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"screening"

Slides: 1–12 of 63

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Overview: Methods

Presentation: Clostridium difficile Infections: Diagnosis, Treatment, and Prevention

Keywords: analysis | data sources | literature | methods | overview

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Rating the Strength of Evidence From the CER

Presentation: Analgesics for Osteoarthritis—An Update

Keywords: comparative effectiveness | strength of evidence | systematic review | methods

This figure shows a sample working framework. It begins on the left side with persons at risk. A solid arrow labeled “Screening” leads to a round-edged rectangle that represents “Early Detection of a Target Condition.” A curvy arrow leads down to an oval representing “Adverse Effects of Screening.” A solid arrow labeled “Treatment” leads right from the first box to another round-edged rectangle representing “Intermediate Outcomes.” Another curvy arrow leads down to an oval representing “Adverse Effects of Treatment.” Finally, a dotted line leads from the “Intermediate Outcomes” box to a sharp-edged box that represents the ultimate health outcome: “Reduced Morbidity and/or Mortality.”

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Sample Working Framework

Presentation: Analytic Frameworks

Keywords: systematic review | analytic framework

This framework begins with a box representing “Women presenting with symptoms of OAB”, which is also labeled “Population” for the PICOTS (population, intervention, comparators, outcomes, timing, and setting) domain. An arrow labeled “History/Clinical exam” leads from this box to a diamond labeled “Testing.” Arrows lead to a box labeled “Further evaluation” and another labeled “None.” Arrows lead from each box to a diamond labeled “Diagnosis.” An arrow leads from this diamond back to the “Testing” diamond. All of the boxes and diamonds listed so far are contained by a bracket labeled “Key Question 1.” An arrow leads from “Diagnosis” to another diamond labeled “Treatment Choice,” which is also labeled “Intervention” for PICOTS and Key Question 5. An arrow leads from “Treatment Choice” to a box labeled “Treatment approach.” An arrow labeled “Key Question 2 & Key Question 3” leads from “Treatment Approach” to a box containing outcomes. This box is labeled “Outcomes” for the PICOTS domain. An arrow leads from the outcomes box to the “Testing” diamond, indicating that the process can be repeated. The entire framework is framed by “Health care system” modifiers at the top, and “KQ4 Individual characteristics” at the bottom.

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Sample Screening and Treatment Framework

Presentation: Analytic Frameworks

Keywords: PICOTS | population | intervention | outcome

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Background: Using Serological Tests To Diagnose Musculoskeletal Pain

Presentation: Antinuclear Antibody, Rheumatoid Factor, and Cyclic-Citrullinated Peptide Testing for the Evaluation of Musculoskeletal Complaints in Pediatric Populations

Keywords: musculoskeletal pain | diagnosis | patient history | physical examination | pain pattern | serological tests | antinuclear antibody | rheumatoid factor | cyclic-citrullinated peptide

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Background: Antinuclear Antibody Test

Presentation: Antinuclear Antibody, Rheumatoid Factor, and Cyclic-Citrullinated Peptide Testing for the Evaluation of Musculoskeletal Complaints in Pediatric Populations

Keywords: antinuclear antibody test | ANA testing | autoimmune conditions | systemic lupus erythematosus | Sjögrens syndrome | systemic sclerosis | indirect immunofluorescence | enzyme immunoassay | ELISA

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Conclusions (1 of 2)

Presentation: Antinuclear Antibody, Rheumatoid Factor, and Cyclic-Citrullinated Peptide Testing for the Evaluation of Musculoskeletal Complaints in Pediatric Populations

Keywords: adolescents | age | children | clinical assessment | juvenile idiopathic arthritis | noninflammatory pain | prevalence | sex | test sensitivity | test specificity | musculoskeletal pain

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Conclusions (2 of 2)

Presentation: Antinuclear Antibody, Rheumatoid Factor, and Cyclic-Citrullinated Peptide Testing for the Evaluation of Musculoskeletal Complaints in Pediatric Populations

Keywords: antinuclear antibody | clinical assessment | connective tissue disease | cyclic-citrullinated peptide | inflammatory arthritis | rheumatoid factor | serological tests | study limitations | methodology

Population and Applicability: Examples. In a trial of women with osteoporosis, only 4,000 of the 54,000 women screened were enrolled; the enrollees were younger, healthier, and more adherent to therapy than is typical of women with osteoporosis. A trial of etanercept for juvenile diabetes excluded patients with side effects during an active run-in period; the trial found a low incidence of adverse events. Clinical trials used to inform Medicare decisions enrolled patients who were younger (60 vs. 75 years of age) and more often male (75 vs. 42%) than is typical of Medicare patients with cardiovascular disease.

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Population and Applicability: Examples

Presentation: Assessing Applicability

Keywords: applicability | population | internal validity | exclusion criteria | inclusion criteria

This slide discusses study population and applicability. It presents a table divided into two columns with one header row and six data rows. Column one is titled “Conditions that limit applicability” and column two is titled “Features that should be extracted into evidence tables.” Each of the six data rows contains conditions described in column one and associated features to be extracted in column two. In the first row, the limiting conditions are: narrow eligibility criteria, high exclusion rate, low enrollment. The features that should be extracted are: eligibility criteria and proportion of screened individuals enrolled. In the second row, limiting conditions are: differences between patients in study and the community. The features that should be extracted are: demographics (range and mean): age, gender, race and ethnicity. In the third row, the limiting conditions are: narrow or unrepresentative severity or stage of illness. The features that should be extracted are: severity or stage of illness (referral or primary care population). In the fourth row, limiting conditions are: run-in periods with high exclusion rates. The features that should be extracted are: run-in period: attrition rate before randomization and reason (e.g., nonadherence, adverse drug events and no response). In the fifth row, limiting conditions are: event rates markedly different than in community. The features that should be extracted are: event rates in treatment and control groups. In the sixth row, limiting conditions are: disease prevalence in study population different than community. The features that should be extracted are: prevalence of disease (for diagnostic studies).

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Population and Applicability

Presentation: Assessing Applicability

Keywords: applicability | population | eligibility criteria | exclusion criteria

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Planned Comparisons

Presentation: Comparative Effectiveness and Safety of Radiotherapy Treatments for Head and Neck Cancer

Keywords: 2DRT | 3DCRT | head and neck cancer | IMRT | proton beam therapy | radiotherapy | comparative effectiveness

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Rating the Strength of Evidence From the CER

Presentation: Comparative Effectiveness of Management Strategies for Adults With Gastroesophageal Reflux Disease: An Update

Keywords: comparative effectiveness | strength of evidence | systematic review | methods

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