Clin Pract 2020 Sep 27;24(3):309-314. Epub 2020 Apr 27.

Department of Pharmacy Practice, Faculty of Pharmacy, M S Ramaiah University of Applied Sciences, Bengaluru, India.

At present, schizophrenia guidelines recommend waiting for 8 weeks before considering a patient as non-responder. This study aims to detect the optimal early response threshold that best predict the final outcome of olanzapine. The study was conducted for 8-week, four points follow up (week 2,3,4, and 8) prospective observational study. A reduction of 20, 25, 30% in Positive and Negative Syndrome Scale (PANSS) score from the base line at week 2,3, and 4 respectively were considered as early response. A reduction of 50% at week 8 was considered as responders. Receiver Operating Characteristics (ROC) curves were performed to detect the optimal threshold. Mean total baseline PANSS score was 106.66(95% CI; 100.4, 112.9). Week 2 (AUC = 50.5%,  > 0.964) and week 3 (AUC = 64.9,  > 0.13) responses failed to predict the 8th week response. Week 4 response (AUC = 92%,  < 0.001) can be taken for the prediction of 8th week response (specificity = 72%, sensitivity = 100%, Positive Predictive Value = 61.1%, Negative Predictive Value = 100% and Optimum Early Response (OER) = 29.4%). 25 patients (69%) achieved more than 50% reduction (responders) in PANSS score after 8 weeks of treatment. Our study suggests that patients with early response at week 4 are likely to achieve positive response after 8 weeks. This may help in appropriate clinical decision making for early non-responders.Key PointsThe early response can forecast the outcome at the endpoint for the treatment of FESA reduction of baseline PANSS score by 30% or more after four weeks are likely to have remission after week 8 with olanzapine therapy.
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http://dx.doi.org/10.1080/13651501.2020.1757118DOI Listing
September 2020

Aromatase inhibitors associated osteonecrosis of jaw: signal refining to identify pseudo safety signals.

Int J Clin Pharm 2020 Apr 8;42(2):721-727. Epub 2020 Apr 8.

Department of Pharmacy Practice, Faculty of Pharmacy, M S Ramaiah University of Applied Sciences, New BEL Road, Bengaluru, 560054, Karnataka, India.

Background Signal generation through data mining algorithms is an innovative and emerging field in pharmacovigilance. Early detection of safety signals is important for public health safety. However, the possibility of generating pseudo signals should not be overlooked. Objective Our study aimed to identify potential signals of aromatase inhibitors associated Osteonecrosis of Jaw and assess the possibilities of the safety signal to be a pseudo signal/false positive in FDA Adverse Event Reporting System (FAERS). Setting Spontaneously reported data in FAERS database. Methods Data for this study were obtained from the public release of data in FAERS. OpenVigil, a pharmacovigilance analytical tool was used to access FAERS data. Reporting Odds Ratio (ROR) was used to assess the relation between the drug and adverse event. A value of ROR-1.96SE  > 1, (SE-standard error) was considered positive. Main outcome measure Signal strength. Results FAERS database had a total of 15,178 reports for Osteonecrosis of Jaw. Amongst which 617 reports were associated with aromatase inhibitors. Signal strength ROR (lower bound of the 95% CI) for letrozole, anastrozole and exemestane associated Osteonecrosis of Jaw without any background correction was 8.34, 6.64 and 15.14 respectively. Upon removing the reports of concomitantly administered drugs (bisphosphonates and denosumab), signal strength drastically decreased to 0.03, 0.36 and 0.47 for letrozole, anastrozole and exemestane respectively. The signal strength of bisphosphonates and denosumab associated Osteonecrosis of Jaw was not changed significantly upon removal of aromatase inhibitors. Conclusion Our study concluded that the signal generated for aromatase inhibitors associated Osteonecrosis of Jaw in FAERS database can be false positive. Careful background corrections with identification of those risk factors are imperative to exclude false positive results.
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http://dx.doi.org/10.1007/s11096-020-01018-zDOI Listing
April 2020

Postlicensure surveillance of human papillomavirus vaccine using the Vaccine Adverse Event Reporting System, 2006-2017.

