Background

Obsessive-compulsive disorder (OCD) is a common, chronic, and impairing psychiatric disorder, defined by one or both of two cardinal features—obsessions and compulsions. Obsessions are persistent thoughts, urges, or images that are experienced as intrusive and unwanted, generally related to one or more domains that can range from fear of illness or death to uncomfortable experiences of incompleteness or disgust. People with OCD exhibit heterogeneous compulsive rituals, avoidance behaviors, and other strategies to neutralize or avoid distress and obsessional triggers.¹ About 3% of youth (children and adolescents) experience OCD.² An international study of patients with OCD reported that 21% had symptom onset in childhood (≤12 years) and 36% had symptom onset during adolescence (13-17 years).³

Early identification and treatment of OCD is important in preventing a cascade of developmental disruptions lasting into adulthood that can affect both function and quality of life, particularly in academic and social functioning.^4-6 Untreated OCD is associated with depression, substance abuse, suicide attempts, and functional impairment in adulthood.^{5, 7-10} Establishing an OCD diagnosis can be more challenging in children than in adults due to overlap with developmentally typical childhood fears and rituals, and, especially in young children, developmentally limited cognitive ability to describe their experiences.^1,11,12 Furthermore, OCD in children is often comorbid with depression, anxiety disorders, attention deficit hyperactivity disorder (ADHD), and eating disorders.¹³ Individuals with OCD may exhibit behaviors similar to those seen in autism, tic disorders, and other anxiety-related disorders, making differential diagnosis challenging.¹²

The 2012 American Academy of Child and Adolescent Psychiatry (AACAP) Practice Parameter recommends that for children and adolescents undergoing psychiatric assessment for any condition, 1. “The psychiatric assessment … should routinely screen for the presence of obsessions and/or compulsions or repetitive behaviors,” , even when not part of the presenting complaint, and 2. “If screening suggests [obsessive compulsive] symptoms may be present, clinicians should fully evaluate the child using [DSM] criteria and scalar assessment”; 3. Clinicians should use information from all available sources, and 4 “A complete psychiatric evaluation should be performed, … with attention to commonly occurring comorbid psychiatric disorders”.¹

The reference standard for an OCD diagnosis is a clinical interview by an expert assessing current DSM criteria, often augmented, particularly in research settings, with a semi-structed diagnostic interview (e.g., the Anxiety Disorders Interview Schedule for DSM-IV-child version [ADIS-C]).¹⁴

Because primary care practitioners do not have the expertise or the time to do the full diagnostic interview required for diagnosis, they only identify about 10% of cases of childhood OCD.¹⁵ Experts in assessing OCD are often overbooked, leading to potential late diagnosis or missed diagnosis of OCD in children. Brief assessment tools that accurately identify OCD (compared to reference standard methods), could allow primary care providers to make a provisional diagnosis, which would be confirmed by a specialist.^16,17

In terms of treatment, the 2012 AACAP Practice Parameter recommends cognitive behavioral therapy (CBT) that incorporates exposure and response prevention (ERP) as a first-line treatment for mild-to-moderate OCD in youth.¹ For moderate-to-severe OCD, the Practice Parameter recommends the addition of pharmacological treatment with a selective serotonin reuptake inhibitor (SSRI). However, questions remain about what (combinations of) treatment strategies work best for specific populations and settings. For example, individual versus family-focused versus parent-mediated, residential versus outpatient settings, through telemedicine as compared to self-guided CBT with ERP, and CBT with ERP combined with medications or other augmentations (e.g., transcranial magnetic stimulation, mindfulness), and medication alone. In addition, new treatment modalities, such as neuromodulation and complementary interventions, have come into use since the 2012 Practice Parameter.

The concept of an “autoimmune OCD” subtype has been proposed for a small subgroup of OCD patients, including pediatric acute-onset neuropsychiatric syndrome (PANS) and pediatric autoimmune neuropsychiatric disorder associated with streptococcal infections (PANDAS).^18,19 In one study of consecutive patients presenting to a subspeciality pediatric OCD clinic, 7 of 136 (5.1%) children with OCD met proposed diagnostic criteria for PANS/PANDAS.²⁰ A 2018 review noted that “the concept of PANDAS brings great challenges to clinicians, patients and their families, with respect to diagnosis and treatment.”²¹ While a systematic review of the evidence relating to the diagnosis criteria for and specific treatment of PANS/PANDAS is outside the scope of this review, given that OCD symptoms are central components of proposed PANS/PANDAS diagnostic criteria, we will summarize the available evidence regarding the comparative effects of behavioral and pharmacological treatments for OCD in this subgroup in the report.

