A taxonomic schema of potential pitfalls in clinical variant analysis based on real-world evidence.
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ABSTRACT:
SUBMITTER: Coovadia A
PROVIDER: S-EPMC10688707 | biostudies-literature | 2023
REPOSITORIES: biostudies-literature
Publications
A taxonomic schema of potential pitfalls in clinical variant analysis based on real-world evidence.
Coovadia Adam A Boccuto Luigi L Chang Yenui Y DeLuca Jane J
PloS one 20231130 11
The classification and interpretation of genetic variants associated with genetic diseases have been shown to vary between clinical genetic laboratories. This can lead to errors introduced in the interpretation and public presentation of genetic findings in the literature and available databases. This qualitative study utilizes real-world evidence to introduce a taxonomic schema of potential pitfalls associated with public and commercial resources commonly used for sequence variant analysis. Dat ...[more]
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Project description:ObjectiveCase-control study designs are commonly used in retrospective analyses of real-world evidence (RWE). Due to the increasingly wide availability of RWE, it can be difficult to determine whether findings are robust or the result of testing multiple hypotheses.Materials and methodsWe investigate the potential effects of modifying cohort definitions in a case-control association study between depression and type 2 diabetes mellitus. We used a large (>75 million individuals) de-identified administrative claims database to observe the effects of minor changes to the requirements of glucose and hemoglobin A1c tests in the control group.ResultsWe found that small permutations to the criteria used to define the control population result in significant shifts in both the demographic structure of the identified cohort as well as the odds ratio of association. These differences remain present when testing against age- and sex-matched controls.DiscussionAnalyses of RWE need to be carefully designed to avoid issues of multiple testing. Minor changes to control cohorts can lead to significantly different results and have the potential to alter even prospective studies through selection bias.ConclusionWe believe this work offers strong support for the need for robust guidelines, best practices, and regulations around the use of observational RWE for clinical or regulatory decision-making.
| S-EPMC8206406 | biostudies-literature
Project description:ImportanceAlthough randomized clinical trials are considered to be the criterion standard for generating clinical evidence, the use of real-world evidence to evaluate the efficacy and safety of medical interventions is gaining interest. Whether observational data can be used to address the same clinical questions being answered by traditional clinical trials is still unclear.ObjectiveTo identify the number of clinical trials published in high-impact journals in 2017 that could be feasibly replicated using observational data from insurance claims and/or electronic health records (EHRs).Design, setting, and participantsIn this cross-sectional analysis, PubMed was searched to identify all US-based clinical trials, regardless of randomization, published between January 1, 2017, and December 31, 2017, in the top 7 highest-impact general medical journals of 2017. Trials were excluded if they did not involve human participants, did not use end points that represented clinical outcomes among patients, were not characterized as clinical trials, and had no recruitment sites in the United States.Main outcomes and measuresThe primary outcomes were the number and percentage of trials for which the intervention, indication, trial inclusion and exclusion criteria, and primary end points could be ascertained from insurance claims and/or EHR data.ResultsOf the 220 US-based trials analyzed, 33 (15.0%) could be replicated using observational data because their intervention, indication, inclusion and exclusion criteria, and primary end points could be routinely ascertained from insurance claims and/or EHR data. Of the 220 trials, 86 (39.1%) had an intervention that could be ascertained from insurance claims and/or EHR data. Among the 86 trials, 62 (72.1%) had an indication that could be ascertained. Forty-five (72.6%) of 62 trials had at least 80% of inclusion and exclusion criteria data that could be ascertained. Of these 45 studies, 33 (73.3%) had at least 1 primary end point that could be ascertained.Conclusions and relevanceThis study found that only 15% of the US-based clinical trials published in high-impact journals in 2017 could be feasibly replicated through analysis of administrative claims or EHR data. This finding suggests the potential for real-world evidence to complement clinical trials, both by examining the concordance between randomized experiments and observational studies and by comparing the generalizability of the trial population with the real-world population of interest.
| S-EPMC6802419 | biostudies-literature
Project description:The US Food and Drug Administration approves tissue-agnostic therapies to target tumor biomarkers regardless of tumor type. In light of the growing number of such approvals in recent years, a better understanding of their relative clinical benefit across cancer types is required. To address this need, we analyzed tissue-agnostic indications (TMB-High, MSI-High/MMRd, BRAFV600E mutations, and NTRK and RET fusions) in a database of 295,316 molecularly-profiled tumor samples with associated clinical outcomes data. Here, we show that 21.5% of tumors harbored at least one of the tissue-agnostic indications investigated, including 5.4% lacking a cancer-specific indication. Our analysis reveals poor uptake of targeted therapies for rare NTRK fusions, significant differences in pembrolizumab-associated outcomes across tumor types for TMB-High and MSI-High/MMRd, as well as clinical benefits in tumor types and drugs of the same class not investigated in the pivotal clinical trials. These results demonstrate that treatment effects are not necessarily tissue-agnostic, and suggest possible expansion of therapeutic avenues for a given tissue-agnostic indication.
