Predicting placebo response in adolescents with major depressive disorder: The Adolescent Placebo Impact Composite Score (APICS)

Nakonezny, Paul A.; Mayes, Taryn L.; Byerly, Matthew J.

doi:10.1016/j.jpsychires.2015.05.003

Cited by 10 publications

(10 citation statements)

References 26 publications

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“…Comparing our model to the two previous models developed by Nelson et al 15 and Nakonezny et al ,14 we found that similar factors were related to placebo response, namely, severity of depression (bodily symptoms), age and age at onset. Nelson et al developed a prediction model of remission to placebo based on eight RCTs with duloxetine for major depression.…”

Section: Discussionsupporting

confidence: 64%

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Development and validation of a prediction model for the probability of responding to placebo in antidepressant trials: a pooled analysis of individual patient data

Shinohara

Tanaka

Noma

et al. 2019

Evid Based Mental Health

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BackgroundIdentifying potential placebo responders among apparent drug responders is critical to dissect drug-specific and nonspecific effects in depression.ObjectiveThis project aimed to develop and test a prediction model for the probability of responding to placebo in antidepressant trials. Such a model will allow us to estimate the probability of placebo response among drug responders in antidepressants trials.MethodsWe identified all placebo-controlled, double-blind randomised controlled trials (RCTs) of second generation antidepressants for major depressive disorder conducted in Japan and requested their individual patient data (IPD) to pharmaceutical companies. We obtained IPD (n=1493) from four phase II/III RCTs comparing mirtazapine, escitalopram, duloxetine, paroxetine and placebo. Out of 1493 participants in the four clinical trials, 440 participants allocated to placebo were included in the analyses. Our primary outcome was response, defined as 50% or greater reduction on Hamilton Rating Scale for Depression at study endpoint. We used multivariable logistic regression to develop a prediction model. All available candidate of predictor variables were tested through a backward variable selection and covariates were selected for the prediction model. The performance of the model was assessed by using Hosmer-Lemeshow test for calibration and the area under the ROC curve for discrimination.FindingsPlacebo response rates differed between 31% and 59% (grand average: 43%) among four trials. Four variables were selected from all candidate variables and included in the final model: age at onset, age at baseline, bodily symptoms, and study-level difference. The final model performed satisfactorily in terms of calibration (Hosmer-Lemeshow p=0.92) and discrimination (the area under the ROC curve (AUC): 0.70).ConclusionsOur model is expected to help researchers discriminate individuals who are more likely to respond to placebo from those who are less likely so.Clinical implicationsA larger sample and more precise individual participant information should be collected for better performance. Examination of external validity in independent datasets is warranted.Trial registration numberCRD42017055912.

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Section: Discussionsupporting

confidence: 64%

“…However, some important factors, such as age at onset of the first episode and physical illness, were not fully examined in their dataset. Also, their dataset included one trial only14 or duloxetine trials only 15. Thus, their models have limited value in terms of validity and generalisability.…”

Section: Introductionmentioning

confidence: 99%

Development and validation of a prediction model for the probability of responding to placebo in antidepressant trials: a pooled analysis of individual patient data

Shinohara

Tanaka

Noma

et al. 2019

Evid Based Mental Health

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“…However, investigators and clinicians routinely encounter certain individuals who respond to placebo treatments (Lasagna et al 1954) and some contend that placebo represents an active intervention in and of itself (Kaptchuk and Miller, 2015). More recently, predicting and understanding the determinants of pill placebo response have emerged as important aspects of both clinical research and clinical practice (Newcorn et al 2009;Cohen et al 2010;Iovieno and Papakostas 2012;Nakonezny et al 2015). Ultimately, a better understanding of placebo response, and the ability to predict its magnitude, may increase the likelihood of detecting treatment effects in randomized controlled trials, particularly those involving children and adolescents as they may inform study design and the conduct of clinical trials.…”

Section: Introductionmentioning

confidence: 99%

Placebo Response in Pediatric Anxiety Disorders: Results from the Child/Adolescent Anxiety Multimodal Study

Dobson

Mills

Cornwall

et al. 2017

Journal of Child and Adolescent Psychopharmacology

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“…13 Moreover, while accumulating positive trials of the SSRIs populated the literature following the initial positive trial of fluoxetine in pediatric patients with MDD 14 in the mid-1990s, increasing numbers of failed trials and negative trials began to emerge. 15–17 The evaluation of antidepressants in pediatric patients with MDD is complicated by increasing placebo response rates 18 which have been hypothesized by some to have resulted in a number of these “failed trials” 18,19 Several efforts have been made to understand placebo-response in depressed youth and it appears that this may be the result of non-specific supportive care that is provided in the context of a clinical trial, although at least one recent analyses suggests that placebo response in depressed youth may also be related to patient level factors, including socioeconomic status, age and duration of illness. 19,20 …”

Section: Introductionmentioning

confidence: 99%

Primary Pediatric Care Psychopharmacology: Focus on Medications for ADHD, Depression, and Anxiety

Dobson

Giles

2017

Current Problems in Pediatric and Adolescent Health Care

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The evidence base for psychopharmacologic interventions in youth with depressive and anxiety disorders as well as attention/deficit hyperactivity disorder (ADHD) has dramatically increased over the past two decades. Psychopharmacologic interventions commonly utilized in the pediatric primary care setting—selective serotonin (norepinephrine) reuptake inhibitors (SSRIs/SSNRIs), stimulants and α2 agonists—are reviewed. General pharmacologic principles are summarized along with class-related side effects and tolerability concerns (e.g., suicidality and activation in antidepressant-treated youth as well as insomnia, irritability, anorexia in stimulant-treated pediatric patients). Selected landmark trials of antidepressant medications in youth with depressive disorders (Treatment of Adolescent Depression Study [TADS] and the Treatment of SSRI-Resistant Depression Study [TADS]) and anxiety disorders (Child/Adolescent Anxiety Multimodal Study [CAMS] and Child/Adolescent Anxiety Multimodal Extended Long-term Study [CAMELS]) are described in addition to the Multimodal Treatment of ADHD Study. Finally, available data are presented that are related to prediction of treatment outcomes in youth with depressive disorders, anxiety disorders and ADHD.

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Predicting placebo response in adolescents with major depressive disorder: The Adolescent Placebo Impact Composite Score (APICS)

Cited by 10 publications

References 26 publications

Development and validation of a prediction model for the probability of responding to placebo in antidepressant trials: a pooled analysis of individual patient data

Development and validation of a prediction model for the probability of responding to placebo in antidepressant trials: a pooled analysis of individual patient data

Placebo Response in Pediatric Anxiety Disorders: Results from the Child/Adolescent Anxiety Multimodal Study

Primary Pediatric Care Psychopharmacology: Focus on Medications for ADHD, Depression, and Anxiety

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