Recent OCD research has examined 1. Extending or improving upon the efficacy of treatments (e.g., optimization and augmentation strategies), 2. “Transporting” treatment efficacy to populations previously excluded from efficacy trials, such as younger children, individuals with autism spectrum disorder, and underserved populations, and 3. Tailoring treatment to specific subgroups (e.g., non-responders, high-conflict families).²²

Purpose of the Review

This comparative effectiveness review will inform a planned update of the 2012 AACAP Practice Parameter.¹

AACAP nominated this topic to the Patient-Centered Outcomes Research Institute (PCORI), which contracted with the Agency for Healthcare Research and Quality (AHRQ) to conduct the review.

Specifically, the systematic review will summarize the findings from 1. Studies related to the accuracy of assessment tools compared to reference standard methods to identify OCD in symptomatic youth and 2. Studies of psychological and/or pharmacological treatments of OCD.

The intended audience includes guideline developers, child psychiatrists and psychologists, pediatricians, family physicians, advanced practice providers, parents, and patients.

Key Questions (KQ)

Introduction: We facilitated a series of calls with Technical Expert Panel (TEP) members to refine the Key Questions and specific inclusion/exclusion criteria. The TEP members endorsed the clinical interview by an expert using current DSM criteria as the sole basis (reference standard) for a diagnosis of OCD. The TEP emphasized the importance of differential diagnosis and identification of comorbid conditions. Thus, rather than focusing on comparison of diagnostic strategies, KQ 1 was amended to focus on the accuracy of available assessment tools (often brief, potentially with multiple informants, such as parent or patient) in symptomatic youth for whom OCD was in the differential diagnosis. The TEP described the potential harms related to the diagnosis of OCD as being largely related to missed diagnosis or over diagnosis. Therefore, a separate sub-question related to the harms of testing was removed. The importance of both family and social factors were mentioned by the TEP and were added as possible effect modifiers to both KQs. The TEP members agreed that the diagnosis of PANS/PANDAS is an important consideration as a potential effect modifier, but that the review should not specifically address diagnosis or treatment of PANS/PANDAS; rather, the review should maintain its focus on youth with symptoms suggestive of OCD (for KQ 1) or with an OCD diagnosis (for KQ 2).

KQ 1: How accurate are assessment tools compared to reference standard methods to identify OCD in symptomatic children and adolescents?

     KQ 1a: How does diagnostic accuracy of assessment tools vary by patient, family, social, or other characteristics, or by respondent type?

KQ 2: What are the comparative effects and harms of treatment interventions, used alone or in combination, for OCD in children and adolescents?

     KQ 2a: How do the effectiveness and harms vary with patient, family, social, or other characteristics?

Study Eligibility Criteria

*Prioritized outcome

Figure 1. Analytic framework for Diagnosis and Management of Obsessive Compulsive Disorders in Children

Abbreviations: ADIS-C = Anxiety Disorders Interview Schedule for DSM-5, K-SADS-PL = Kiddie Schedule for Affective Disorders and Schizophrenia, Present and Lifetime version , MINI-KID = Mini-International Neuropsychiatric Interview for Children and Adolescents, AUC = Area under the receiver operating characteristic curve,  KQ = Key question, OCD = Obsessive-compulsive disorder, PANS = pediatric acute-onset neuropsychiatric syndrome, PANDAS = pediatric autoimmune neuropsychiatric disorder associated with streptococcal infections.

The systematic review for KQs 1 and 2 will follow the Evidence-based Practice Center Program methodology, as described in its Methods Guide, particularly as it pertains to reviews of comparative effectiveness.²⁴

Criteria for Inclusion/Exclusion of Studies in the Systematic Review: See detailed eligibility criteria in Section II.

In brief, for Key Question 1, we will include studies that evaluate the diagnostic accuracy (predictive validity) of different assessment scales for OCD in children and adolescents, compared to a reference standard (clinical interview by an expert assessing current DSM criteria, possibly augmented by a semi-structured interview using a validated diagnostic assessment instrument). We will evaluate outcomes as listed in the Study Eligibility Criteria section, focusing on sensitivity and specificity jointly.

