Adverse Event Processing During Clinical Trials

1999 ◽  
pp. 481-501
Author(s):  
Kenneth Michael
Keyword(s):  
Clinical Trials ◽  
Adverse Event ◽  
Event Processing

scholarly journals A Bayesian meta-analytic approach for safety signal detection in randomized clinical trials

2017 ◽  
Vol 14 (2) ◽  
pp. 192-200 ◽  
Author(s):  
Motoi Odani ◽  
Satoru Fukimbara ◽  
Tosiya Sato
Keyword(s):  
Clinical Trials ◽  
Adverse Event ◽  
Adverse Events ◽  
Hierarchical Structure ◽  
Meta Analysis ◽  
Event Data ◽  
Analysis Model ◽  
Exact Test ◽  
Adverse Event Data ◽  
Fisher’S Exact Test

Background/Aim: Meta-analyses are frequently performed on adverse event data and are primarily used for improving statistical power to detect safety signals. However, in the evaluation of drug safety for New Drug Applications, simple pooling of adverse event data from multiple clinical trials is still commonly used. We sought to propose a new Bayesian hierarchical meta-analytic approach based on consideration of a hierarchical structure of reported individual adverse event data from multiple randomized clinical trials. Methods: To develop our meta-analysis model, we extended an existing three-stage Bayesian hierarchical model by including an additional stage of the clinical trial level in the hierarchical model; this generated a four-stage Bayesian hierarchical model. We applied the proposed Bayesian meta-analysis models to published adverse event data from three premarketing randomized clinical trials of tadalafil and to a simulation study motivated by the case example to evaluate the characteristics of three alternative models. Results: Comparison of the results from the Bayesian meta-analysis model with those from Fisher’s exact test after simple pooling showed that 6 out of 10 adverse events were the same within a top 10 ranking of individual adverse events with regard to association with treatment. However, more individual adverse events were detected in the Bayesian meta-analysis model than in Fisher’s exact test under the body system “Musculoskeletal and connective tissue disorders.” Moreover, comparison of the overall trend of estimates between the Bayesian model and the standard approach (odds ratios after simple pooling methods) revealed that the posterior median odds ratios for the Bayesian model for most adverse events shrank toward values for no association. Based on the simulation results, the Bayesian meta-analysis model could balance the false detection rate and power to a better extent than Fisher’s exact test. For example, when the threshold value of the posterior probability for signal detection was set to 0.8, the false detection rate was 41% and power was 88% in the Bayesian meta-analysis model, whereas the false detection rate was 56% and power was 86% in Fisher’s exact test. Limitations: Adverse events under the same body system were not necessarily positively related when we used “system organ class” and “preferred term” in the Medical Dictionary for Regulatory Activities as a hierarchical structure of adverse events. For the Bayesian meta-analysis models to be effective, the validity of the hierarchical structure of adverse events and the grouping of adverse events are critical. Conclusion: Our proposed meta-analysis models considered trial effects to avoid confounding by trial and borrowed strength from both within and across body systems to obtain reasonable and stable estimates of an effect measure by considering a hierarchical structure of adverse events.

Analyzing inmuno-related adverse event: A real-world DATA study.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e18751-e18751
Author(s):  
Blanca Cantos ◽  
Juan Cristobal Sanchez ◽  
Beatriz Nuñez García ◽  
Miriam Mendez ◽  
Aranzazu Gonzalez del Alba ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Adverse Event ◽  
Severe Toxicity ◽  
Toxicity Profile ◽  
Real World Data ◽  
Related Adverse Event ◽  
Appropriate Treatment ◽  
Initial Stage ◽  
Practice Methods ◽  
Grade Iii

