scholarly journals c212: An R Package for the Detection of Safety Signals in Clinical Trials Using Body-Systems (System Organ Classes)

2020 ◽  
Vol 5 (56) ◽  
pp. 2706
Author(s):  
Raymond Carragher ◽  
Chris Robertson
Keyword(s):  
Clinical Trials ◽  
R Package ◽  
Safety Signals ◽  
System Organ

scholarly journals idem: An R Package for Inferences in Clinical Trials with Death and Missingness

2020 ◽  
Vol 93 (12) ◽  
Author(s):  
Chenguang Wang ◽  
Elizabeth Colantuoni ◽  
Andrew Leroux ◽  
Daniel O. Scharfstein
Keyword(s):  
Clinical Trials ◽  
R Package

A Semi-Automated Term Harmonization Pipeline Applied to Pulmonary Arterial Hypertension Clinical Trials

2021 ◽  
Author(s):  
Ryan J. Urbanowicz ◽  
John H. Holmes ◽  
Dina Appleby ◽  
Vanamala Narasimhan ◽  
Stephen Durborow ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Pulmonary Arterial Hypertension ◽  
Arterial Hypertension ◽  
System Organ Class ◽  
High Level Group ◽  
Fuzzy Matching ◽  
Pulmonary Arterial ◽  
High Level ◽  
Level Group ◽  
System Organ

Abstract Objective Data harmonization is essential to integrate individual participant data from multiple sites, time periods, and trials for meta-analysis. The process of mapping terms and phrases to an ontology is complicated by typographic errors, abbreviations, truncation, and plurality. We sought to harmonize medical history (MH) and adverse events (AE) term records across 21 randomized clinical trials in pulmonary arterial hypertension and chronic thromboembolic pulmonary hypertension. Methods We developed and applied a semi-automated harmonization pipeline for use with domain-expert annotators to resolve ambiguous term mappings using exact and fuzzy matching. We summarized MH and AE term mapping success, including map quality measures, and imputation of a generalizing term hierarchy as defined by the applied Medical Dictionary for Regulatory Activities (MedDRA) ontology standard. Results Over 99.6% of both MH (N = 37,105) and AE (N = 58,170) records were successfully mapped to MedDRA low-level terms. Automated exact matching accounted for 74.9% of MH and 85.5% of AE mappings. Term recommendations from fuzzy matching in the pipeline facilitated annotator mapping of the remaining 24.9% of MH and 13.8% of AE records. Imputation of the generalized MedDRA term hierarchy was unambiguous in 85.2% of high-level terms, 99.4% of high-level group terms, and 99.5% of system organ class in MH, and 75% of high-level terms, 98.3% of high-level group terms, and 98.4% of system organ class in AE. Conclusion This pipeline dramatically reduced the burden of manual annotation for MH and AE term harmonization and could be adapted to other data integration efforts.

scholarly journals A hierarchical testing approach for detecting safety signals in clinical trials

2020 ◽  
Vol 39 (10) ◽  
pp. 1541-1557 ◽  
Author(s):  
Xianming Tan ◽  
Bingshu E. Chen ◽  
Jianping Sun ◽  
Tejendra Patel ◽  
Joseph G. Ibrahim
Keyword(s):  
Clinical Trials ◽  
Hierarchical Testing ◽  
Testing Approach ◽  
Safety Signals

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]

SAE: An R package for early stopping rules in clinical trials

2011 ◽  
Vol 104 (2) ◽  
pp. 243-248 ◽  
Author(s):  
C. Bascoul-Mollevi ◽  
A. Laplanche ◽  
M.C. Le Deley ◽  
A. Kramar
Keyword(s):  
Clinical Trials ◽  
R Package ◽  
Stopping Rules ◽  
Early Stopping

scholarly journals Visualizing adverse events in clinical trials using correspondence analysis with R-package visae