For Key Question 2, we will include studies comparing psychological and pharmacological interventions for OCD, alone or in combination, compared to no treatment, placebo or another active intervention or co-intervention(s), or delivery method. We will evaluate outcomes as listed in the Study Eligibility Criteria section, focusing on listed prioritized outcomes related to OCD symptom severity, treatment response and remission, functional impairment, family accommodation, quality of life, and acceptability of treatment and adverse events related to treatment. Prioritized outcomes are in bold font (with asterisks) in the Study Eligibility Criteria table.

For all Key Questions, we will attempt to identify predictors and moderators of treatment effect (see potential effect modifiers/subgroups of interest).

With input from the TEP, we have prioritized the following list of outcomes. As described below, we will evaluate the strength of evidence (SoE) for these outcomes. We may also evaluate SoE for other included outcomes. The prioritized outcomes include:

KQ 1

• Sensitivity/Specificity

KQ 2

• OCD symptom severity
• Treatment response and remission
• Functional impairment in school, social, and home/family domains
• Family accommodation
• Quality of life
• Acceptability of treatment
• Adverse events related to treatment

Literature Search Strategies to Identify Relevant Studies to Answer the Key Questions

We will search for studies and existing systematic reviews in MEDLINE (via PubMed), the Cochrane Register of Clinical Trials, the Cochrane Database of Systematic Reviews, Embase, CINAHL and PsycINFO and Education Resources Information Center (ERIC) databases. We will search index terms, along with free-text words, for concepts related to OCD and pediatric and adolescent populations. Duplicate citations will be removed prior to screening. We will not apply language, date, or country restrictions. Search strategies will include filters to remove nonhuman studies and articles that are not primary studies or systematic reviews. The PubMed search strategy is detailed in Appendix A.

Additional searches will be conducted in the ClinicalTrials.gov registry for ongoing and unpublished studies with study results. The reference lists of relevant existing systematic reviews will be screened for additional eligible studies. A Supplemental Evidence And Data for Systematic review (SEADS) portal and Federal Register Notice will be available for this review. We will ask the TEP to provide citations of potentially relevant articles and will screen any additional citations identified by the TEP and other experts and stakeholders during peer and public review. Additional articles suggested to us from any source, including peer and public review, will be screened with the same eligibility criteria as the studies identified in the database searches.

Per our EPC’s standard processes, we will take advantage of the machine learning capacities of Abstrackr (http://abstrackr.cebm.brown.edu/) to limit resources spent on abstract screening. We will train the machine learning algorithm as follows: (1) We will review the reference lists from known existing systematic reviews and clinical practice guidelines to identify potentially relevant studies for each KQ. (2) We will confirm this set of potentially relevant citations was successfully captured by our PubMed search. (3) Based on recently published work by Sampson et. al.,²⁵ we will select the top 500 articles from our search using PubMed's best-match algorithm. (4) The articles from steps (1) and (3) will be entered into Abstrackr and screened by all team members, with resolution of all conflicts in conference. (5) Subsequently, citations found by the full literature searches will be added to the already-screened citations in Abstrackr, and abstract screening will continue in duplicate, with conflicts adjudicated in conference or by a third screener. (6) As screening progresses, the pretrained Abstrackr machine learning algorithm will continue to adapt and will sort the list of unscreened abstracts such that the most potentially relevant articles are presented first. This process will make screening more efficient and will enable us to capture the preponderance of relevant articles relatively early in the abstract screening process. (7) We will stop double screening when the predicted likelihood of the remaining unscreened papers being relevant is very low. We typically use a threshold for the prediction score of the unscreened citations of 0.40 (this threshold is based on experience with several dozen screening projects and an analysis in preparation for publication but may be lowered depending on whether we continue to find eligible abstracts near the threshold). To confirm that the selected prediction score threshold is appropriate for this literature base, when the maximum prediction score is <0.40, we will screen at least 400 additional consecutive citations (this sample size is chosen because the upper 97.5% confidence interval bound for a proportion of 0/400 is less than 1%). If any of the 400 citations are screened in (at the abstract level), we will repeat the process (restart counting an additional 400 citations) until we have rejected at least 400 consecutive citations.

Potentially relevant citations will be retrieved in full text. Non-English language articles will be screened, and data extracted from full text, either by readers of the relevant languages or after translation via Google Translate (https://translate.google.com/), if possible. The search strategies for all databases will be peer reviewed by another experienced systematic review librarian. Searches will be updated during the draft report’s public posting period.

