Datasets:

marianna13
/

litarch

+{"file": "cer148_NBK274474/abbreviations.s1.nxml", "text": "American College of Rheumatology\nAdverse effects\nAllied and Complementary Medicine\nAnkylosing spondylitis\nBeck Depression Inventory\nBrief Pain Inventory\nBody Mass Index\nComplementary and alternative medicine\nCochrane Central Register of Controlled Trials\nComparative effectiveness review\nClinical Global Impression of Severity Scale\nElectromyography\nEuroQol health outcomes assessment\nErythrocyte Sedimentation Rate\nFood and Drug Administration\nFibromyalgia Impact Questionnaire\nRevised FIQ\nFibromyalgia\nGeneralized Anxiety Disorder\nGastrointestinal\nHamilton Rating Scale for Depression\nHealth-related quality of life\nIrritable Bowel Syndrome\nIndividual patient data\nInternational Controlled Trial Registry Platform\nMultidimensional Assessment of Fatigue\nMinimum Clinically Important Difference\nMajor Depressive Disease\nMedical subject headings\nMedical Outcomes Study sleep scale\nMultidimensional Fatigue Inventory\nMinnesota Multiphasic Personality Inventory\nMultidisciplinary Treatment\nNot Reported\nNon White\nOsteoarthritis\nPatient\u2019s Global Assessment of Response to Therapy\nPatient Global Impression of Change Score\nPatient Global Impression of Improvement Scale\nPopulation, Intervention, Comparator, Outcomes, Timing, Setting\nPittsburgh Sleep Quality Index\nQuality of Life\nRheumatoid arthritis\nRandomized controlled trial\nSymptom Checklist-90-Revised\nSheehan Disability Scale\nMOS Short-Form 36-item Health Survey\nLupus\nSelective Serotonin Reuptake Inhibitors\nSerotonin Nor-epinephrine Reuptake Inhibitors\nWhite\nVisual Analogue Scale", "pairs": [], "interleaved": []}
+{"file": "cer148_NBK274474/fm.ack.nxml", "text": "The authors wish to thank Uzoma Abakporo and Nathan Carter, who served as research assistants on this project, and Marilyn Eells and Jeannine Ouellette for their assistance in editing the report.", "pairs": [], "interleaved": []}
+{"file": "cer148_NBK274474/fm.s2.nxml", "text": "In designing the study questions, the EPC consulted several Key Informants who represent the end-users of research. The EPC sought Key Informant input on the priority areas for research and synthesis. Key Informants are not involved in the analysis of the evidence or the writing of the report. Therefore, in the end, study questions, design, methodological approaches, and/or conclusions do not necessarily represent the views of individual Key Informants.\nKey Informants must disclose any financial conflicts of interest greater than $10,000 and any other relevant business or professional conflicts of interest. Because of their role as end-users, individuals with potential conflicts may be retained. The TOO and the EPC work to balance, manage, or mitigate any conflicts of interest.\nThe list of Key Informants who participated in developing this report follows:\nJason Busse, D.C., Ph.D.\nMcMaster University\nHamilton, ON, Canada\nAkiko Okifuji, Ph.D.\nUniversity of Utah\nSalt Lake City, UT\nLinda M. Torma, Ph.D., A.P.R.N.,\nG.C.N.S.-B.C.\nMontana State University\nBozeman, MT\nAnn Vincent, M.D.\nMayo Clinic\nRochester, MN", "pairs": [], "interleaved": []}
+{"file": "cer148_NBK274474/appc.nxml", "text": "\n\nRCT Risk of bias assessment: Fibromyalgia subgroup studies\n\nPooled individual patient data RCTs risk of bias assessment: Fibromyalgia subgroup studies", "pairs": [["litarch_figures_28/08/5b/cer148_NBK274474/appcfm1.jpg", "", ""], ["litarch_figures_28/08/5b/cer148_NBK274474/appcfm2.jpg", "\nRCT Risk of bias assessment: Fibromyalgia subgroup studies\n", ""], ["litarch_figures_28/08/5b/cer148_NBK274474/appcfm3.jpg", "\nPooled individual patient data RCTs risk of bias assessment: Fibromyalgia subgroup studies\n", ""]], "interleaved": [["litarch_figures_28/08/5b/cer148_NBK274474/appcfm1.jpg", "", ""], ["litarch_figures_28/08/5b/cer148_NBK274474/appcfm2.jpg", "\nRCT Risk of bias assessment: Fibromyalgia subgroup studies\n", ""], ["RCT Risk of bias assessment: Fibromyalgia subgroup studies"], ["litarch_figures_28/08/5b/cer148_NBK274474/appcfm3.jpg", "\nPooled individual patient data RCTs risk of bias assessment: Fibromyalgia subgroup studies\n", ""], ["Pooled individual patient data RCTs risk of bias assessment: Fibromyalgia subgroup studies"]]}
