Drug safety profiling for assessment of drug combinations in oncology

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 15037-15037
Author(s):  
S. N. Voss ◽  
A. Czarnecki
Keyword(s):  
Ovarian Cancer ◽  
Drug Safety ◽  
Gastrointestinal Disorders ◽  
Safety Database ◽  
New Drug ◽  
Combination Treatments ◽  
Potential Safety ◽  
Drug Regimens ◽  
Safety Signals ◽  
System Organ

15037 Background: It is important to understand the safety profile (SP)/toxicity of new drug regimens in oncology. We compared SPs of gemcitabine (Gem) + carboplatin (Carbo) in NSCLC with Gem alone and in different combinations and also tested the methodology of drug safety profiling (DSP). Methods: Spontaneous cases for the period of 1995–2005 were reviewed on the Lilly Safety Database (LSD). DSP was used to evaluate differences in the SPs of several combinations: Gem+Carbo in NSCLC, Gem+Carbo in ovarian cancer, Gem+ cisplatin (Cis) in NSCLC, Gem+Carbo in all indications, and Gem regardless of treatment regimen, for all indications. Frequencies of adverse events (AEs) for all MedDRA System Organ Classes (SOCs) were used for each regimen. In addition, the MedDRA Preferred Terms (PTs) were reviewed to detect potential safety signals. The numbers of AEs in different SOCs were assessed as proportions of the total reports for the Gem combinations in the LSD. Results: With the exception of the Investigations SOC, the proportions of AEs for patients treated for NSCLC with Gem+Carbo were consistent with those for patients treated for NSCLC with Gem+Cis and with Gem for all indications. However, the frequency in the Investigations SOC was consistent with that reported for Gem+Carbo in all indications (14.2% v. 12.0%). A greater frequency of AEs was seen in the Gastrointestinal Disorders SOC for patients treated with Gem+Carbo for ovarian cancer compared to patients treated with Gem+Carbo for NSCLC. The review of individual PTs for Gem+Carbo did not reveal any safety signals. Conclusions: The SP of Gem+Carbo in NSCLC using DSP showed similar patterns to all other Gem combinations with only some differences due to the indication. DSP is a useful tool in assessing the new drug combination treatments in existing or new indications. [Table: see text]

Applying quantitative methods for detecting new drug safety signals in pharmacovigilance national database

2007 ◽  
Vol 16 (10) ◽  
pp. 1136-1140 ◽  
Author(s):  
Gloria Shalviri ◽  
Kazem Mohammad ◽  
Reza Majdzadeh ◽  
Kheirollah Gholami
Keyword(s):  
Drug Safety ◽  
Quantitative Methods ◽  
National Database ◽  
New Drug ◽  
Safety Signals

scholarly journals Assessing an ASCO Decision Aid for Improving the Accuracy and Attribution of Serious Adverse Event Reporting From Investigators to Sponsors

2019 ◽  
Vol 15 (12) ◽  
pp. e1050-e1065 ◽  
Author(s):  
Kathryn F. Mileham ◽  
Caroline Schenkel ◽  
Meredith K. Chuk ◽  
Andrea Buchmeier ◽  
Raymond P. Perez ◽  
...  
Keyword(s):  
Adverse Event ◽  
Case Studies ◽  
Drug Safety ◽  
Decision Aid ◽  
Small Sample ◽  
Research Staff ◽  
Convenience Sample ◽  
New Drug ◽  
Safety Signals

PURPOSE: Investigators often send reports to sponsors that incorrectly categorize adverse event (AE)s as serious or attribute AEs to investigational drugs. Such errors can contribute to high volumes of uninformative investigational new drug safety reports that sponsors submit to the US Food and Drug Administration and participating investigators, which strain resources and impede the detection of valid safety signals. To improve the quality of serious AE (SAE) reporting by physician-investigators and research staff, ASCO developed and tested a Decision Aid. METHODS: A preliminary study with crossover design was conducted in a convenience sample. Physician-investigators and research staff were randomly assigned to receive case studies. Case studies were assessed for seriousness and attribution, first unassisted and then with the Decision Aid. Participants completed a feedback survey about the Decision Aid. Effectiveness of reporting and attribution are reported as odds ratios (ORs) with 95% CI. Power to detect associations was limited because of a small sample size. RESULTS: The Decision Aid did not significantly affect accuracy of determining seriousness (OR, 0.87; 95% CI, 0.31 to 2.46), but it did significantly increase accuracy of attributing an SAE to a drug (OR, 3.60; 95% CI, 1.15 to 11.4). Most of the 29 participants reported that the Decision Aid was helpful (93%) and improved decision-making time (69%) and confidence in reporting (83%), and that they would use the Decision Aid in practice (83%). CONCLUSION: The Decision Aid shows promise as a method to improve the quality of SAE attribution, which may improve the detection of valid safety signals and reduce the administrative burden of uninformative investigational new drug safety reports. Study of the Decision Aid in a larger sample with analysis stratified by participant role and SAE reporting experience would further assess the tool’s impact.