Evidence Map

Due to time and resource restrictions, for KQ 2 we plan to restrict synthesis within the full report to comparisons with three or more studies (with some possible exceptions, described below). Our logic is that these are the comparisons researchers have deemed to be of greatest interest and they are the comparisons we are most likely to be able to make conclusions about (beyond “insufficient evidence”). The restriction will reduce the need to spend resources on extracting and summarizing studies that will only lead to “insufficient” evidence. However, if we find comparisons with two studies, both of which are large (N≥100) and neither of which is at high risk of bias, we will include these in the full report. All treatment comparisons that meet criteria, regardless of number of studies, will be included in the appendix as an “evidence map” spreadsheet. The evidence map will provide a high-level overview of the evidence, including basic study design, size, population, intervention, and high-level effectiveness information. We will include the extractions for this spreadsheet to SRDRplus to allow it to be easily downloadable and searchable.

Data Extraction and Data Management

Data from eligible studies will be extracted into the Systematic Review Data Repository Plus (SRDR+) software. Each article will be extracted by one researcher and entered data will be confirmed by a second researcher. Individual studies with multiple publications will be extracted as a single study (with a single entry in SRDR+). Articles that report multiple studies will be entered into SRDR+ separately for each study.

For each study, we will extract publication data, study design features, population characteristics, intervention and comparator names and descriptions, relevant outcomes and their definitions, and funding source. All subgroup analyses or other evaluations of heterogeneity of treatment effect will be extracted.

Assessment of Quality and/or Methodological Risk of Bias of Individual Studies

We will evaluate each study for risk of bias and methodological quality during data extraction. Each study will be assessed by one researcher. Their assessments will be confirmed by a second researcher. Disagreements will be discussed in conference with the team or with the Lead.

For randomized controlled trials (RCTs), including cluster randomized trials, we will complete the Cochrane Risk of Bias tool,²⁶ which addresses issues related to randomization and allocation concealment; blinding; deviations from intended intervention; missing data; outcome measurement; and reporting biases. We will also evaluate the adequacy of descriptions of study participants, interventions, outcomes, and study designs. In addition, we will assess the adequacy of analyses. Questions related to outcome assessor blinding, missing data, outcome measurement reporting adequacy, and analytic adequacy will be assessed for each outcome.

For nonrandomized comparative studies, we will add assessments of specific elements from ROBINS-I²⁷ related to selection bias (comparability of groups) and relevant concepts addressed for RCTs (i.e., related to missing data, outcome measurement, analysis plan).²⁷ The questions will be assessed for each outcome (e.g., whether each outcome was adjusted for potential confounders).

For single arm studies, we assessed methodological quality using items from the Cochrane Risk of Bias Tool²⁶ that pertain to participant loss to follow up, incomplete outcome data, and selective outcome reporting, and items from the National Heart, Lung, and Blood Institute (NHLBI) Tool²⁸ that focus on the adequacy of descriptions of eligibility criteria, interventions, and outcomes. Treatment effect estimates from single arm trials will not be used to inform graded conclusions. We may use single arm trials to provide context for graded conclusions regarding applicability and feasibility of specific interventions or in specific populations. If available, we will extract and summarize evidence regarding predictors of within-arm treatment effects.

For single test diagnostic accuracy studies, we will assess specific elements from the QUADAS-2, and if needed, the QUADAS-C, for comparative diagnostic accuracy studies.^29-31

Data Synthesis

We will summarize the evidence both narratively and, when feasible, quantitatively.

Each study will be described in summary and evidence tables presenting study design features, study participant characteristics, descriptions of interventions, outcome results, and risk of bias/methodological quality. In text and tables, we will describe the characteristics of the study participants (particularly including those related to subgroups of interest) and features of the interventions (particularly including those related to regimen details). In extraction and summary of RCTs and NRCSs, we will preferentially include adjusted over crude analyses.

The specific metrics (summary effect measures) to be meta-analyzed will depend on available, reported study data. We will prefer continuous effect metrics on the original scale, rather than use standardized effect sizes, but may consider standardized effect sizes if necessary to allow comparisons across studies. Continuous metrics will be preferred over categorical metrics. If reported or estimable, we will analyze net mean differences (NMD; the difference between arms of the within-arm changes in outcome). Where appropriate or necessary, we will analyze mean differences between groups.

For diagnostic test studies, we will extract all relevant outcome measures (e.g., sensitivity, specificity, AUC ROC). If reported, we will extract relevant measures at all reported thresholds.

