scholarly journals Predictive P-score for treatment ranking in Bayesian network meta-analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Kristine J. Rosenberger ◽  
Rui Duan ◽  
Yong Chen ◽  
Lifeng Lin
Keyword(s):  
Decision Making ◽  
Future Study ◽  
Meta Analysis ◽  
Treatment Strategies ◽  
Medical Decision ◽  
Posterior Distributions ◽  
Future Studies ◽  
Common Value ◽  
Multiple Treatments ◽  
Different Sources

Abstract Background Network meta-analysis (NMA) is a widely used tool to compare multiple treatments by synthesizing different sources of evidence. Measures such as the surface under the cumulative ranking curve (SUCRA) and the P-score are increasingly used to quantify treatment ranking. They provide summary scores of treatments among the existing studies in an NMA. Clinicians are frequently interested in applying such evidence from the NMA to decision-making in the future. This prediction process needs to account for the heterogeneity between the existing studies in the NMA and a future study. Methods This article introduces the predictive P-score for informing treatment ranking in a future study via Bayesian models. Two NMAs were used to illustrate the proposed measure; the first assessed 4 treatment strategies for smoking cessation, and the second assessed treatments for all-grade treatment-related adverse events. For all treatments in both NMAs, we obtained their conventional frequentist P-scores, Bayesian P-scores, and predictive P-scores. Results In the two examples, the Bayesian P-scores were nearly identical to the corresponding frequentist P-scores for most treatments, while noticeable differences existed for some treatments, likely owing to the different assumptions made by the frequentist and Bayesian NMA models. Compared with the P-scores, the predictive P-scores generally had a trend to converge toward a common value of 0.5 due to the heterogeneity. The predictive P-scores’ numerical estimates and the associated plots of posterior distributions provided an intuitive way for clinicians to appraise treatments for new patients in a future study. Conclusions The proposed approach adapts the existing frequentist P-score to the Bayesian framework. The predictive P-score can help inform medical decision-making in future studies.

Bioethics in the field of pediatric surgery

2020 ◽  
Vol 69 (4) ◽  
pp. 483-492
Author(s):  
Marko Bašković ◽  
Dora Škrljak Šoša
Keyword(s):  
Decision Making ◽  
Legal System ◽  
Pediatric Surgery ◽  
Medical Decision Making ◽  
Treatment Strategies ◽  
Moral Dilemmas ◽  
The State ◽  
Best Interests ◽  
Medical Decision ◽  
Team Members

It is the professional responsibility of pediatric surgeons to follow the principles of maintaining life and alleviating suffering, often by questioning whether they have acted correctly. Apart from the moral dilemmas of choosing the best treatment strategies, they are often in dilemmas with the parents, who also involve their own “strategy” in the whole story, which they think is the most optimal treatment for their child, despite the contrary recommendations of the profession. Children, and especially adolescents, may be somewhat involved in medical decision making. Mostly the parent-physician-child / adolescent triangle agrees, but this is not always the case, which is why pediatric surgeons encounter problems. Ethical committees, composed of competent people, supported by the legal system of the state, who are able by consensus of team members to advocate and ensure the best interests of patients, must be activated for the full scope of the solution.

scholarly journals Evaluating the Effects of Symptom Monitoring on Menopausal Health Outcomes: A Systematic Review and Meta-Analysis

2021 ◽  
Vol 2 ◽  
Author(s):  
Robin Andrews ◽  
Gabrielle Hale ◽  
Bev John ◽  
Deborah Lancastle
Keyword(s):  
Systematic Review ◽  
Decision Making ◽  
Medical Decision Making ◽  
Meta Analysis ◽  
Menopausal Symptoms ◽  
Medical Decision ◽  
Health Awareness ◽  
Symptom Monitoring ◽  
Hot Flush ◽  
Doctor Communication