+{"file": "cer148_NBK274474/methods.nxml", "text": "We followed the methods suggested in the AHRQ \u201cMethods Guide for Effectiveness and Comparative Effectiveness Reviews\u201d for this comparative effectiveness review (CER) follow (available at www.effectivehealthcare.ahrq.gov/methodsguide.cfm). The main sections below reflect the elements of the protocol established for this CER; certain methods map to the PRISMA checklist.\nTopic Refinement and Review Protocol\nThe topic of this report and preliminary Key Questions arose through a public process that involved a topic nomination by a consumer, followed by refinement of the research questions with input from various stakeholder groups, including professionals from the disciplines of rheumatology, psychology, psychiatry, physical therapy, nursing, gerontology, chiropractic, and outcomes research. We used a preliminary literature scan and expert input to determine which subgroups to address a priori in this review.\nThe draft Key Questions were posted for public comment on AHRQ\u2019s Effective Health Care website from October 25, 2013, through November 14, 2013. Based on that feedback, minor revisions were made to the analytic framework (added symptom improvement as a final outcome, deleted intermediate outcomes as not salient to this topic), and PICOTS (limited treatment to noninpatient settings). We then drafted a protocol for the review and recruited a panel of technical experts to provide high-level content and methodological expertise during the development of the review. The Key Informants and members of the TEP were required to disclose any financial conflicts of interest greater than $10,000 and any other relevant business or professional conflicts. Any potential conflicts of interest were balanced or mitigated. Neither Key Informants nor members of the TEP performed analysis of any kind, nor did any of them contribute to the writing of this report. Members of the TEP were invited to provide feedback on an initial draft of the review protocol which was then refined based on their input, reviewed by AHRQ, and posted for public access on the AHRQ Effective Health Care Website.\nLiterature Search Strategies\nWe searched Ovid MEDLINE\u00ae, Embase\u00ae, Ovid PsycINFO\u00ae, AMED (Allied and Complementary Medicine) and the Cochrane Central Register of Controlled Trials (CENTRAL) bibliographic databases to identify randomized controlled trials, systematic reviews, and observational studies with control groups published from 1985 to August 2014 on treatments for adults with fibromyalgia. CINAHL was excluded from our search; it was unlikely to provide additional subgroup studies beyond the five databases we searched.66,67\nOur search strategies are included in Appendix B. An experienced librarian in the Minnesota EPC developed the MEDLINE search strategy; we modified the search for other databases. The search strategy used relevant Medical Subject Headings (MeSH\u00ae) and natural language terms to identify two fibromyalgia concepts: (1) fibromyalgia, fibrositis and myofascial pain syndrome, and (2) specific filters to identify study designs. We supplemented bibliographic database searches with backward citation searches of highly relevant systematic reviews.\nInclusion and Exclusion Criteria\nIncluded\nSince fibromyalgia is a chronic condition in adults, we limited our analysis to studies of individuals age 18 or older that compared treatments for fibromyalgia in subgroups of adults who were followed 3 months or longer after treatment initiation. We included randomized controlled trials (RCTs), pooled analyses of individual patient-level RCT data, and observational studies that examined one or more treatments for fibromyalgia in adults, utilized a comparator group, and reported treatment outcomes in at least one subgroup 12 or more weeks after the initiation of treatment. RCTs of mixed samples (not pure subgroups) provided direct outcome comparisons. Pure subgroup populations (the study was designed to sample from the subgroup) were also included for indirect evidence. We included clinical studies that were published from 1985 to August 2014 in the English language. The possibility that non-English language studies would have tested treatments that were FDA approved or used in the United States, and reported on subgroups is remote.68-70\nExcluded\nWe excluded studies: of drugs not FDA approved in the United States for any condition; that included patients with different health conditions and did not separately report baseline and outcomes in fibromyalgia patients; that did not use established fibromyalgia diagnostic criteria for subject selection (American College of Rheumatology [ACR]13-15 or Yunus55 criteria for fibrositis from 1985\u20131990); or pharmacologic RCTs where patients were unblinded to treatment for any part of the study. Studies that did not examine patient-important outcomes (such as brain imaging or lab studies) were excluded. For drug trials, we excluded randomized controlled trials where patients were unblinded to treatment for any part of the clinical study or followup or where the blinding status of patients to treatment was unclear or conflicted in the article text.