e18751 Background: In the last years, Immunotherapy (IT) has emerged as a standard treatment in an increasing number of tumors. This type of treatment has a specific toxicity profile which is clearly different from chemotherapy, known as an Immuno-related Adverse Event (AEir). We know the data from clinical trials, but little about the incidence and impact of this EAir in our clinical practice. Methods: A retrospective observational study was carried out including all patients from our institution (HUPHM in Madrid) who had received IT, either in monotherapy or in combination between January 2014 and December 2019. A total of 279 patients were included and data were collected between January and July 2020, guaranteeing a minimum 6-month follow-up after receiving the first dose of immunotherapy. The toxicities found were classified into four categories: pulmonary, digestive, endocrine and others, and have been graded according to CTCEA v.5 (Common Terminology Criteria for Adverse Event) published in November 2017 and analyzed according to drug and tumor. Results: The most frequent diagnoses in our patients were: 60% lung carcinoma, 15% melanoma, 8% kidney carcinoma, and 6% bladder carcinoma. 76% of the patients received IT as first or second line in a metastatic context, 6% in the initial stage (clinical trials) and the rest in more advanced lines of treatment (3 or more). 67% received anti-PD1 drug, 6% anti-PDL1, 4% anti-CTL4 monotherapy, 10% a combination of several IT drugs, and 14% an IT combination and chemotherapy. 45% of the total presented EAir (16% grade I, 14% grade II, 11% grade III and 4% grade IV). 1/5 of the patients had manifestations in more than one organ. The incidence of the different toxicities in our population was listed in the table below. These patients reported 8% dermatological toxicities, 6% had renal toxicity (most of them grade III or IV), only 2% had arthralgia or myalgia, and 3% asthenia. Combined IT treatment had significantly higher rates of pneumonitis, colitis, and endocrine toxicities. These differences were not observed between the monotherapy treatment and the combination of immunotherapy plus chemotherapy. Conclusions: Immunotherapy has represented an important advance in oncology, achieving long survivals in a growing group of tumors. Immunotherapy has a unique toxicity profile that is very different from chemotherapy and with which we must become familiar. Most of the adverse events are mild and if they are diagnosed early and with the appropriate treatment, maintenance of IT is possible. Severe toxicity (III-IV) means in most cases the suspension of treatment, compromising its efficacy. Therefore, we must learn to recognize these toxicities early and apply the recommended treatments as soon as possible.[Table: see text]

scholarly journals Adverse Event Burden Score—A Versatile Summary Measure for Cancer Clinical Trials

Cancers ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 3251
Author(s):  
Jennifer G. Le-Rademacher ◽  
Shauna Hillman ◽  
Elizabeth Storrick ◽  
Michelle R. Mahoney ◽  
Peter F. Thall ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Adverse Event ◽  
Treatment Cycle ◽  
Controlled Trials ◽  
Cancer Clinical Trials ◽  
Weighted Sum ◽  
Summary Measure ◽  
Double Blind ◽  
Double Blind Placebo ◽  
Over Time

This article introduces the adverse event (AE) burden score. The AE burden by treatment cycle is a weighted sum of all grades and AEs that the patient experienced in a cycle. The overall AE burden score is the total AE burden the patient experienced across all treatment cycles. AE data from two completed Alliance multi-center randomized double-blind placebo-controlled trials, with different AE profiles (NCCTG 97-24-51: 176 patients, and A091105: 83 patients), were utilized for illustration. Results of the AE burden score analyses corroborated the trials’ primary results. In 97-24-51, the overall AE burden for patients on the treatment arm was 2.2 points higher than those on the placebo arm, with a higher AE burden for patients who went off treatment early due to AE. Similarly, in A091105, the overall AE burden was 1.6 points higher on the treatment arm. On the placebo arms, the AE burden in 97-24-51 remained constant over time; and increased in later cycles in A091105, likely attributable to the increase in disease morbidity. The AE burden score enables statistical comparisons analogous to other quantitative endpoints in clinical trials, and can readily accommodate different trial settings, diseases, and treatments, with diverse AE profiles.

Dealing With a Deluge of Data: An Assessment of Adverse Event Data on North Central Cancer Treatment Group Trials

2005 ◽  
Vol 23 (36) ◽  
pp. 9275-9281 ◽  
Author(s):  
Michelle R. Mahoney ◽  
Daniel J. Sargent ◽  
Michael J. O'Connell ◽  
Richard M. Goldberg ◽  
Paul Schaefer ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Adverse Event ◽  
Patient Safety ◽  
Treatment Group ◽  
Cancer Treatment ◽  
Phase Iii ◽  
Small Subset ◽  
North Central ◽  
Normal Limits ◽  
Life Threatening