Evidence suggests that monitoring and appraising symptoms can result in increased engagement in medical help-seeking, improved patient-doctor communication, and reductions in symptom prevalence and severity. To date, no systematic reviews have investigated whether symptom monitoring could be a useful intervention for menopausal women. This review explored whether symptom monitoring could improve menopausal symptoms and facilitate health-related behaviours. Results suggested that symptom monitoring was related to improvements in menopausal symptoms, patient-doctor communication and medical decision-making, heightened health awareness, and stronger engagement in setting treatment goals. Meta-analyses indicated large effects for the prolonged use of symptom diaries on hot flush frequencies. Between April 2019 and April 2021, PsychInfo, EMBASE, MEDLINE, CINAHL, Cochrane, ProQuest, PsychArticles, Scopus, and Web of Science were searched. Eighteen studies met the eligibility criteria and contributed data from 1,718 participants. Included studies quantitatively or qualitatively measured the impact of symptom monitoring on menopausal populations and symptoms. Research was narratively synthesised using thematic methods, 3 studies were examined via meta-analysis. Key themes suggest that symptom monitoring is related to improvements in menopausal symptoms, improved patient-doctor communication and medical decision-making, increased health awareness, and stronger engagement in goal-setting behaviours. Meta-analysis results indicated large effects for the prolonged use of symptom diaries on hot flush frequency: 0.73 [0.57, 0.90]. This review is limited due to the low number of studies eligible for inclusion, many of which lacked methodological quality. These results indicate that symptom monitoring has potential as an effective health intervention for women with menopausal symptoms. This intervention may be beneficial within healthcare settings, in order to improve patient-doctor relations and adherence to treatment regimes. However, findings are preliminary and quality assessments suggest high risk of bias. Thus, further research is needed to support these promising outcomes.Systematic Review Registration Number:https://www.crd.york.ac.uk/prospero/display_record.php?, PROSPERO, identifier: CRD42019146270.

Importance of Faith on Medical Decisions Regarding Cancer Care

2003 ◽  
Vol 21 (7) ◽  
pp. 1379-1382 ◽  
Author(s):  
Gerard A. Silvestri ◽  
Sommer Knittig ◽  
James S. Zoller ◽  
Paul J. Nietert
Keyword(s):  
Lung Cancer ◽  
Decision Making ◽  
Formal Education ◽  
Treatment Decisions ◽  
Medical Decision ◽  
Advanced Lung Cancer ◽  
Medical Decisions ◽  
Future Studies ◽  
Medical Oncologists ◽  
Individual Decisions

Purpose: Decisions regarding cancer treatment choices can be difficult. Several factors may influence the decision to undergo treatment. One poorly understood factor is the influence of a patient’s faith on how they make medical decisions. We compared the importance of faith on treatment decisions among doctors, patients, and patient caregivers. Methods: One hundred patients with advanced lung cancer, their caregivers, and 257 medical oncologists were interviewed. Participants were asked to rank the importance of the following factors that might influence treatment decisions: cancer doctor’s recommendation, faith in God, ability of treatment to cure disease, side effects, family doctor’s recommendation, spouse’s recommendation, and children’s recommendation. Results: All three groups ranked the oncologist’s recommendation as most important. Patients and caregivers ranked faith in God second, whereas physicians placed it last (P < .0001). Patients who placed a high priority on faith in God had less formal education (P < .0001). Conclusion: Patients and caregivers agree on the factors that are important in deciding treatment for advanced lung cancer but differ substantially from doctors. All agree that the oncologist’s recommendation is most important. This is the first study to demonstrate that, for some, faith is an important factor in medical decision making, more so than even the efficacy of treatment. If faith plays an important role in how some patients decide treatment, and physicians do not account for it, the decision-making process may be unsatisfactory to all involved. Future studies should clarify how faith influences individual decisions regarding treatment.

The Effect of Patient Sex on Medical Decision-Making: A Meta-Analysis

2003 ◽  
Author(s):  
E. Kiernan Mcgorty ◽  
Srividya N. Iyer ◽  
Jennifer S. Hunt
Keyword(s):  
Decision Making ◽  
Medical Decision Making ◽  
Meta Analysis ◽  
Medical Decision

scholarly journals Dynamic meta-analysis: a method of using global evidence for local decision making

BMC Biology ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Gorm E. Shackelford ◽  
Philip A. Martin ◽  
Amelia S. C. Hood ◽  
Alec P. Christie ◽  
Elena Kulinskaya ◽  
...  
Keyword(s):  
Decision Making ◽  
Evidence Synthesis ◽  
Meta Analysis ◽  
Global Scale ◽  
Classification Systems ◽  
Evidence Based ◽  
Proof Of Concept ◽  
Future Studies ◽  
Evidence Based Decision Making ◽  
Global Evidence