\nStudy Selection\nTwo independent investigators reviewed titles and abstracts that resulted from the bibliographic database searches to identify studies that examined interventions for fibromyalgia in adults. Citations deemed as potentially eligible by either investigator underwent full text screening for possible subgroup reporting. Study selection involved an extensive full text review process to identify adult subgroups, since subgroup reporting was usually not evident in titles and abstracts. Full text articles were initially reviewed to identify outcomes reporting for at least one adult subgroup. Differences in screening decisions were resolved through discussions; when needed, a third investigator was consulted until consensus was achieved.\nWe conducted additional grey literature searches to identify relevant completed and ongoing clinical studies. Grey literature search results were also used to identify studies, outcomes, and analyses not reported in the published literature. We searched ClinicalTrials.gov and the International Controlled Trials Registry Platform (ICTRP) for studies that specified a fibromyalgia subgroup analysis in their study protocol. We also reviewed Scientific Information Packets sent by manufacturers to AHRQ for recent information on relevant pharmaceuticals and other interventions.\nData Extraction\nOne investigator trained in research methodology extracted relevant study, population, risk of bias, and outcomes data. Initial data abstraction was quality checked by a second trained investigator. Data fields were determined based upon the proposed summary analysis. These fields included author, year of publication, setting, fibromyalgia diagnostic and severity criteria used, subject inclusion and exclusion criteria, subgroup, intervention(s), allowed and disallowed co-interventions, control characteristics (intervention delivery, timing, frequency, duration), treatment and followup duration, participant baseline demographics, comorbidities, descriptions and results of primary outcomes and adverse effects, results of treatment-by-subgroup interactions, within-stratum primary outcomes when subgroup interaction results were lacking for a given comparison, and study funding source. Data were entered into Excel spreadsheets by one trained investigator and checked for accuracy by a second.\nFor pooled RCT analyses of drug trial data, we examined the pooled study and the input RCTs that comprised the pooled sample to assure nonoverlap of our subsequent reporting of subgroup-treatment-outcomes in this review.\nQuality (Risk-of-Bias) Assessment of Individual Studies\nThe risk of bias of eligible studies was assessed by two independent investigators using instruments specific to each study design (Appendix C). The two investigators consulted to reconcile any discrepancies in overall risk of bias assessments and, when needed, a third investigator was consulted to reconcile the summary judgment.\nFor RCTs, we assessed the risk of bias using a modified Cochrane Risk of Bias tool.71 The seven domains of the tool are sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessment, incomplete outcome data, selective reporting, and other sources of bias (i.e., problems not covered by other domains). We also evaluated potential risk of bias associated with treatment definition. We included additional items to assess the credibility of subgroup analyses of individual RCTs with mixed patient samples based on Sun et al.72 These guidelines were: if the subgroup variable was measured at baseline, if the subgroup hypothesis was a priori, if the study included only a small number of subgroup hypotheses, if the interaction test suggests a low likelihood of chance explanation, among other contextual issues.72\nOverall summary risk of bias assessments for each study were classified as low, moderate, or high based upon the collective risk of bias inherent in each domain and confidence that the results are believable given the study\u2019s limitations.71 A consolidating algorithm was not used. Elements that contributed to a low risk of bias assessment included whether a study used a random sequence generation, concealed allocation of treatment assignments, blinded outcomes assessors, demonstrated treatment fidelity, had minimal to modest missing outcomes data or balanced missing data across groups with similar reasons for missing data, and credible subgroup analysis methods.71 High risk of bias elements include nonrandom sequence generation, lack of blinding of outcomes assessors when the outcome was likely to be affected by the lack of blinding, or high and/or differential losses to followup across treatment groups when missing outcomes data may have been related to real outcomes. Moderate risk of bias was assigned to studies that were challenged across several of the domains but the study was blinded or, if blinding was not possible, outcome assessors were blinded to treatment assignment. The potential for placebo effects in fibromyalgia treatments is high, thus special weight was given to the blinding domain.