Where appropriate and feasible, we will conduct random-effects meta-analyses of comparative studies if at least three studies  are sufficiently similar in population, interventions, outcomes, and study design. For KQ 1, we will attempt to create summary ROC curves. For KQ 2, we will explore the possibility of conducting network meta-analyses of a widely reported outcome (e.g., CY-BOCS) to indirectly compare alternative treatment regimens across studies.

As feasible, we will describe reporting of differences in effects and harms by different factors, subgroups, or predictors. We expect to primarily rely on reported within-study differences in effects (or harms). However, we will look for opportunities to qualitatively and/or quantitatively summarize and/or compare results across studies.

Grading the Strength of Evidence for Prioritized Outcomes

Following AHRQ Methods guidance²³ the review team will consider the number of studies, their designs, limitations (i.e., risk of bias and overall methodological quality), the directness of the evidence to the KQs, the consistency of study results, the precision of any estimates of effect, the likelihood of reporting bias, other limitations, and the overall findings across studies, and will assign a consensus strength of evidence (SoE) rating of high, moderate, low, or insufficient to estimate an effect, addressing each prioritized outcome for each Key Question.

Outcomes with highly imprecise estimates (with 95% confidence intervals that extend beyond both 0.5 and 2.0 for categorical outcomes), highly inconsistent findings across studies (in terms of directions of effect), or with data from only one study were deemed to have insufficient evidence to allow for a conclusion (with the exception that a single particularly large, well-conducted, and generalizable single study could provide low SoE). This approach is consistent with the concept that for imprecise evidence “any estimate of effect is very uncertain,” which is the definition of Very low-quality evidence per the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) approach.³²

Assessing Applicability

For each Key Question, we will describe the applicability of the included studies primarily based on the studies’ eligibility criteria and their included participants. We will describe the populations to which the evidence may be most applicable and will highlight populations for whom the evidence may be less applicable.