| S-EPMC11920432 | biostudies-literature
Project description:Cognitive function is an important end point of treatments in dementia clinical trials. Measuring cognitive function by standardized tests, however, is biased toward highly constrained environments (such as hospitals) in selected samples. Patient-powered real-world evidence using information and communication technology devices, including environmental and wearable sensors, may help to overcome these limitations. This position paper describes current and novel information and communication technology devices and algorithms to monitor behavior and function in people with prodromal and manifest stages of dementia continuously, and discusses clinical, technological, ethical, regulatory, and user-centered requirements for collecting real-world evidence in future randomized controlled trials. Challenges of data safety, quality, and privacy and regulatory requirements need to be addressed by future smart sensor technologies. When these requirements are satisfied, these technologies will provide access to truly user relevant outcomes and broader cohorts of participants than currently sampled in clinical trials.
| S-EPMC6179371 | biostudies-literature
Project description:IntroductionReal-world evidence is important in regulatory and funding decisions. Manual data extraction from electronic health records (EHRs) is time-consuming and challenging to maintain. Automated extraction using natural language processing (NLP) and artificial intelligence may facilitate this process. Whereas NLP offers a faster solution than manual methods of extraction, the validity of extracted data remains in question. The current study compared manual and automated data extraction from the EHR of patients with advanced lung cancer.MethodsPreviously, we extracted EHRs from 1209 patients diagnosed with advanced lung cancer (stage IIIB or IV) between January 2015 and December 2017 at Princess Margaret Cancer Centre (Toronto, Canada) using the commercially available artificial intelligence engine, DARWEN (Pentavere, Ontario, Canada). For comparison, 100 of 333 patients that received systemic therapy were randomly selected and clinical data manually extracted by two trained abstractors using the same accepted gold standard feature definitions, including patient, disease characteristics, and treatment data. All cases were re-reviewed by an expert adjudicator. Accuracy and concordance between automated and manual methods are reported.ResultsAutomated extraction required considerably less time (<1 day) than manual extraction (∼225 person-hr). The collection of demographic data (age, sex, diagnosis) was highly accurate and concordant with both methods (96%-100%). Accuracy (for either extraction approach) and concordance were lower for unstructured data elements in EHR, such as performance status, date of diagnosis, and smoking status (NLP accuracy: 88%-94%; Manual accuracy: 78%-94%; concordance: 71%-82%). Concurrent medications (86%-100%) and comorbid conditions (96%-100%), were reported with high accuracy and concordance. Treatment details were also accurately captured with both methods (84%-100%) and highly concordant (83%-99%). Detection of whether biomarker testing was performed was highly accurate and concordant (96%-98%), although detection of biomarker test results was more variable (accuracy 84%-100%, concordance 84%-99%). Features with syntactic or semantic variation requiring clinical interpretation were extracted with slightly lower accuracy by both NLP and manual review. For example, metastatic sites were more accurately identified through NLP extraction (NLP: 88%-99%; manual: 71%-100%; concordance: 70%-99%) with the exception of lung and lymph node metastases (NLP: 66%-71%; manual: 87%-92%; concordance: 58%) owing to analogous terms used in radiology reports not being included in the accepted gold standard definition.ConclusionsAutomated data abstraction from EHR is highly accurate and faster than manual abstraction. Key challenges include poorly structured EHR and the use of analogous terms beyond the accepted gold standard definition. The application of NLP can facilitate real-world evidence studies at a greater scale than could be achieved with manual data extraction.