\nWe developed an instrument to assess risk of bias for observational studies using the RTI Observational Studies Risk of Bias and Precision Item Bank73 because concerns about selection bias and blinding make the use of observational studies debatable in comparative effectiveness reviews. We selected items most relevant in assessing risk of bias from observational studies of fibromyalgia and to foster consistency with the risk of bias instrument for randomized controlled trials71 Bias issues common to observational studies involve the nonrandom selection of subjects, the completeness and validity of the recording of baseline patient information, attrition, and the ascertainment of outcomes. Items included from the RTI Item Bank addressed participant selection, group membership, efforts to address selection bias, identification of baseline effect modifiers and confounders, and appropriateness of analytic methods for observational studies. We classified the overall summary risk of bias assessments for each individual study as low, moderate, or high based on the collective risk of bias inherent in each outcome domain and confidence that the results are believable given the study\u2019s limitations. Similar to risk of bias for RCTs, the overall summary risk of bias was weighted towards low for studies that demonstrated comparability across groups. Moderate risk of bias would have been assigned to large cohort studies with a sample size for adequate power to detect differences, moderate to large effect sizes, and strong evidence of attempting to control for plausible confounders.\nWe paid special attention to risk of bias assessment for observational studies that pooled patient-level data from randomized controlled trials. Risk of bias of pooled analyses depended in part on the risk of bias of the inputs (RCTs) and the risk of bias in how the pooled analysis was conducted and reported. The risk of bias of the individual RCTs that comprise each pooled analysis was assessed per the Cochrane tool as described above.71,72 The additional risk of bias in how the pooled analysis was conducted was assessed using the critical appraisal by Fisher et al.74 of the principal methods for pooling individual-level RCT data to determine treatment-covariate interactions in the literature. Only within-trial patient-level interactions were considered as across-trial information has a higher risk of bias.74\nThe risk of bias and quality assessment forms are included in Appendix C.\nData Synthesis\nWe summarized the results into evidence tables and qualitatively synthesized evidence by the type of study (RCT, observational, pooled individual patient data [IPD] RCT analyses) for each unique population, comparison, and outcome combination within specific followup time periods. Because of the high probability of placebo effects in fibromyalgia treatments, if subgroup analysis was available through an RCT or pooled RCT literature for a given subgroup-treatment-outcome comparison, the observational literature was not included in the analytic set for that comparison. Studies were grouped by study design, intervention category and then subgroup.\nWe summarized patient-centered subgroup outcomes comparisons72 for pain, global improvement, function, fatigue, and quality of life. Pooling was planned for measures that assessed the same outcome and had comparable scoring characteristics (such as the FIQ59 and FIQR60 tools). However, quantitative meta-analysis with pooling of data was not possible due to differences in subgroup-treatment-outcome combinations.\nWherever possible, we report data and/or interaction results that assessed whether treatment effects varied in subgroups. If interaction results were not reported and data were presented for within-stratum results (such as stratum-specific change from baseline in pain in those with MDD (treated vs. control) and for those without MDD (treated vs. control), we identify and report within-stratum information.\nWhen available in the literature, we identified minimal clinically important outcomes differences for measures specific to fibromyalgia patients. Additionally, when subgroup data were provided, we calculated the difference in mean change from baseline between treated and control groups by subgroup strata as a general measure of magnitude of the treatment effect relative to the placebo (control) group.