Immortal Time Bias in Observational Studies Yadav, Kabir; Lewis, Roger J
JAMA : the journal of the American Medical Association,
02/2021, Letnik:
325, Številka:
7
Journal Article
Recenzirano
This JAMA Guide to Statistics and Medicine explains immortal time bias, an error in estimating the association between an exposure and an outcome that results from misclassification or exclusion of ...time intervals; explains how this misclassification or exclusion can occur; and presents approaches to minimize or avoid immortal time bias.
Confounding by Indication in Clinical Research Kyriacou, Demetrios N; Lewis, Roger J
JAMA : the journal of the American Medical Association,
11/2016, Letnik:
316, Številka:
17
Journal Article
Recenzirano
Kyriacou and Lewis stress that the possibility of confounding by other factors must be considered in the assessment of the effect of a treatment or potential risk factor--termed an exposure--on a ...patient outcome. The primary goal of clinical research is to obtain valid measures of the effects of treatments or potential risk factors on patient outcomes. Because confounding distorts the true relationship between the exposure of interest and the outcome, investigators attempt to control confounding to provide valid measures of the observed associations or treatment effects. In particular, randomized clinical trials (RCTs) use randomized treatment assignment to balance potential confounding factors--whether measured, unmeasured, or unknown--that might affect the outcome to ensure that those factors are unrelated to the assigned intervention. Thus, RCTs do not typically require use of statistical methods to adjust for confounding, as the randomization process is meant to limit all forms of confounding.
The Propensity Score Haukoos, Jason S; Lewis, Roger J
JAMA,
10/2015, Letnik:
314, Številka:
15
Journal Article
Recenzirano
Odprti dostop
Haukoos and Lewis explain why propensity methods were used in the studies conducted by Rose et al and Huybrechts et al. These two recent studies involved the analysis of observational data to ...estimate the effect of a treatment on patient outcomes. They also discuss four ways propensity scores are used.
Purpose
Invasive pulmonary aspergillosis (IPA) is increasingly reported in patients with severe coronavirus disease 2019 (COVID-19) admitted to the intensive care unit (ICU). Diagnosis and management ...of COVID-19 associated pulmonary aspergillosis (CAPA) are challenging and our aim was to develop practical guidance.
Methods
A group of 28 international experts reviewed current insights in the epidemiology, diagnosis and management of CAPA and developed recommendations using GRADE methodology.
Results
The prevalence of CAPA varied between 0 and 33%, which may be partly due to variable case definitions, but likely represents true variation. Bronchoscopy and bronchoalveolar lavage (BAL) remain the cornerstone of CAPA diagnosis, allowing for diagnosis of invasive
Aspergillus
tracheobronchitis and collection of the best validated specimen for
Aspergillus
diagnostics. Most patients diagnosed with CAPA lack traditional host factors, but pre-existing structural lung disease and immunomodulating therapy may predispose to CAPA risk. Computed tomography seems to be of limited value to rule CAPA in or out, and serum biomarkers are negative in 85% of patients. As the mortality of CAPA is around 50%, antifungal therapy is recommended for BAL positive patients, but the decision to treat depends on the patients’ clinical condition and the institutional incidence of CAPA. We recommend against routinely stopping concomitant corticosteroid or IL-6 blocking therapy in CAPA patients.
Conclusion
CAPA is a complex disease involving a continuum of respiratory colonization, tissue invasion and angioinvasive disease. Knowledge gaps including true epidemiology, optimal diagnostic work-up, management strategies and role of host-directed therapy require further study.
Decision Curve Analysis Fitzgerald, Mark; Saville, Benjamin R; Lewis, Roger J
JAMA : the journal of the American Medical Association,
01/2015, Letnik:
313, Številka:
4
Journal Article
Recenzirano
Decision curve analysis (DCA) is a method for evaluating the benefits of a diagnostic test across a range of patient preferences for accepting risk of undertreatment and overtreatment to facilitate ...decisions about test selection and use) In this issue of JAMA. Siddiqul and colleagues used DCA to evaluate 3 prostate biopsy strategies: targeted magnetic resonance/ultrasound fusion biopsy, standard extended-sextant biopsy, or a combination, for establishing the diagnosis of intermediate- to high-risk prostate cancer. Their goal was to identify the best biopsy strategy to ensure prostatectomy is offered to patients with intermediate- and high-risk tumors and avoided for patients with low-risk tumors. Here, Fitzgerald et al detail the limitations of DCA Method and its findings.
Purpose
Invasive pulmonary aspergillosis is increasingly reported in patients with influenza admitted to the intensive care unit (ICU). Classification of patients with influenza-associated pulmonary ...aspergillosis (IAPA) using the current definitions for invasive fungal diseases has proven difficult, and our aim was to develop case definitions for IAPA that can facilitate clinical studies.
Methods
A group of 29 international experts reviewed current insights into the epidemiology, diagnosis and management of IAPA and proposed a case definition of IAPA through a process of informal consensus.
Results
Since IAPA may develop in a wide range of hosts, an entry criterion was proposed and not host factors. The entry criterion was defined as a patient requiring ICU admission for respiratory distress with a positive influenza test temporally related to ICU admission. In addition, proven IAPA required histological evidence of invasive septate hyphae and mycological evidence for
Aspergillus
. Probable IAPA required the detection of galactomannan or positive
Aspergillus
culture in bronchoalveolar lavage (BAL) or serum with pulmonary infiltrates or a positive culture in upper respiratory samples with bronchoscopic evidence for tracheobronchitis or cavitating pulmonary infiltrates of recent onset. The IAPA case definitions may be useful to classify patients with COVID-19-associated pulmonary aspergillosis (CAPA), while awaiting further studies that provide more insight into the interaction between
Aspergillus
and the SARS-CoV-2-infected lung.
Conclusion
A consensus case definition of IAPA is proposed, which will facilitate research into the epidemiology, diagnosis and management of this emerging acute and severe
Aspergillus
disease, and may be of use to study CAPA.
When assessing the clinical utility of therapies intended to improve subjective outcomes, the amount of improvement that is important to patients must be determined. The smallest benefit of value to ...patients is called the minimal clinically important difference (MCID). The MCID is a patient-centered concept, capturing both the magnitude of the improvement and also the value patients place on the change. Using patient-centered MCIDs is important for studies involving patient-reported outcomes, for which the clinical importance of a given change may not be obvious to clinicians selecting treatments. The MCID defines the smallest amount an outcome must change to be meaningful to patients. Here, McGlothin and Lewis explain the use of MCID method.
The Bayesian analysis allows for the integration or updating of prior information with newly obtained data to yield a final quantitative summary of the information. Here, Quintana et al discuss the ..."prior information."
Futility in Clinical Trials Wendelberger, Barbara; Lewis, Roger J
JAMA : the journal of the American Medical Association,
08/2023, Letnik:
330, Številka:
8
Journal Article
Recenzirano
This JAMA Guide to Statistics and Methods discusses the early stopping of clinical trials for futility due to lack of evidence supporting the desired benefit, evidence of harm, or practical issues ...that make successful completion unlikely.
Missing data are common in clinical research, particularly for variables requiring complex, time-sensitive, resource-intensive, or longitudinal data collection methods. However, even seemingly ...readily available information can be missing. Here, Newgard et al tells why these methods are used and cite ways by which data may be missing.
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