| S-EPMC9201015 | biostudies-literature
Project description:BackgroundHelicobacter pylori (H. pylori) infects ~ 35% of Americans and can lead to serious sequelae if left untreated. Growing evidence indicates that clarithromycin-based therapies (CBT) are becoming increasingly ineffective for treating H. pylori infection. RHB-105 was approved by the US Food and Drug Administration in 2019 for the treatment of H. pylori infection in adults.AimsThe primary aim of this study was to assess prescribing patterns and associated cure rates of physician-directed therapy for subjects with persistent H. pylori infection after participation in one of two Phase 3 clinical trials (ERADICATE Hp and ERADICATE Hp2).MethodsWe reviewed study reports to identify specific physician-directed regimens selected for subjects whose H. pylori infection was not eradicated. We also conducted a CYP2C19 genotype analysis of subjects who were prescribed CBT. Finally, we analyzed real-world H. pylori retail prescription data and compared these with to the physician-directed therapies in the clinical trials studies.ResultsFollowing ERADICATE Hp, CBT was prescribed for 27/31 (87%) subjects achieving a 59.3% cure rate. Following ERADICATE Hp2, CBT was prescribed for 48/94 (51%) subjects achieving a 60.4% cure rate. Rapid CYP2C19 metabolizers (2/11) had a cure rate of 18.2% with CBT. Real-world prescription data from IQVIA showed more than 80% of prescriptions for H. pylori infection were for CBT.ConclusionsRates of CBT use persist despite sub-optimal eradication rates. Since RHB-105 does not contain clarithromycin, it can be prescribed first-line without concerns about clarithromycin resistance or CYP2C19 status. NCT03198507 & NCT01980095.
| S-EPMC9352601 | biostudies-literature
Project description:Background: Despite the ongoing innovations and the availability of numerous effective inhaled treatment options, achieving optimal disease control in most patients frequently remains disappointing. Unfortunately, although inhaled therapy is the cornerstone of respiratory disease management, the selection of the most appropriate inhaler is still overlooked or underestimated by some healthcare professionals, and inhaler misuse remains a significant challenge in managing chronic respiratory diseases which directly influences patients' quality of life, clinical outcomes, and risk of disease progression. Materials and Methods: This is a unicentric, observational, cross-sectional study designed to evaluate the inhaled therapy prescribed in hospitalized patients and to analyze device changes after hospitalization, as well as the factors associated with these changes. A single face-to-face visit was performed during the patient's hospitalization, where the inhaled therapy used prior to hospitalization was evaluated: technique (critical errors), compliance (TAI questionnaire), maximum peak inspiratory flow [PIF (L/min)], and level of inhaler handling-related knowledge. A binary logistic regression model was used to explore the association between changing device at discharge and the other independent variables Results: The inhaler most used during hospitalization was the metered-dose inhaler (MDI) with a chamber (51.9% of patients), with the dry powdered inhalers (DPI) being the inhalers used in 43% of maintenance inhaled therapies in the community setting prior to hospitalization. In addition, 90% of patients showed a maximum PIF ≥ 30 L/min, and 35.6% performed critical inhaler errors. These patients had statistically significantly lower maximum PIF values (52.1 L/min in patients with critical inhaler errors vs. 60.8 L/min without critical inhaler errors; p > 0.001) and were more likely to exhibit poor inhaler compliance compared to those without critical errors (50.5% vs. 31.0%, respectively). More than half of the patients who used MDI with spacer chamber made critical inhaler errors; 69.9% showed regular or poor treatment adherence, although 75.6% demonstrated good knowledge about inhaler handling. Only in 27% of the patients did the healthcare professional change the type of inhaler after hospitalization within clinical practice. The medical and nursing staff responsible for the patient's hospitalization were not informed of the assessment carried out in the study. The probability of not performing a device change at discharge was lower in patients with previous at-home treatment with combined inhaled therapy with LABA + ICS (OR 0.3 [0.18-0.83], p = 0.016) and in patients under triple inhaled therapy (OR 0.3 [0.17-0.76], p = 0.007). No significant differences were observed in inhaler changes when considering the frequency of critical inhaler errors, inhaler handling-related knowledge or maximum PIF values. Conclusions: Our study highlights the urgent need for a more personalized inhaler selection and consistent monitoring by healthcare professionals to minimize inhaler misuse, increase treatment compliance and adherence, and improve disease management outcomes. It is essential to provide training and promote the role of nursing in the evaluation and education of inhaled therapy. Additionally, the use of standardized approaches and tools, such as the CHECK DIAL, is crucial to facilitate the adaptation of devices to patients' needs.
