ABSTRACT
OBJECTIVES: To determine whether mild stage chronic obstructive pulmonary disease (COPD) can be detected on chest radiography without substantial overdiagnosis. METHODS: A retrospective nested case-control study (case:control, 1:1) was performed in 783 patients scheduled for cardiothoracic surgery who underwent both spirometry and a chest radiograph preoperative. Diagnostic accuracy of chest radiography for diagnosing mild COPD was investigated using objective measurements and overall appearance specific for COPD on chest radiography. Inter-observer variability was investigated and variables with a kappa >0.40 as well as baseline characteristics were used to make a diagnostic model which was aimed at achieving a high positive predictive value (PPV). RESULTS: Twenty percent (155/783) had COPD. The PPV of overall appearance specific for COPD alone was low (37-55%). Factors in the diagnostic model were age, type of surgery, gender, distance of the right diaphragm apex to the first rib, retrosternal space, sternodiaphragmatic angle, maximum height right diaphragm (lateral view) and subjective impression of COPD (using both views). The model resulted in a PPV of 100%, negative predictive value (NPV) of 82%, sensitivity of 10% and specificity of 100% with an area under the curve of 0.811. CONCLUSIONS: Detection of mild COPD without substantial overdiagnosis was not feasible on chest radiographs in our cohort.
Subject(s)
Pulmonary Disease, Chronic Obstructive/diagnostic imaging , Aged , Case-Control Studies , Diaphragm/physiopathology , Female , Forced Expiratory Volume/physiology , Humans , Male , Middle Aged , Observer Variation , Pulmonary Disease, Chronic Obstructive/physiopathology , Radiography, Thoracic/standards , Retrospective Studies , Sensitivity and Specificity , Vital Capacity/physiologyABSTRACT
We describe the rationale for a new study examining the prognostic value of unrequested findings in diagnostic imaging. The deployment of more advanced imaging modalities in routine care means that such findings are being detected with increasing frequency. However, as the prognostic significance of many types of unrequested findings is unknown, the optimal response to such findings remains uncertain and in many cases an overly defensive approach is adopted, to the detriment of patient-care. Additionally, novel and promising image findings that are newly available on many routine scans cannot be used to improve patient care until their prognostic value is properly determined. The PROVIDI study seeks to address these issues using an innovative multi-center case-cohort study design. PROVIDI is to consist of a series of studies investigating specific, selected disease entities and clusters. Computed Tomography images from the participating hospitals are reviewed for unrequested findings. Subsequently, this data is pooled with outcome data from a central population registry. Study populations consist of patients with endpoints relevant to the (group of) disease(s) under study along with a random control sample from the cohort. This innovative design allows PROVIDI to evaluate selected unrequested image findings for their true prognostic value in a series of manageable studies. By incorporating unrequested image findings and outcomes data relevant to patients, truly meaningful conclusions about the prognostic value of unrequested and emerging image findings can be reached and used to improve patient-care.
