On the 12th Day of Christmas, a Statistician Sent to Me . . .

Objective We conducted a systematic review to characterize and critically appraise developed prediction models based on structured electronic health record (EHR) data for adverse drug event (ADE) diagnosis and prognosis in adult hospitalized patients. Materials and Methods We searched the Embase and Medline databases (from January 1, 1999, to July 4, 2022) for articles utilizing structured EHR data to develop ADE prediction models for adult inpatients. For our systematic evidence synthesis and critical appraisal, we applied the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS). Results Twenty-five articles were included. Studies often did not report crucial information such as patient characteristics or the method for handling missing data. In addition, studies frequently applied inappropriate methods, such as univariable screening for predictor selection. Furthermore, the majority of the studies utilized ADE labels that only described an adverse symptom while not assessing causality or utilizing a causal model. None of the models were externally validated. Conclusions Several challenges should be addressed before the models can be widely implemented, including the adherence to reporting standards and the adoption of best practice methods for model development and validation. In addition, we propose a reorientation of the ADE prediction modeling domain to include causality as a fundamental challenge that needs to be addressed in future studies, either through acquiring ADE labels via formal causality assessments or the usage of adverse event labels in combination with causal prediction modeling.

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“…For causal prediction models , a different approach is needed that addresses confounding bias. 64 , 65 …”

Section: Discussionmentioning

confidence: 99%

Electronic health record-based prediction models for in-hospital adverse drug event diagnosis or prognosis: a systematic review

Kom

Dongelmans

Keizer

et al. 2023

Journal of the American Medical Informatics Association

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“…First, it is a single-centre retrospective study using a convenience sample, which limits the generalizability of the results. Second, the sample size was small and although an attempt at performing a multivariate analysis was made, this analysis must be considered to be merely explorative; in other terms, the absence of an evidence in this analysis does not mean evidence of an absent impact or correlation of the outcome with the given factors among those tested (such as gender, age, BMI, hypertension and combination therapy) [ 36 ]. Third, the chosen outcome (i.e.…”

Section: Discussionmentioning

confidence: 99%

Interleukin-62/lymphocyte as a proposed predictive index for COVID-19 patients treated with monoclonal antibodies

et al. 2023

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In a convenience sample of 93 patients treated with monoclonal antibodies (moAbs) against SARS-CoV-2, the interleukin-62/lymphocyte count ratio (IL-62/LC) was able to predict clinical worsening both in early stages of COVID-19 and in oxygen-requiring patients. Moreover, we analysed 18 most at-risk patients with asymptomatic or mild disease treated with both moAbs and antiviral treatment and found that only 2 had clinical progression, while patients with a similar risk were reported to have an unfavourable outcome in most cases from recent data. In only one of our 18 patients, clinical progression was attributable to COVID-19, and in the other cases, clinical progression was observed despite IL-62/LC being above the risk cut-off. In conclusion, IL-62/LC may be a valuable method to identify patients requiring more aggressive treatments both in earlier and later stages of the disease; however, most at-risk patients can be protected from clinical worsening by combining moAbs and antivirals, even if levels of the IL-62/LC biomarker are lower than the risk cut-off.

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“…To identify predictors of decisional conflict, we will perform a binary logistic regression analysis. The dichotomisation of a variable implies a loss of information 63. To ensure a good description of the decisional conflict, we will also process this variable as continuous and perform a multiple linear regression analysis.…”

Section: Discussionmentioning

confidence: 99%

Decisional needs assessment for patient-centred pain care in Canada: the DECIDE-PAIN study protocol

et al. 2023

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IntroductionThe 2021 Action Plan for Pain from the Canadian Pain Task Force advocates for patient-centred pain care at all levels of healthcare across provinces. Shared decision-making is the crux of patient-centred care. Implementing the action plan will require innovative shared decision-making interventions, specifically following the disruption of chronic pain care during the COVID-19 pandemic. The first step in this endeavour is to assess current decisional needs (ie, decisions most important to them) of Canadians with chronic pain across their care pathways.Methods and analysisDesignGrounded in patient-oriented research approaches, we will perform an online population-based survey across the ten Canadian provinces. We will report methods and data following the CROSS reporting guidelines.SamplingThe Léger Marketing company will administer the online population-based survey to its representative panel of 500 000 Canadians to recruit 1646 adults (age ≥18 years old) with chronic pain according to the definition by the International Association for the Study of Pain (eg, pain ≥12 weeks).ContentBased on the Ottawa Decision Support Framework, the self-administered survey has been codesigned with patients and contain six core domains: (1) healthcare services, consultation and postpandemic needs, (2) difficult decisions experienced, (3) decisional conflict, (4) decisional regret, (5) decisional needs and (6) sociodemographic characteristics. We will use several strategies such as random sampling to improve survey quality.AnalysisWe will perform descriptive statistical analysis. We will identify factors associated with clinically significant decisional conflict and decision regret using multivariate analyses.Ethics and disseminationEthics was approved by the Research Ethics Board at the Research Centre of the Centre Hospitalier Universitaire de Sherbrooke (project #2022-4645). We will codesign knowledge mobilisation products with research patient partners (eg, graphical summaries and videos). Results will be disseminated via peer-reviewed journals and national and international conferences to inform the development of innovative shared decision-making interventions for Canadians with chronic pain.

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On the 12th Day of Christmas, a Statistician Sent to Me . . .

Abstract: On the 12th Day of Christmas, a Statistician Sent to Me . . . The BMJ's statistical editors relish a quiet Christmas, so make their wish come true and pay attention to the list of common statistical faux pas presented here by Riley and colleagues

Cited by 16 publications

References 87 publications

Electronic health record-based prediction models for in-hospital adverse drug event diagnosis or prognosis: a systematic review

Electronic health record-based prediction models for in-hospital adverse drug event diagnosis or prognosis: a systematic review

Interleukin-62/lymphocyte as a proposed predictive index for COVID-19 patients treated with monoclonal antibodies

Decisional needs assessment for patient-centred pain care in Canada: the DECIDE-PAIN study protocol

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