Purpose Adverse events (AEs) are monitored in clinical trials for patient safety, to satisfy reporting requirements, and develop safety profiles. Recently, much attention has been placed on the reporting of serious AEs (SAEs) that are either life threatening or lethal in clinical trials. However, SAEs comprise a small subset of all AE data collected for trials; the majority of AE data collected are routine AEs (RAEs) regarding non–life-threatening events. We assessed the utility of the RAE data collected, relative to the volume. Patients and Methods We surveyed the RAE data from 26 North Central Cancer Treatment Group coordinated trials. Results A total of 8,318 (11%) of 75,598 of RAEs required queries. Of these, 86% were protocol-required RAEs, 83% of RAEs required per protocol were within normal limits (eg, platelets) or not present, and 61% of extra AEs were mild. One fifth of RAEs were considered unlikely to be related or unrelated to treatment. Overall, 3% of events were severe, life threatening, or caused death. Only 1% of RAE data reported required expedited reporting (eg, via Adverse Event Expedited Reporting System). Results indicate that 72% of RAEs would be eliminated if only the maximum severity per patient and type were required. These results were validated in a large phase III trial. Conclusion The majority of RAEs identified, transcribed, and entered are not clinically important. Our data suggest that reducing the number of AEs monitored will affect substantially neither overall patient safety nor compromise evaluation of regimens undergoing testing. We present several considerations for such a reduction in data collection, as well as a policy that we have used to address the deluge of RAE data.

Nomograms to predict serious adverse events (SAEs) in patients (pts) enrolled in phase II clinical trials of molecularly targeted agents (MTAs)

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 6601-6601
Author(s):  
G. R. Pond ◽  
L. L. Siu ◽  
M. J. Moore ◽  
A. M. Oza ◽  
H. Hirte ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Adverse Event ◽  
Phase Ii ◽  
Statistical Significance ◽  
Characteristic Curve ◽  
External Validation ◽  
Charlson Score ◽  
Serious Adverse Events ◽  
Internal Validation ◽  
Ecog Ps

6601 Background: The likelihood of experiencing a SAE in clinical trials with a MTA is of interest for clinicians discussing treatment options. Adverse event data from clinical trials in the Princess Margaret Hospital Phase II Consortium [PMH2C] database were analyzed to address this question. Methods: All pts in the PMH2C database treated at the phase II dose level with either a MTA alone or in combination regimens since 2001 were included. Generalised estimating equations were used to construct optimal regression models predicting the increased/decreased odds of a SAE of all causalities (defined as a grade 3+ non-hematologic adverse event, or a grade 4+ hematologic adverse event) during the first cycle of treatment relative to a ‘reference’ pt. Nomograms were constructed to ease interpretation and internal validation explored using bootstrapping on trials larger than 35 pts. Results: 576 pts (median age=60, 55% male, ECOG PS 0:1:2=259:284:35) were accrued to 42 studies. In order of statistical significance, higher ECOG PS, increased LDH, decreased albumin, increased Charlson score, increased number of target lesions, not having prior radiotherapy and decreased age were predictive of increased odds of cycle 1 SAE. As an example, a 56-year old patient with ECOG 2, Charlson score=0, 5 target lesions, LDH=1.70x upper limit of normal [ULN], albumin=0.84xULN and no prior radiation would have ∼3 times increased odds of a SAE in cycle 1, compared to a 63-year old with ECOG 1, Charlson score=0, 1 target lesion, LDH=0.76xULN, albumin=0.68xULN and no prior radiation. Internal validation of the 4 largest studies indicated moderate-good accuracy (estimated area under the receiver operating characteristic curve = 0.57–0.86). Conclusions: A nomogram was produced allowing estimation of the increased odds of a SAE during cycle 1 of therapy in a phase II trial setting. Actual risk can then be further estimated by incorporating clinical judgment of risks for an average pt when given a particular MTA. This nomogram can potentially improve patient knowledge, risk estimates and the decision-making process. External validation of the model is still necessary to adequately assess model reliability. No significant financial relationships to disclose.