1. Practice parameter for the assessment and treatment of children and adolescents with obsessive-compulsive disorder. J Am Acad Child Adolesc Psychiatry. 2012 Jan;51(1):98-113. doi: 10.1016/j.jaac.2011.09.019. PMID: 22176943.
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5. Piacentini J, Bergman RL, Keller M, et al. Functional impairment in children and adolescents with obsessive-compulsive disorder. J Child Adolesc Psychopharmacol. 2003;13 Suppl 1:S61-9. doi: 10.1089/104454603322126359. PMID: 12880501.
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7. Ezpeleta L, Keeler G, Erkanli A, et al. Epidemiology of psychiatric disability in childhood and adolescence. J Child Psychol Psychiatry. 2001 Oct;42(7):901-14. doi: 10.1111/1469-7610.00786. PMID: 11693585.
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10. Thomsen PH, Mikkelsen HU. Course of obsessive-compulsive disorder in children and adolescents: a prospective follow-up study of 23 Danish cases. J Am Acad Child Adolesc Psychiatry. 1995 Nov;34(11):1432-40. doi: 10.1097/00004583-199511000-00009. PMID: 8543510.
11. Krebs G, Heyman I. Obsessive-compulsive disorder in children and adolescents. Arch Dis Child. 2015 May;100(5):495-9. doi: 10.1136/archdischild-2014-306934. PMID: 25398447.
12. Boileau B. A review of obsessive-compulsive disorder in children and adolescents. Dialogues Clin Neurosci. 2011;13(4):401-11. doi: 10.31887/DCNS.2011.13.4/bboileau. PMID: 22275846.
13. Sharma E, Sharma LP, Balachander S, et al. Comorbidities in Obsessive-Compulsive Disorder Across the Lifespan: A Systematic Review and Meta-Analysis. Front Psychiatry. 2021;12:703701. doi: 10.3389/fpsyt.2021.703701. PMID: 34858219.
14. Silverman WK, Nelles WB. The Anxiety Disorders Interview Schedule for Children. J Am Acad Child Adolesc Psychiatry. 1988 Nov;27(6):772-8. doi: 10.1097/00004583-198811000-00019. PMID: 3198566.
15. Hudziak JJ, Althoff RR, Stanger C, et al. The Obsessive Compulsive Scale of the Child Behavior Checklist predicts obsessive-compulsive disorder: a receiver operating characteristic curve analysis. J Child Psychol Psychiatry. 2006 Feb;47(2):160-6. doi: 10.1111/j.1469-7610.2005.01465.x. PMID: 16423147.
16. Abramovitch A, Abramowitz JS, McKay D, et al. An ultra-brief screening scale for pediatric obsessive-compulsive disorder: The OCI-CV-5. J Affect Disord. 2022 Sep 1;312:208-16. doi: 10.1016/j.jad.2022.06.009. PMID: 35697331.
17. Nelson EC, Hanna GL, Hudziak JJ, et al. Obsessive-compulsive scale of the child behavior checklist: specificity, sensitivity, and predictive power. Pediatrics. 2001 Jul;108(1):E14. doi: 10.1542/peds.108.1.e14. PMID: 11433093.
18. Endres D, Pollak TA, Bechter K, et al. Immunological causes of obsessive-compulsive disorder: is it time for the concept of an "autoimmune OCD" subtype? Transl Psychiatry. 2022 Jan 10;12(1):5. doi: 10.1038/s41398-021-01700-4. PMID: 35013105.
19. Susan E. Swedo, James F. Leckman, Rose NR. From Research Subgroup to Clinical Syndrome: Modifying the PANDAS Criteria to Describe PANS (Pediatric Acute-onset Neuropsychiatric Syndrome). Pediatr Therapeut. 2012;2(2). doi: 10.4172/2161-0665.1000113.
20. Jaspers-Fayer F, Han SHJ, Chan E, et al. Prevalence of Acute-Onset Subtypes in Pediatric Obsessive-Compulsive Disorder. J Child Adolesc Psychopharmacol. 2017 May;27(4):332-41. doi: 10.1089/cap.2016.0031. PMID: 28121463.
21. Wilbur C, Bitnun A, Kronenberg S, et al. PANDAS/PANS in childhood: Controversies and evidence. Paediatr Child Health. 2019 May;24(2):85-91. doi: 10.1093/pch/pxy145. PMID: 30996598.
22. Freeman J, Benito K, Herren J, et al. Evidence Base Update of Psychosocial Treatments for Pediatric Obsessive-Compulsive Disorder: Evaluating, Improving, and Transporting What Works. J Clin Child Adolesc Psychol. 2018 Sep-Oct;47(5):669-98. doi: 10.1080/15374416.2018.1496443. PMID: 30130414.
23. Farhat LC, Vattimo EFQ, Ramakrishnan D, et al. Systematic Review and Meta-analysis: An Empirical Approach to Defining Treatment Response and Remission in Pediatric Obsessive-Compulsive Disorder. J Am Acad Child Adolesc Psychiatry. 2022 Apr;61(4):495-507. doi: 10.1016/j.jaac.2021.05.027. PMID: 34597773.
24. AHRQ Methods for Effective Health Care. Rockville (MD): Agency for Healthcare Research and Quality (US); 2017. https://effectivehealthcare.ahrq.gov/products/collections/cer-methods-guide. Accessed on August 15 2023.
25. Sampson M, Nama N, O'Hearn K, et al. Creating enriched training sets of eligible studies for large systematic reviews: the utility of PubMed's Best Match algorithm. Int J Technol Assess Health Care. 2020 Dec 18;37:e7. doi: 10.1017/S0266462320002159. PMID: 33336640.
26. Higgins JP, Altman DG, Gøtzsche PC, et al. The Cochrane Collaboration's tool for assessing risk of bias in randomised trials. Bmj. 2011 Oct 18;343:d5928. doi: 10.1136/bmj.d5928. PMID: 22008217.
27. Sterne JA, Hernán MA, Reeves BC, et al. ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions. Bmj. 2016 Oct 12;355:i4919. doi: 10.1136/bmj.i4919. PMID: 27733354.
28. National Heart, Lung, and Blood Institute. Study Quality Assessment Tools. 2013. https://www.nhlbi.nih.gov/health-topics/study-quality-assessment-tools. Accessed on July 8 2023.
29. Whiting P, Rutjes AW, Dinnes J, et al. Development and validation of methods for assessing the quality of diagnostic accuracy studies. Health Technol Assess. 2004 Jun;8(25):iii, 1-234. doi: 10.3310/hta8250. PMID: 15193208.
30. Whiting P, Rutjes AW, Reitsma JB, et al. The development of QUADAS: a tool for the quality assessment of studies of diagnostic accuracy included in systematic reviews. BMC Med Res Methodol. 2003 Nov 10;3:25. doi: 10.1186/1471-2288-3-25. PMID: 14606960.
31. Whiting PF, Rutjes AW, Westwood ME, et al. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med. 2011 Oct 18;155(8):529-36. doi: 10.7326/0003-4819-155-8-201110180-00009. PMID: 22007046.
32. Guyatt GH, Oxman AD, Kunz R, et al. Going from evidence to recommendations. BMJ. 2008 May 10;336(7652):1049-51. doi: 10.1136/bmj.39493.646875.AE. PMID: 18467413.