| S-EPMC11856687 | biostudies-literature
Project description:BackgroundEosinophilic esophagitis is a chronic inflammatory disorder of the esophagus. This real-world study used patient and physician surveys to describe the clinical characteristics and disease burden of eosinophilic esophagitis-overall and in a subgroup of patients with dysphagia despite treatment.MethodsData analyzed in this study were collected in 2020 from US and EU patients with eosinophilic esophagitis. Eligible patients were aged ≥ 12 years with a diagnosis of eosinophilic esophagitis, had an esophageal count of ≥ 15 eosinophils/high-power field at diagnosis, and were currently prescribed treatment for eosinophilic esophagitis.ResultsOverall, 1001 patients were included, of whom 356 (36%) had dysphagia despite treatment. Demographics and clinical characteristics were similar in both populations. The severity of eosinophilic esophagitis was mild in more patients overall (69%) versus those with dysphagia despite treatment (48%). Patient disease history was similar in both populations, with some exceptions: common patient-reported symptoms were dysphagia (70% and 86%) and heartburn/acid reflux (55% and 49%), and common physician-reported symptoms were dysphagia (75% and 91%) and food impaction (46% and 52%). Treatment history was similar in both populations; overall, the most common treatments were proton pump inhibitors (83%) and topical corticosteroids (51%). Patients reported slightly more days with symptoms, higher impacts on activities of daily living, and slightly higher anxiety or depression in the dysphagia-despite-treatment population versus the overall population.ConclusionsEosinophilic esophagitis presents severe symptoms and comorbidities that substantially impact patients' well-being and quality of life. Greater awareness of and novel treatments for eosinophilic esophagitis are needed.
| S-EPMC11297626 | biostudies-literature
Project description:PurposeMinimizing the future risk of asthma exacerbation (AE) is one of the main goals of asthma management. We investigated prognostic factors for risk of severe AE (SAE) in a real-world clinical setting.MethodsThis is an observational study evaluating subjects who were diagnosed with asthma and treated with anti-asthmatic medications from January 1995 to June 2018. Risk factors for SAE were analyzed in 2 treatment periods (during the initial 2 years and the following 3-10 years of treatment) using the big data of electronic medical records.ResultsIn this study, 5,058 adult asthmatics were enrolled; 1,335 (28.64%) experienced ≥ 1 SAE during the initial 2 years of treatment. Female sex, higher peripheral eosinophil/basophil counts, and lower levels of forced expiratory volume in 1 second (FEV1; %) were factors predicting the risk of SAEs (P < 0.001 for all). Higher serum total immunoglobulin E levels increased the risk of SAEs among the patients having ≤ 2 SAEs (P = 0.025). Patients with more frequent SAEs during the initial 2 years of treatment had significantly higher risks of SAEs during the following years of treatment (P < 0.001, for all) (patients with ≥ 4 SAEs, odds ratio [OR], 29.147; those with 3 SAEs, OR, 14.819; those with 2 SAEs, OR, 9.867; those with 1 SAE, OR, 5.116), had higher maintenance doses of systemic steroids, and showed more gradual decline in FEV1 (%) and FEV1/forced vital capacity levels maintained during the following years of treatment (P < 0.001 for all).ConclusionsAsthmatics having risk factors for SAEs (female sex, higher peripheral eosinophil/basophil counts, and lower FEV1) should be strictly monitored to prevent future risk and improve clinical outcomes.
| S-EPMC7984950 | biostudies-literature
Project description:ObjectiveRecent large trials yield conflicting results on the association between incretin-based therapies (IBTs) and diabetic retinopathy (DR). We examined whether IBTs increase DR risk compared with other antihyperglycemics.Research design and methodsWe implemented an active comparator, new-user cohort design using a nationwide 20% random sample of fee-for-service U.S. Medicare beneficiaries aged 65 years or older with Parts A, B, and D coverage between 2007 and 2015. We identified the following cohorts without prior treatment for retinopathy: dipeptidyl peptidase 4 inhibitors (DPP4i) versus sulfonylureas (SU), DPP4i versus thiazolidinediones (TZD), glucagon-like peptide-1 receptor agonists (GLP1RA) versus long-acting insulin (LAI), and GLP1RA versus TZD. Primary outcome was advanced diabetic retinopathy requiring treatment (ADRRT), defined as a procedure code for retinopathy treatment. Incident diabetic retinopathy (IDR), identified by a diagnosis code, was a secondary outcome. We estimated propensity scores to balance confounders and adjusted hazard ratios (95% CI) using weighted Cox proportional hazards models.ResultsWe identified 213,652 eligible patients. During a median duration of 0.58 to 0.87 years across comparisons, with a rate from 6.0 to 12.8 per 1,000 person-years, IBTs were not associated with increased ADRRT or IDR risk. The adjusted hazard ratios (95% CI) for ADRRT were 0.91 (0.79-1.04) by comparing DPP4i to SU (n = 39,292 and 87,073); 0.91 (0.75-1.11), DPP4i to TZD (n = 51,410 and 22,231); 0.50 (0.39-0.65), GLP1RA to LAI (n = 9,561 and 82,849); and 0.75 (0.53-1.06), GLP1RA to TZD (n = 10,355 and 27,345).ConclusionsOur population-based cohort study of older U.S. adults with diabetes suggests that IBTs used for approximately 1 year do not increase the DR risk.
| S-EPMC6105327 | biostudies-literature