\nStrength of the Body of Evidence\nWe evaluated the overall strength of evidence for select clinical outcomes within each comparison based on four domains: (1) study limitations (internal validity); (2) directness (single, direct link between the intervention and outcome); (3) consistency (similarity of effect direction and size); and (4) precision (degree of certainty around an estimate), with the study limitations domain having considerable importance.75 Study limitations were rated as low, moderate, or high according to study design and conduct. Consistency was rated as consistent, inconsistent, or unknown/not applicable (e.g., single study), based on direction and magnitude of effect. Directness was rated as either direct or indirect based on outcome and study design. Precision was rated as precise or imprecise based on the number of patients needed for an evidence base to be adequately powered. We required the existence of at least two studies (which could be high risk of bias) to assign low rather than insufficient strength of evidence. We required at least one low risk of bias study for moderate strength of evidence and two low risk of bias studies for high strength of evidence. In addition, to be considered moderate or higher, intervention-outcome pairs need a positive response on two out of the three domains other than risk of bias. Based on these factors, the possible SOE grades were:75\nHigh. Very confident that the estimate of effect lies close to the true effect. Few or no deficiencies in body of evidence; findings believed to be stable.\nModerate. Moderately confident that the estimate of effect lies close to true effect. Some deficiencies in body of evidence; findings likely to be stable but some doubt.\nLow. Limited confidence that estimate of effect lies close to true effect; major or numerous deficiencies in body of evidence. Additional evidence necessary before concluding that findings are stable or that estimate of effect is close to true effect.\nInsufficient. No evidence, unable to estimate and effect, or no confidence in estimate of effect. No evidence is available or the body of evidence precludes judgment.\nApplicability\nApplicability of studies was determined according to the PICOTS (populations, interventions, comparators, outcomes, timing, settings) framework. Study characteristics that could affect applicability include, but are not limited to, changes in the diagnostic criteria over time (1990 vs. 2010), narrow inclusion criteria, or patient and intervention characteristics different than those described by population studies of fibromyalgia treatments. Importantly, adults in clinical trials of fibromyalgia treatments may be higher functioning, less impaired, and have fewer or less severe concomitant medical or mental health conditions than the fibromyalgia patient population as a whole, which impacts the generalizability of clinical trial results to the broader fibromyalgia population.", "pairs": [], "interleaved": []}
+{"file": "cer148_NBK274474/appe.nxml", "text": "Sample selection criteria and allowed co-interventions for included fibromyalgia randomized clinical trials\nSample selection criteria and allowed co-interventions for included pooled studies of patient-level randomized clinical trial data\nSample selection criteria and allowed co-interventions for included fibromyalgia observational studies\nFibromyalgia randomized clinical trials with subgroups and mixed samples, by class of treatment\nFibromyalgia randomized clinical trials with pure subgroup samples, by class of treatment\nFibromyalgia pooled studies of patient-level RCT data with subgroup reporting, by pharmacologic treatment\nFibromyalgia observational studies with subgroups, by class of treatment\nSubgroup outcomes reported in the fibromyalgia randomized clinical trial literature\nSubgroup outcomes reported in pooled randomized clinical trial analyses and observational studies\nFibromyalgia risk of bias summary for RCTs: mixed samples and pure subgroups\nFibromyalgia risk of bias summary for observational studies\nQuality issues and risk of bias summary for pooled analyses of patient-level randomized clinical trial data on fibromyalgia subgroups\nFunding source and corresponding author information in fibromyalgia randomized clinical trials, mixed samples\nFunding source and corresponding author information in fibromyalgia randomized clinical trials with pure subgroup samples\nFunding source and corresponding author information in fibromyalgia pooled studies of individual patient data from randomized clinical trials\nFunding source and corresponding author information in fibromyalgia observational studies\nJustification for retaining potentially overlapping individual RCTs and associated pooled patient-level data duloxetine studies that differed in outcome or timing of outcome assessment", "pairs": [], "interleaved": []}