scholarly journals Safety Profile of Ibrutinib: An Analysis of the WHO Pharmacovigilance Database

2021 ◽  
Vol 12 ◽  
Author(s):  
Marion Allouchery ◽  
Cécile Tomowiak ◽  
Thomas Lombard ◽  
Marie-Christine Pérault-Pochat ◽  
Francesco Salvo
Keyword(s):  
Safety Profile ◽  
Large Scale ◽  
Reference Group ◽  
Heart Diseases ◽  
Proportional Reporting Ratio ◽  
World Health ◽  
Safety Database ◽  
Potential Safety ◽  
Pharmacovigilance Database ◽  
Safety Signals

As ibrutinib has become a standard of care in B-cell malignancies in monotherapy or in combination with other agents, definition of its safety profile appears essential. The aim of this study was to further characterize the safety profile of ibrutinib through the identification of potential safety signals in a large-scale pharmacovigilance database. All serious individual case safety reports (ICSRs) in patients aged ≥18 years involving ibrutinib suspected in the occurrence of serious adverse drug reactions or drug interacting from November 13th, 2013 to December 31st, 2020 were extracted from VigiBase, the World Health Organization global safety database. Disproportionality reporting was assessed using the information component (IC) and the proportional reporting ratio (PRR), with all other anticancer drugs used as the reference group. To mitigate the confounding of age, two subgroups were considered: patients aged<75 years and ≥75 years. A signal of disproportionate reporting (SDR) was defined if both IC and PRR were significant. A total of 16,196 ICSRs were included. The median age of patients was 72.9 years, 42.6% of ICSRs concerned patients aged ≥75 years, and 64.2% male patients. More than half (56.2%) of ICSRs resulted in hospitalization or prolonged hospitalization. Among 713 SDRs, 36 potential safety signals emerged in ibrutinib-treated patients, mainly ischemic heart diseases, pericarditis, uveitis, retinal disorders and fractures. All potential safety signals having arisen in this analysis may support patient care and monitoring of ongoing clinical trials. However, owing to the mandatory limitations of this study, our results need further confirmation using population-based studies.

FDA's New Drug Safety Board Under Scrutiny

2005 ◽  
Vol 39 (3) ◽  
pp. 51
Author(s):  
JENNIFER SILVERMAN
Keyword(s):  
Drug Safety ◽  
New Drug

Re-using Mini-Sentinel data following rapid assessments of potential safety signals via modular analytic programs

2013 ◽  
Vol 22 (10) ◽  
pp. 1036-1045 ◽  
Author(s):  
Sengwee Toh ◽  
Jerry Avorn ◽  
Ralph B. D'Agostino ◽  
Jerry H. Gurwitz ◽  
Bruce M. Psaty ◽  
...  
Keyword(s):  
Potential Safety ◽  
Safety Signals

scholarly journals Two-stage Bayesian hierarchical modeling for blinded and unblinded safety monitoring in randomized clinical trials

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Junhao Liu ◽  
Jo Wick ◽  
Renee’ H. Martin ◽  
Caitlyn Meinzer ◽  
Dooti Roy ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Drug Safety ◽  
Safety Data ◽  
Safety Monitoring ◽  
Safety Signal ◽  
Two Stage ◽  
Bayesian Hierarchical ◽  
Potential Safety ◽  
Stage 1

Abstract Background Monitoring and reporting of drug safety during a clinical trial is essential to its success. More recent attention to drug safety has encouraged statistical methods development for monitoring and detecting potential safety signals. This paper investigates the potential impact of the process of the blinded investigator identifying a potential safety signal, which should be further investigated by the Data and Safety Monitoring Board with an unblinded safety data analysis. Methods In this paper, two-stage Bayesian hierarchical models are proposed for safety signal detection following a pre-specified set of interim analyses that are applied to efficacy. At stage 1, a hierarchical blinded model uses blinded safety data to detect a potential safety signal and at stage 2, a hierarchical logistic model is applied to confirm the signal with unblinded safety data. Results Any interim safety monitoring analysis is usually scheduled via negotiation between the trial sponsor and the Data and Safety Monitoring Board. The proposed safety monitoring process starts once 53 subjects have been enrolled into an eight-arm phase II clinical trial for the first interim analysis. Operating characteristics describing the performance of this proposed workflow are investigated using simulations based on the different scenarios. Conclusions The two-stage Bayesian safety procedure in this paper provides a statistical view to monitor safety during the clinical trials. The proposed two-stage monitoring model has an excellent accuracy of detecting and flagging a potential safety signal at stage 1, and with the most important feature that further action at stage 2 could confirm the safety issue.

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