Perspect Clin Res 2020 Jan-Mar;11(1):24-30. Epub 2019 Apr 26.

Department of Pharmacy Practice, Faculty of Pharmacy, M.S. Ramaiah University of Applied Sciences, Bangalore, India.

Background: The United States Food and Drug Administration (FDA) has licensed three HPV (Human papilloma virus) vaccines. The centers for disease control and prevention (CDC) and advisory committee on immunization practices (ACIP) recommends routine HPV vaccination at age 11 or 12 years. This study aimed to summarize and characterize adverse events following HPV vaccination reported to VAERS database from July 2006 to May 2017.

Methods: A systematic data mining was performed in the VAERS database for reports associated with HPV vaccine. Clinically relevant Vaccine Event Combinations (VEC) were identified in the VAERS database following HPV vaccination. A VEC was considered for analysis only if a minimum of hundred reports were present in database for the given Adverse Event (AE). The data mining algorithm used in this study was reporting odds ratio. A value of ROR-1.96SE >1 was considered as positive signal.

Results: VAERS received 49444 reports after receipt of HPV vaccine during the study period. Out of 49444, 2307 unique reactions were identified. A total of 177 death reports and 3526 non death serious reactions were reported to VAERS. ROR showed positive signals for abdominal pain, syncope, dizziness, convulsion, abortion spontaneous, alopecia, amenorrhea, anogenital warts, cervical dysplasia, anaemia, dyskinesia, migrane, blood pressure decreased, fall, head injury, loss of consciousness, pallor, presyncope, seizures.

Conclusion: The present analysis did not identify any new/unexpected safety concern and was consistent with the safety data from prelicensure trials. Further epidemiological studies are required to systematically validate the data provided by VAERS.
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http://dx.doi.org/10.4103/picr.PICR_140_18DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7034135PMC
April 2019

Deprescribing of benzodiazepines and Z-drugs amongst the psychiatric patients of a tertiary care Hospital.

Asian J Psychiatr 2019 Aug 29;44:189-194. Epub 2019 Jul 29.

Department of Community Medicine, Ramaiah Medical College, Bangalore, Karnataka, India.

Background: In current clinical practice, regardless of the clinical guidelines, BZDs and Z drugs are used beyond the period of indication, resulting in undesirable effects. This study aimed to assess feasibility of deprescribing amongst patients utilizing BZDs and Z drugs inappropriately for longer duration than the prescribed period. The study also analysed the Quality of Sleep (QoS) and Cost Savings incurred amongst deprescribed patients.

Methods: It was a prospective interventional study conducted in IP and OP settings of Psychiatry Department, Bangalore, India. Based on inclusion criteria, 109 patients were recruited for the study for a period of 7 months. Deprescribing was advised to inappropriate BZD and Z-drug users by clinical pharmacist after discussing with the prescribing psychiatrist. The patients were followed-up twice in a month after deprescribing. QoS was assessed by using Pittsburg Sleep Quality Index (PSQI) scale. The total medications cost incurred per patient/month before and after the intervention among both the groups was measured.

Results: Post-intervention, 40(30.69%) BZD users were deprescribed i.e, either dose tapered 6(5.5%), completely ceased 27(24.8%) or on si opus sit (SOS) BZDs prescription 7(6.4%). A majority of 44(40.36%) patients continued BZDs according to the algorithm. Clonazepam 35(87.5%) was the most deprescribed BZD. Deprescribing of BZDs showed an association with QoS of patients, p-value (<0.05). A statistically significant cost reduction was observed after deprescribing BZDs, (Z = 5.465, p=<0.001).

Discussion: Deprescribing BZDs was associated with decline in its usage; implementing deprescribing practice amongst the inappropriate BZD users is feasible, provides an improved QoS and an economic benefit.
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http://dx.doi.org/10.1016/j.ajp.2019.07.041DOI Listing
August 2019

Predictors of adverse drug reactions in geriatric patients: An exploratory study among cancer patients.