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Márcio A. Diniz ◽  
Gillian Gresham ◽  
Sungjin Kim ◽  
Michael Luu ◽  
N. Lynn Henry ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Adverse Events ◽  
Correspondence Analysis ◽  
Ductal Carcinoma ◽  
Single Agent ◽  
R Package ◽  
Two Dimensional ◽  
Loss Of Information ◽  
Essential Components ◽  
Shiny App

Abstract Background Graphical displays and data visualization are essential components of statistical analysis that can lead to improved understanding of clinical trial adverse event (AE) data. Correspondence analysis (CA) has been introduced decades ago as a multivariate technique that can communicate AE contingency tables using two-dimensional plots, while quantifying the loss of information as other dimension reduction techniques such as principal components and factor analysis. Methods We propose the application of stacked CA using contribution biplots as a tool to explore differences in AE data among treatments in clinical trials. We defined five levels of refinement for the analysis based on data derived from the Common Terminology Criteria for Adverse Events (CTCAE) grades, domains, terms and their combinations. In addition, we developed a Shiny app built in an R-package, visae, publicly available on Comprehensive R Archive Network (CRAN), to interactively investigate CA configurations based on the contribution to the explained variance and relative frequency of AEs. Data from two randomized controlled trials (RCT) were used to illustrate the proposed methods: NSABP R-04, a neoadjuvant rectal 2 × 2 factorial trial comparing radiation therapy with either capecitabine (Cape) or 5-fluorouracil (5-FU) alone with or without oxaliplatin (Oxa), and NSABP B-35, a double-blind RCT comparing tamoxifen to anastrozole in postmenopausal women with hormone-positive ductal carcinoma in situ. Results In the R04 trial (n = 1308), CA biplots displayed the discrepancies between single agent treatments and their combinations with Oxa at all levels of AE classes, such that these discrepancies were responsible for the largest portion of the explained variability among treatments. In addition, an interaction effect when adding Oxa to Cape/5-FU was identified when the distance between Cape+Oxa and 5-FU + Oxa was observed to be larger than the distance between 5-FU and Cape, with Cape+Oxa and 5-FU + Oxa in different quadrants of the CA biplots. In the B35 trial (n = 3009), CA biplots showed different patterns for non-adherent Anastrozole and Tamoxifen compared with their adherent counterparts. Conclusion CA with contribution biplot is an effective tool that can be used to summarize AE data in a two-dimensional display while minimizing the loss of information and interpretation.

scholarly journals dfpk: An R-package for Bayesian dose-finding designs using pharmacokinetics (PK) for phase I clinical trials

2018 ◽  
Vol 157 ◽  
pp. 163-177 ◽  
Author(s):  
A. Toumazi ◽  
E. Comets ◽  
C. Alberti ◽  
T. Friede ◽  
F. Lentz ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Phase I ◽  
R Package ◽  
Dose Finding ◽  
Phase I Clinical Trials

scholarly journals Worsening of Lymphopenia during Apremilast Treatment

2016 ◽  
Vol 8 (3) ◽  
pp. 319-322 ◽  
Author(s):  
Antonios G.A. Kolios ◽  
Lars E. French ◽  
Alexander A. Navarini
Keyword(s):  
Clinical Trials ◽  
Psoriatic Arthritis ◽  
Private Practice ◽  
Laboratory Tests ◽  
Oral Route ◽  
Surrogate Markers ◽  
Regular Monitoring ◽  
Term Basis ◽  
Safety Signals

Apremilast is an oral phosphodiesterase IV inhibitor recently registered for the treatment of psoriasis and psoriatic arthritis in Switzerland and other countries. Even though it offers only moderate efficacy compared to biologics, many patients prefer drugs given by the oral route. Apremilast is frequently used in private practice, as it showed no relevant safety signals in clinical trials and often, laboratory tests are omitted completely. Here we report a patient who developed acute lymphopenia and worsening of psoriasis during apremilast treatment, which resolved with discontinuation of apremilast. We suggest that at least in prospective registries, that regular monitoring of laboratory surrogate markers should be performed on a long-term basis to detect rare but potentially important safety signals.

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