| Literature DB >> 29987525 |
Monika Wagner1, Dima Samaha2, Jesus Cuervo3, Harshila Patel4, Marta Martinez3, William M O'Neil4, Paula Jimenez-Fonseca5.
Abstract
INTRODUCTION: Unresectable, well-differentiated nonfunctioning gastroenteropancreatic neuroendocrine tumors (GEP-NETs) can be monitored (watchful waiting, WW) or treated with systemic therapy such as somatostatin analogues (SSAs) to delay progression. We applied a reflective multicriteria decision analysis (MCDA) shared-decision framework (previously developed for the USA) to explore what matters to Spanish patients and clinicians considering GEP-NET treatment options.Entities:
Keywords: EVIDEM; Gastroenteropancreatic neuroendocrine tumors; MCDA; Shared decision-making
Mesh:
Substances:
Year: 2018 PMID: 29987525 PMCID: PMC6096971 DOI: 10.1007/s12325-018-0745-6
Source DB: PubMed Journal: Adv Ther ISSN: 0741-238X Impact factor: 3.845
Fig. 1Mean (SD) normalized weights assigned by 11 participants using hierarchical point allocation to each domain/criterion/subcriterion of the MCDA a core and b modulated benefit–risk trees
Condensed evidence synthesis and participant scores (N = 11) and individual comments exploring the decision scenario of treatment (lanreotide as a reference case) versus watchful waiting
AE adverse event, CI confidence interval, ENETS European Neuroendocrine Tumor Society, HR hazard ratio, HRQoL health-related quality of life, NA not available (no comments provided), OLE open-label extension, QoL quality of life, RCT randomized clinical trial, SEOM Sociedad Española de Oncología Médica, SSA somatostatin analogue
Fig. 2Mean RBRB contributions* of each quantitative criterion and overall RBRB† for treatment (using lanreotide as reference case) versus watchful waiting a core benefit–risk model, b modulated benefit–risk model. *Values shown represent the contribution of criteria to the relative benefit–risk balance calculated as normalized weight (summing to 1) multiplied by score for each criterion (theoretical range from − 1 to + 1). †Relative benefit–risk balance is the sum of contributions from all criteria (theoretical range from − 1 to + 1). Error bars show standard deviations across 11 participants
Comparison of RBRBs and modulated RBRBs incorporating weights elicited using the primary (HPA) and alternative (DRS) weighting methods
| RBRB incorporates | Proportion of participants for whom HPA- and DRS-derived RBRBs differed by | |||
|---|---|---|---|---|
| HPA weights (primary analysis) | DRS weights (alternative analysis) | ≥ 0.1 points | ≥ 0.05 points | |
| Treatment vs watchful waiting | ||||
| Mean (SD) RBRB | 0.32 (0.24) | 0.29 (0.22) | 9% (1/11) | 36% (4/11) |
| Mean (SD) modulated RBRB | 0.50 ± 0.14 | 0.45 ± 0.13 | 18% (2/11) | 55% (6/11) |
| Treatment 1 vs treatment 2 | ||||
| Mean (SD) RBRB | 0.07 ± 0.12 | 0.06 ± 0.10 | 0% (0/11) | 27% (3/11) |
| Mean (SD) modulated RBRB | 0.10 ± 0.10 | 0.08 ± 0.06 | 18% (2/11) | 27% (3/11) |
RBRBs and modulated RBRBs can range from − 1 to + 1. N = 11 participants
DRS direct weighting scale, HPA hierarchical point allocation, RBRB relative benefit–risk balance, SD standard deviation
Fig. 3Comparison of normalized weights from US and Spanish study participants* for the (sub)criteria of the a core and b the modulated benefit–risk tree. *5 patients and 6 clinicians participated in each study. Error bars represent the standard error of the mean
Fig. 4Comparison of scores from US and Spanish study participants for the a benefit–risk intervention outcomes criteria and b the modulating criteria. *5 patients and 6 clinicians participated in each study. Error bars represent the standard error of the mean