South Asian J Cancer 2019 Apr-Jun;8(2):130-133

Department of Pharmacy Practice, Faculty of Pharmacy, M. S. Ramaiah University of Applied Sciences, Bengaluru, Karnataka, India.

Objectives: The objective of this study was to study the predictors of adverse drug reactions (ADRs) among geriatric patients in the Department of Medical Oncology.

Methods: A hospital-based prospective observational study was carried out among 153 inpatients in the Department of Medical Oncology for 6 months. Patients above 60 years of age with a confirmed history of malignancy were included in the study. The potential risk factors for ADR were defined in relation to the patient and chemotherapeutic regimen and relationship between them was assessed by univariate and multivariate logistic regression analysis.

Results: Among 153 patients, 94 (64.43%) experienced ADRs. The mean ADR per patient was 0.88 ± 1.2. The common ADRs found were alopecia (30.18%) and diarrhea (28.68%). Risk estimates revealed that there was a significant association between smokers (odds ratio [OR] = 10.326; 95% confidence interval [CI] 2.345-45.47, = 0.001), alcoholics (OR = 10.897; 95% CI 2.479-47.902, = 0.001), increasing age (OR = 2.22; 95% CI 1.698-2.909, = 0.001), overweight (OR = 16.68; 95% CI 2.179-127.741, = 0.001), and male participants (OR = 0.143; 95% CI 0.05-0.390 = 0.001) with the development of ADRs. The risk of carboplatin (OR = 13.359; 95% CI 3.056-58.406 = 0.001) and 5-fluorouracil (OR = 1.938 95% CI 1.266-2.935 = 0.001) use and occurrence of ADRs were also found to be high.

Conclusion: The study findings showed that smoking, alcohol consumption, age more than 70 years, and overweight had a high risk for developing ADRs in geriatric patients who underwent chemotherapy. The independent risk factors identified should be targeted for preventive measures to improve anticancer agent prescription and reduce the risk of ADRs.
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http://dx.doi.org/10.4103/sajc.sajc_218_18DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6498717PMC
May 2019

Novel Adverse Events of Iloperidone: A Disproportionality Analysis in US Food and Drug Administration Adverse Event Reporting System (FAERS) Database.

Curr Drug Saf 2019 ;14(1):21-26

Department of Pharmacy Practice, Faculty of Pharmacy, M.S. Ramaiah University of Applied Sciences, Bengaluru, India.

Background: The signal is defined as "reported information on a possible causal relationship between an adverse event and a drug, of which the relationship is unknown or incompletely documented previously".

Objective: To detect novel adverse events of iloperidone by disproportionality analysis in FDA database of Adverse Event Reporting System (FAERS) using Data Mining Algorithms (DMAs).

Methodology: The US FAERS database consists of 1028 iloperidone associated Drug Event Combinations (DECs) which were reported from 2010 Q1 to 2016 Q3. We consider DECs for disproportionality analysis only if a minimum of ten reports are present in database for the given adverse event and which were not detected earlier (in clinical trials). Two data mining algorithms, namely, Reporting Odds Ratio (ROR) and Information Component (IC) were applied retrospectively in the aforementioned time period. A value of ROR-1.96SE>1 and IC- 2SD>0 were considered as the threshold for positive signal.

Results: The mean age of the patients of iloperidone associated events was found to be 44years [95% CI: 36-51], nevertheless age was not mentioned in twenty-one reports. The data mining algorithms exhibited positive signal for akathisia (ROR-1.96SE=43.15, IC-2SD=2.99), dyskinesia (21.24, 3.06), peripheral oedema (6.67,1.08), priapism (425.7,9.09) and sexual dysfunction (26.6-1.5) upon analysis as those were well above the pre-set threshold.

