Parent Priorities in End-of-Life Care for Children With Cancer
child; Terminal Care; terminal care; female; human; death; child parent relation; psychology; cross-sectional study; middle aged; neoplasm/th [Therapy]; Bayes theorem
Importance: Robust quality measures to benchmark end-of-life care for children with cancer do not currently exist; 28 candidate patient-centered quality measures were previously developed. Objective(s): To prioritize quality measures among parents who lost a child to cancer. Design, Setting, and Participant(s): This survey study was conducted using an electronic, cross-sectional discrete choice experiment (DCE) with maximum difference scaling from January to June 2021 in the US. In each of 21 questions in the DCE, participants were presented with a set of 4 quality measures and were asked to select the most and least important measures within each set. All 28 quality measures were presented an equal number of times in different permutations. In the volunteer sample, 69 eligible bereaved parents enrolled in the study; 61 parents completed the DCE (participation rate, 88.4%). Main Outcomes and Measures: Using choices participants made, a hierarchical bayesian multinomial logistic regression was fit to derive mean importance scores with 95% credible intervals (95% Crs) for each quality measure, representing the overall probability of a quality measure being selected as most important. Importance scores were rescaled proportionally from 0 to 100, with the sum of scores for all quality measures adding up to 100. This enabled interpretation of scores as the relative importance of quality measures. Result(s): Participants included 61 bereaved parents (median [range] age, 48 [24-74] years; 55 individuals self-identified as women [90.2%]; 1 American Indian or Alaska Native [1.6%], 1 Asian [1.6%], 2 Black or African American [3.3%], 1 Native Hawaiian or Pacific Islander, and 58 White [91.8%]; 58 not Hispanic or Latinx [95.1%]). Highest-priority quality measures by mean importance score included having a child's symptoms treated well (9.25 [95% Cr, 9.06-9.45]), feeling that a child's needs were heard by the health care team (8.39 [95% Cr, 8.05-8.73]), and having a goal-concordant end-of-life experience (7.45 [95% Cr, 6.84-8.05]). Lowest-priority quality measures included avoiding chemotherapy (0.33 [95% Cr, 0.21-0.45]), provision of psychosocial support for parents (1.01 [95% Cr, 0.57-1.45]), and avoiding the intensive care unit (1.09 [95% Cr, 0.74-1.43]). Rank-ordering measures by mean importance revealed that symptom management was 9 times more important to parents than psychosocial support for themselves. Conclusions and Relevance: This study found that bereaved parents prioritized end-of-life quality measures focused on symptom management and goal-concordant care while characterizing quality measures assessing their own psychosocial support and their child's hospital resource use as substantially less important. These findings suggest that future research should explore innovative strategies to measure care attributes that matter most to families of children with advanced cancer.
Ananth P; Lindsay M; Mun S; McCollum S; Shabanova V; de Oliveira S; Pitafi S; Kirch R; Ma X; Gross CP; Boyden JY; Feudtner C; Wolfe J
JAMA Network Open
2023
Article information provided for research and reference use only. PedPalASCNET does not hold any rights over the resource listed here. All rights are retained by the journal listed under publisher and/or the creator(s).
<a href="http://doi.org/10.1001/jamanetworkopen.2023.13503" target="_blank" rel="noreferrer noopener">10.1001/jamanetworkopen.2023.13503</a>
Combining single patient (N-of-1) trials to estimate population treatment effects and to evaluate individual patient responses to treatment
Humans; Outcome Assessment (Health Care); Research Design; Antidepressive Agents; Cross-Over Studies; Models; Statistical; Chronic disease; Amitriptyline/therapeutic use; Bayes Theorem; Fibromyalgia/drug therapy; Randomized Controlled Trials as Topic/statistics & numerical data; Tricyclic
When treating individual patients, physicians may face difficulties using the evidence from center-based randomized control trials (RCTs) due to limitations in these studies generalizability. Therefore, they often perform their own "informal" tests of treatment effectiveness. Single patient ("N-of-1") trials provide a structured design for more rigorous assessment of medical treatments of chronic diseases, but are applied only to the index patient. We present a hierarchical Bayesian random effects model to combine N-of-1 studies to obtain an estimate of treatment effectiveness for the population and to use this population information to aid in the evaluation of an individual patient's trial results. The model's treatment effect estimates are adjustments between the population estimate and the individual's observed results. This adjustment is based upon the within-patient and between-patient heterogeneity. We demonstrate this patient-focused method using published data from 23 N-of-1 trial results comparing amitriptyline and placebo for the treatment of fibromyalgia.
1997
Zucker DR; Schmid CH; McIntosh MW; D'Agostino RB; Selker HP; Lau J
Journal Of Clinical Epidemiology
1997
Article information provided for research and reference use only. PedPalASCNET does not hold any rights over the resource listed here. All rights are retained by the journal listed under publisher and/or the creator(s).
Journal Article
<a href="http://doi.org/10.1016/s0895-4356(96)00429-5" target="_blank" rel="noreferrer">10.1016/s0895-4356(96)00429-5</a>