Evaluation of reported bone pain in patients (pts) receiving chemotherapy in pegfilgrastim clinical trials

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. 9621-9621 ◽  
Author(s):  
J. Sierra ◽  
R. Harms ◽  
M. Mo ◽  
C. L. Vogel
Keyword(s):  
Colorectal Cancer ◽  
Clinical Trials ◽  
Adverse Event ◽  
Growth Factors ◽  
Surface Area ◽  
Body Surface Area ◽  
Body Surface ◽  
Bone Pain ◽  
The Mean ◽  
Grade 3

9621 Background: Bone pain is the most commonly reported treatment-related adverse event (AE) associated with colony-stimulating growth factors. Some authors have suggested that pegfilgrastim-induced bone pain is unpredictable and refractory to analgesics (Kirshner 2007), though that impression may not be uniformly accepted. To better characterize this adverse event we evaluated bone pain across pegfilgrastim clinical trials. Methods: Completed Amgen-sponsored trials that both incorporated pegfilgrastim 6mg administered 24 hours after chemotherapy and utilized MedDRA library coding of AEs were examined. Included were 2 studies comparing pegfilgrastim with placebo (Vogel 2005, Hecht 2007) and 2 studies comparing pegfilgrastim with filgrastim (Sierra 2008, Lopez 2004). The incidence of bone pain was determined by treatment (pegfilgrastim, filgrastim, or placebo), chemotherapy (taxane-containing or not), cycle, severity, age, and body surface area (BSA). Analysis and recoding of studies with preferred AEs coded to nonMedDRA dictionaries is ongoing. Results: 1310 pts (filgrastim=67, pegfilgrastim=665, placebo=578) were analyzed. In studies comparing pegfilgrastim (n=74) and filgrastim (n==7) in pts with AML and NHL, 52% were female, and the mean (SD) age was 50 (15.1) years. Similar proportions (CI) of pts reported bone pain (24.3% [16.1, 35.7] vs 25.4% [15.5, 37.5], respectively), and grade 3/4 bone pain was reported in 3% [0.3, 9] versus 0% [-, -] of pts, respectively. Studies comparing pegfilgrastim (n=591) and placebo (n=578) pts in breast and colorectal cancer are below ( Table ). Conclusions: Bone pain of any grade was commonly reported in all 3 groups (pegfilgrastim, filgrastim, and placebo) and was marginally higher in pts receiving pegfilgrastim compared with placebo. Bone pain was most common in cycle 1. Severe bone pain was infrequently reported. Bone pain was similar in pts receiving pegfilgrastim and filgrastim. Chemotherapy (eg, taxanes) may also contribute to bone pain. [Table: see text] [Table: see text]

Reconsenting patients with cancer on clinical trials: Does added risk influence continued participation?

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. e15610-e15610
Author(s):  
A. Elegbede ◽  
A. Andrei ◽  
A. Andrei ◽  
K. D. Holen
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Adverse Event ◽  
Side Effects ◽  
Adverse Events ◽  
Study Participant ◽  
P Value ◽  
Study Participation ◽  
Grade 5 ◽  
Study Results

e15610 Background: The general policy endorsed by multiple professional societies and cooperative groups regarding patients on cancer clinical trials states that subjects should be informed of new adverse events or significant developments during study participation and re-consented to continue on study. However, no information is known as to the effect of re-consenting on a patients’ decision to continue study participation. Our research question addresses how the severity of reported risk to other study participants will impact the subjects’ decision to continue participation in a clinical trial. Methods: We surveyed 34 patients with gastrointestinal (GI) tumors all of whom were currently enrolled in a clinical trial. The survey portrayed hypothetical adverse reactions affecting another study participant ranging from Grade 1 to Grade 5 according to the National Cancer Institutes Common Terminology Criteria for Adverse Effects v. 3.0. The survey asked about subjects’ opinions of the theoretical adverse event categorized as “would not be concerned,” “would be concerned, but would continue the study,” and “would discontinue the study.” Results: Patients willingness to continue the study was highest at Grade 1 with 97% of all participants. However, willingness to continue participation progressively declined as the severity of adverse events increased such that only 44% of participants would continue participation with a reported Grade 5 adverse event. Conclusions: Among surveyed GI cancer patients, willingness to continue participation in a clinical trial declined significantly as the severity of adverse events increased from Grade 1 to Grade 3 - 5 (p-value < 0.001. This could be due to multiple factors, including the terminal nature of the patients’ cancer, the side effects of study therapy and the patients’ response to study treatment. This data could produce a reasonable adverse event grade cut-off for re-consenting patients regarding new side effects. No significant financial relationships to disclose.

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