Conclusion: Iloperidone associated five potential signals were generated by data mining in the FDA AERS database. The result requires an integration of further clinical surveillance for the quantification and validation of possible risks for the adverse events reported of iloperidone.
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http://dx.doi.org/10.2174/1574886313666181026100000DOI Listing
May 2019

Safety Profile of Levonorgestrel: A Disproportionality Analysis of Food and Drug Administration Adverse Event Reporting System (Faers) Database.

J Reprod Infertil 2018 Jul-Sep;19(3):152-156

Department of Community Medicine, M.S. Ramaiah Medical College, Bangalore, India.

Background: Levonorgestrel is most commonly utilized as an emergency oral contraceptive. Little is known and/or studied about the adverse effects of levonorgestrel, therefore, current investigation was aimed to generate signal for unreported adverse drug reactions of levonorgestrel using disproportionality analysis in food and drug administration adverse events reporting system database.

Methods: In FDA Adverse Events Reporting System (FAERS) database, all adverse event reports for levonorgestrel between January 2006 to June 2015 were identified and disproportionality analysis was conducted for selected adverse events of levonorgestrel using Reporting Odds Ratio, Proportional Reporting Ratio and Information Component with 95% confidence interval.

Results: A disproportionality analysis was done for 15 adverse events of levonorgestrel; out of these, signal for 10 adverse events was found and among them menstruation delayed was reported maximum (1791), followed by pregnancy after post-coital contraception (942), breast tenderness (901), metrorrhagia (899), dysmenorrhea (822), menorrhagia (541), nipple disorder (141), breast enlargement (77), ectopic pregnancy (61) and premenstrual syndrome (35). Pregnancy after post-coital contraception showed the highest signal having the Information Component value of 129.2, Reporting Odds Ratio value of 6.51 and Proportional Reporting Ratio value of 6.49.

Conclusion: In this paper, ten novel AEs were identified that were disproportionately reported with the use of LNG by using data mining techniques. Although a causal relationship cannot be established, the number of cases reported suggests that there might be an association. If confirmed by epidemiologic studies, the findings from this study would have potential implications for the use of LNG and patient management in clinical practice.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6104423PMC
September 2018

Novel adverse events of vortioxetine: A disproportionality analysis in USFDA adverse event reporting system database.

Asian J Psychiatr 2017 Dec 14;30:152-156. Epub 2017 Sep 14.

Department of Pharmacy Practice, Faculty of Pharmacy, M S Ramaiah University of Applied Sciences, Bengaluru, India.

Background: Signal detection is one of the most advanced and emerging field in pharmacovigilance. It is a modern method of detecting new reaction (which can be desired or undesired) of a drug. It facilitates early adverse drug reaction detection which enables health professionals to identify adverse events that may not have been identified in pre-marketing clinical trials. Vortioxetine, the first mixed serotonergic antidepressant was initially approved by the US Food and Drug Administration (USFDA) on September 30, 2013 for the treatment of adults with Major Depressive Disorder (MDD). This study was to identify the signal strength for vortioxetine associated ADRs using data mining technique in USFDA Adverse Event Reporting System (AERS) database.

Methodology: Most commonly used three data mining algorithms, Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR) and Information Component (IC) were selected for the study and they were applied retrospectively in USFDA AERS database from 2015Q1 to 2016Q3. A value of ROR-1.96SE >1, PRR≥2, IC- 2SD>0 were considered as the positive signal.

Result: A study population of 61,22,000 were reported all over the world. Among which 3481 reactions were associated with vortioxetine which comprised of 632 unique events encompassed with 27 clinically relevant reactions. ROR, PRR and IC showed positive signal for weight loss, agitation, anger, ketoacidosis, insomnia and abnormal dreams.

Conclusion: The present study suggests that vortioxetine may result in these adverse events. Further pharmacoepidemiologic studies are necessary to confirm this conclusion and to improve the precision of the prevalence and/or the risk factors of this ADRs.
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http://dx.doi.org/10.1016/j.ajp.2017.09.005DOI Listing
December 2017