If we need to amend this protocol, we will give the date of each amendment, describe each change and give the rationale in this section.

The Agency for Healthcare Research and Quality (AHRQ) posted the Key Questions on the AHRQ Effective Health Care Website for public comment. The Evidence-based Practice Center (EPC) refined and finalized them after reviewing the public comments and seeking input from Key Informants (KIs).

KIs are end users of research, including patients and caregivers, practicing clinicians, relevant professional and consumer organizations, purchasers of health care, and others with a role in making health care decisions. Within the EPC program, the KIs’ role is to provide input into refining the Key Questions for research that will inform healthcare decisions. The EPC solicits input from KIs when refining questions for systematic review. KIs are not involved in analyzing the evidence or writing the report and have not reviewed the report, except as given the opportunity to do so through the peer or public review mechanism.

KIs must disclose any financial conflicts of interest greater than $5,000 and any other relevant business or professional conflicts of interest. Drawing upon their roles as end-users, diverse individuals are invited to serve as KIs. Those who present with potential conflicts can be retained although the TOO and the EPC work to balance, manage, or mitigate any potential conflicts of interest identified.

Technical Experts constitute a multi-disciplinary group of clinical, content, and methodological experts who provide input in defining populations, interventions, comparisons, or outcomes. The Technical Expert Panel is selected to provide broad expertise and perspectives specific to the topic under development. Divergent and conflicting opinions are common and perceived as healthy scientific discourse that fosters the completion of a thoughtful, relevant systematic review. As such, study questions, design, and methodological approaches do not necessarily represent the views of individual technical and content experts.

Technical Experts provide further input to finalize the KQs, study eligibility criteria, and analysis plans. The Technical Experts provide feedback on the full protocol. They provide information to the EPC to identify literature search strategies and suggest approaches to specific issues as requested by the EPC. They may help to identify particular studies or databases to search for studies to be included in the review. Technical Experts do not do analysis of any kind; neither do they contribute to the writing of the report. They do not review the report, except as given the opportunity to do so through the peer or public review mechanism.

Members of the TEP must disclose any financial conflicts of interest greater than $5,000 and any other relevant business or professional conflicts of interest. Because of their unique clinical or content expertise, individuals are invited to serve as Technical Experts and those who present with potential conflicts may be retained although the AHRQ TOO and the EPC work to balance, manage, or mitigate any potential conflicts of interest identified.

Peer reviewers are invited to provide written comments on the draft report based on their clinical, content, or methodological expertise. The EPC considers all peer review comments on the draft report in preparation of the final report. Peer reviewers do not participate in writing or editing of the final report or other products. The final report does not necessarily represent the views of individual reviewers. The EPC will complete a disposition of all peer review comments. The disposition of comments for systematic reviews and technical briefs will be published three months after the publication of the evidence report.

Potential Peer Reviewers must disclose any financial conflicts of interest greater than $5,000 and any other relevant business or professional conflicts of interest. Invited Peer Reviewers may not have any financial conflict of interest greater than $5,000. Peer reviewers who disclose potential business or professional conflicts of interest may submit comments on draft reports through the public comment mechanism.

EPC core team members must disclose any financial conflicts of interest greater than $1,000 and any other relevant business or professional conflicts of interest. Related financial conflicts of interest that cumulatively total greater than $1,000 will usually disqualify EPC core team investigators from participation in the review.

This project is funded by the Patient-Centered Outcomes Research Institute (PCORI) and executed under AHRQ, U.S. Department of Health and Human Services through Contract Nos. 75Q80120D00001/75Q80123F32010 (Task Order #10). The TOO will review contract deliverables for adherence to contract requirements and quality. The authors of this report will be responsible for its content. Statements in the report should not be construed as endorsement by PCORI, AHRQ, or the U.S. Department of Health and Human Services.

This protocol will be registered in the international prospective register of systematic reviews (PROSPERO).