Evidence map›Paper›PMID 25010522›Full record

ArticleNPJ primary care respiratory medicine2014

COPD Diagnostic Questionnaire (CDQ) for selecting at-risk patients for spirometry: a cross-sectional study in Australian general practice.

Anthony J Stanley, Iqbal Hasan, Alan J Crockett, Onno C P van Schayck, Nicholas A Zwar

Abstract read
In one paragraph

Article in NPJ primary care respiratory medicine, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

26 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Performance of alternative COPD case-finding tools: a systematic review and meta-analysis.European respiratory review : an official journal of the European Respiratory Society · 2021
    Pooled it
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  6. A Two-Staged, Risk-Stratified Strategy Combining FEVRespirology (Carlton, Vic.) · 2025
    Observational
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  11. Article
  12. Article
  13. Review
  14. Current Progress of COPD Early Detection: Key Points and Novel Strategies.International journal of chronic obstructive pulmonary disease · 2023
    Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Anthony J StanleySchool of Public Health and Community Medicine, Faculty of Medicine, University of New South Wales, Kensington, New South Wales, Australia.
Iqbal HasanCentre for Health Equity Training Research and Evaluation (CHETRE), Ingham Institute, Liverpool BC, New South Wales, Australia.
Alan J Crockett1] School of Health, University of South Australia, Adelaide, South Australia, Australia [2] Discipline of General Practice, School of Population Health, University of Adelaide, Adelaide, South Australia, Australia.
Onno C P van SchayckDepartment of General Practice, CAHPRI School for Public Health and Care, Maastricht University Medical Centre, Maastricht, The Netherlands.
Nicholas A ZwarSchool of Public Health and Community Medicine, Faculty of Medicine, University of New South Wales, Kensington, New South Wales, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundUsing the COPD Diagnostic Questionnaire (CDQ) as a selection tool for spirometry could potentially improve the efficiency and accuracy of chronic obstructive pulmonary disease (COPD) diagnosis in at-risk patients.

aimTo identify an optimal single cut point for the CDQ that divides primary care patients into low or high likelihood of COPD, with the latter group undergoing spirometry.

methodsFormer or current smokers aged 40-85 years with no prior COPD diagnosis were invited to a case-finding appointment with the practice nurse at various general practices in Sydney, Australia. The CDQ was collected and pre- and post-bronchodilator spirometry was performed. Cases with complete CDQ data and spirometry meeting quality standards were analysed (1,054 out of 1,631 patients). CDQ cut points were selected from a receiver operating characteristic (ROC) curve.

resultsThe area under the ROC curve was 0.713. A cut point of 19.5 had the optimal combination of sensitivity (63%) and specificity (70%) with two-thirds below this cut point. A cut point of 14.5 corresponded to a sensitivity of 91%, specificity of 35% and negative predictive value of 96%, and 31% of patients below this cut point.

conclusionsThe CDQ can be used to select patients at risk of COPD for spirometry using one cut point. We consider two possible cut points. The 19.5 cut point excludes a higher proportion of patients from undergoing spirometry with the trade-off of more false negatives. The 14.5 cut point has a high sensitivity and negative predictive value, includes more potential COPD cases but has a higher rate of false positives.

Indexed as

AdultAgedAged, 80 and overAustraliaCross-Sectional StudiesFemaleHumansMaleMiddle AgedPulmonary Disease, Chronic ObstructiveRisk FactorsSensitivity and SpecificitySpirometrySurveys and Questionnaires

Identifiers

PMID25010522
PMCPMC4373382

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.