+{"file": "cer148_NBK274474/fm.s4.nxml", "text": "Prior to publication of the final evidence report, EPCs sought input from independent Peer Reviewers without financial conflicts of interest. However, the conclusions and synthesis of the scientific literature presented in this report do not necessarily represent the views of individual reviewers.\nPeer Reviewers must disclose any financial conflicts of interest greater than $10,000 and any other relevant business or professional conflicts of interest. Because of their unique clinical or content expertise, individuals with potential nonfinancial conflicts may be retained. The TOO and the EPC work to balance, manage, or mitigate any potential nonfinancial conflicts of interest identified.\nThe list of Peer Reviewers follows:\nBrian T. Walitt, M.D., M.P.H.\nSchool of Medicine\nGeorgetown University\nWashington, DC\nL. Susan Wieland, Ph.D.\nCenter for Integrative Medicine\nUniversity of Maryland\nBaltimore, MD\nDavid A. Williams, Ph.D.\nDepartment of Anesthesiology\nUniversity of Michigan\nAnn Arbor, MI\nFrederick Wolfe, M.D.\nNational Data Bank for Rheumatic Diseases\nWichita, KS", "pairs": [], "interleaved": []}
+{"file": "cer148_NBK274474/fm.s1.nxml", "text": "The Agency for Healthcare Research and Quality (AHRQ), through its Evidence-based Practice Centers (EPCs), sponsors the development of systematic reviews to assist public- and private-sector organizations in their efforts to improve the quality of health care in the United States. These reviews provide comprehensive, science-based information on common, costly medical conditions, and new health care technologies and strategies.\nSystematic reviews are the building blocks underlying evidence-based practice; they focus attention on the strength and limits of evidence from research studies about the effectiveness and safety of a clinical intervention. In the context of developing recommendations for practice, systematic reviews can help clarify whether assertions about the value of the intervention are based on strong evidence from clinical studies. For more information about AHRQ EPC systematic reviews, see www.effectivehealthcare.ahrq.gov/reference/purpose.cfm.\nAHRQ expects that these systematic reviews will be helpful to health plans, providers, purchasers, government programs, and the health care system as a whole. Transparency and stakeholder input are essential to the Effective Health Care Program. Please visit the Web site (www.effectivehealthcare.ahrq.gov) to see draft research questions and reports or to join an email list to learn about new program products and opportunities for input.\nWe welcome comments on this systematic review. They may be sent by mail to the Task Order Officer named below at: Agency for Healthcare Research and Quality, 540 Gaither Road, Rockville, MD 20850, or by email to \n\nRichard G. Kronick, Ph.D.\nDirector\nAgency for Healthcare Research and Quality\nStephanie Chang, M.D., M.P.H.\nDirector, EPC Program\nCenter for Evidence and Practice Improvement\nAgency for Healthcare Research and Quality\nDavid Meyers, M.D.\nActing Director\nCenter for Evidence and Practice Improvement\nAgency for Healthcare Research and Quality\nSuchitra Iyer, Ph.D.\nTask Order Officer\nCenter for Evidence and Practice Improvement\nAgency for Healthcare Research and Quality", "pairs": [], "interleaved": []}
+{"file": "cer148_NBK274474/fm.s3.nxml", "text": "In designing the study questions and methodology at the outset of this report, the EPC consulted several technical and content experts. Broad expertise and perspectives were sought. Divergent and conflicted opinions are common and perceived as healthy scientific discourse that results in a thoughtful, relevant systematic review. Therefore, in the end, study questions, design, methodologic approaches, and/or conclusions do not necessarily represent the views of individual technical and content experts.\nTechnical Experts must disclose any financial conflicts of interest greater than $10,000 and any other relevant business or professional conflicts of interest. Because of their unique clinical or content expertise, individuals with potential conflicts may be retained. The TOO and the EPC work to balance, manage, or mitigate any potential conflicts of interest identified.\nThe list of Technical Experts who participated in developing this report follows:\nJason Busse, D.C., Ph.D.\nMcMaster University\nHamilton, ON, Canada\nRoger Chou, M.D.\nOregon Health & Science University\nPortland, OR\nEdward C. Covington, M.D.\nCleveland Clinic\nCleveland, OH\nDon L. Goldenberg, M.D.\nTufts University School of Medicine\nNewton, MA\nKim Dupree Jones, R.N.C., Ph.D., FNP\nOregon Health & Science University\nPortland, OR\nRobert D. Kerns, Ph.D.\nVA Connecticut Healthcare System\nYale University\nWest Haven, CT\nAkiko Okifuji, Ph.D.\nUniversity of Utah\nSalt Lake City, UT\nLinda M. Torma, Ph.D., A.P.R.N.,\nG.C.N.S.-B.C.\nMontana State University\nBozeman, MT", "pairs": [], "interleaved": []}