Abstract Background Meta-analysis is often used to make generalisations across all available evidence at the global scale. But how can these global generalisations be used for evidence-based decision making at the local scale, if the global evidence is not perceived to be relevant to local decisions? We show how an interactive method of meta-analysis—dynamic meta-analysis—can be used to assess the local relevance of global evidence. Results We developed Metadataset (www.metadataset.com) as a proof-of-concept for dynamic meta-analysis. Using Metadataset, we show how evidence can be filtered and weighted, and results can be recalculated, using dynamic methods of subgroup analysis, meta-regression, and recalibration. With an example from agroecology, we show how dynamic meta-analysis could lead to different conclusions for different subsets of the global evidence. Dynamic meta-analysis could also lead to a rebalancing of power and responsibility in evidence synthesis, since evidence users would be able to make decisions that are typically made by systematic reviewers—decisions about which studies to include (e.g. critical appraisal) and how to handle missing or poorly reported data (e.g. sensitivity analysis). Conclusions In this study, we show how dynamic meta-analysis can meet an important challenge in evidence-based decision making—the challenge of using global evidence for local decisions. We suggest that dynamic meta-analysis can be used for subject-wide evidence synthesis in several scientific disciplines, including agroecology and conservation biology. Future studies should develop standardised classification systems for the metadata that are used to filter and weight the evidence. Future studies should also develop standardised software packages, so that researchers can efficiently publish dynamic versions of their meta-analyses and keep them up-to-date as living systematic reviews. Metadataset is a proof-of-concept for this type of software, and it is open source. Future studies should improve the user experience, scale the software architecture, agree on standards for data and metadata storage and processing, and develop protocols for responsible evidence use.

scholarly journals Spontaneous intracerebral hemorrhage and the challenge of surgical decision making: a review

2013 ◽  
Vol 34 (5) ◽  
pp. E1 ◽  
Author(s):  
Michael L. Kelly ◽  
Daniel P. Sulmasy ◽  
Robert J. Weil
Keyword(s):  
Decision Making ◽  
Intracerebral Hemorrhage ◽  
Medical Care ◽  
Cognitive Biases ◽  
Treatment Strategies ◽  
Medical Decision ◽  
Future Research ◽  
Spontaneous Intracerebral Hemorrhage ◽  
Surgical Decision ◽  
Surgical Decision Making

Decision making for patients with spontaneous intracerebral hemorrhage (ICH) poses several challenges. Outcomes in this patient population are generally poor, prognostication is often uncertain, and treatment strategies offer limited benefits. Studies demonstrate variability in the type and intensity of treatment offered, which is attributed to clinical uncertainty and habits of training. Research has focused on new techniques and more stringent evidence-based selection criteria to improve outcomes and produce consensus around treatment strategies for patients with ICH. Such focus, however, offers little description of how ICH treatment decisions are made and how such decisions reflect patient preferences regarding medical care. A growing body of literature suggests that the process of decision making in ICH is laden with bias, value assumptions, and subjective impressions. Factors such as geography, cognitive biases, patient perceptions, and physician characteristics can all shape decision making and the selection of treatment. Such factors often serve as a barrier to providing patient-centered medical care. In this article, the authors review how surgical decision making for patients with ICH is shaped by these decisional factors and suggest future research pathways to study decision making in ICH. Such research efforts are important for establishing quality guidelines and pay-for-performance measures that reflect the preferences of individual patients and the contextual nature of medical decision making.

scholarly journals Continuously updated network meta-analysis and statistical monitoring for timely decision-making

2016 ◽  
Vol 27 (5) ◽  
pp. 1312-1330 ◽  
Author(s):  
Adriani Nikolakopoulou ◽  
Dimitris Mavridis ◽  
Matthias Egger ◽  
Georgia Salanti
Keyword(s):  
Decision Making ◽  
Multiple Testing ◽  
Meta Analysis ◽  
Indirect Evidence ◽  
Current Evidence ◽  
Methodological Framework ◽  
Z Score ◽  
Future Studies ◽  
Statistical Monitoring ◽  
Made In

Pairwise and network meta-analysis (NMA) are traditionally used retrospectively to assess existing evidence. However, the current evidence often undergoes several updates as new studies become available. In each update recommendations about the conclusiveness of the evidence and the need of future studies need to be made. In the context of prospective meta-analysis future studies are planned as part of the accumulation of the evidence. In this setting, multiple testing issues need to be taken into account when the meta-analysis results are interpreted. We extend ideas of sequential monitoring of meta-analysis to provide a methodological framework for updating NMAs. Based on the z-score for each network estimate (the ratio of effect size to its standard error) and the respective information gained after each study enters NMA we construct efficacy and futility stopping boundaries. A NMA treatment effect is considered conclusive when it crosses an appended stopping boundary. The methods are illustrated using a recently published NMA where we show that evidence about a particular comparison can become conclusive via indirect evidence even if no further trials address this comparison.

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