Prediction of True Positive Lung Cancers in Individuals with Abnormal Suspicious Chest Radiographs—A Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial Study

Department of Community Health Sciences, Brock University, St Catharines, Ontario, Canada.
Journal of thoracic oncology: official publication of the International Association for the Study of Lung Cancer (Impact Factor: 5.28). 04/2009; 4(6):710-21. DOI: 10.1097/JTO.0b013e31819e77ce
Source: PubMed


Chest radiographs are routinely employed in clinical practice. Radiographic findings that are abnormal suspicious (AS) for lung cancer occur commonly. The majority of AS radiographic abnormalities are not cancer. This study identifies predictors of true positive (TP) AS and presents models for estimating the probability of lung cancer.
This is a prospective cohort study nested in the randomized National Cancer Institute's Prostate Lung Colorectal Ovarian Cancer Screening Trial (PLCO). First-time AS screens in the screening arm of the PLCO were studied. Associations between nonradiographic and radiographic factors, and TP AS were evaluated by multiple logistic regression.
The PLCO intervention arm had 77,465 individuals, of whom 12,314 were AS and of these 232 (1.9%) had lung cancer (were TP). Important independent predictors of TP were older age, lower education, greater pack years and duration smoking history, body mass index <30, family history of lung cancer, lung nodule, lung mass, unilateral mediastinal or hilar lymphadenopathy, lung infiltrate, and upper/middle chest AS location. The model including these variables had a receiver operator characteristic area under the curve (ROC AUC) of 86.4%. This model excluding the smoking variables had an ROC AUC of 77.1% and excluding all nonradiographic variables had an ROC AUC of 73.3% (p < 0.0001 for all these model differences). Smoking and nonsmoking nonradiographic variables significantly added to prediction.
This study identifies important nonradiographic and radiographic predictors of lung cancer, and presents an accurate model for estimating the probability of lung cancer in individuals with suspicious radiographs. These findings may be of value for screening, research, and patient and clinician decision-making.

5 Reads

  • Journal of thoracic oncology: official publication of the International Association for the Study of Lung Cancer 10/2009; 4(10):1192-4. DOI:10.1097/JTO.0b013e3181b88045 · 5.28 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Identification of individuals at high risk for lung cancer should be of value to individuals, patients, clinicians, and researchers. Existing prediction models have only modest capabilities to classify persons at risk accurately. Prospective data from 70 962 control subjects in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO) were used in models for the general population (model 1) and for a subcohort of ever-smokers (N = 38 254) (model 2). Both models included age, socioeconomic status (education), body mass index, family history of lung cancer, chronic obstructive pulmonary disease, recent chest x-ray, smoking status (never, former, or current), pack-years smoked, and smoking duration. Model 2 also included smoking quit-time (time in years since ever-smokers permanently quit smoking). External validation was performed with 44 223 PLCO intervention arm participants who completed a supplemental questionnaire and were subsequently followed. Known available risk factors were included in logistic regression models. Bootstrap optimism-corrected estimates of predictive performance were calculated (internal validation). Nonlinear relationships for age, pack-years smoked, smoking duration, and quit-time were modeled using restricted cubic splines. All reported P values are two-sided. During follow-up (median 9.2 years) of the control arm subjects, 1040 lung cancers occurred. During follow-up of the external validation sample (median 3.0 years), 213 lung cancers occurred. For models 1 and 2, bootstrap optimism-corrected receiver operator characteristic area under the curves were 0.857 and 0.805, and calibration slopes (model-predicted probabilities vs observed probabilities) were 0.987 and 0.979, respectively. In the external validation sample, models 1 and 2 had area under the curves of 0.841 and 0.784, respectively. These models had high discrimination in women, men, whites, and nonwhites. The PLCO lung cancer risk models demonstrate high discrimination and calibration.
    Journal of the National Cancer Institute 05/2011; 103(13):1058-68. DOI:10.1093/jnci/djr173 · 12.58 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Screening for lung cancer is not currently recommended, even in persons at high risk for this condition. Most patients with lung cancer present with symptomatic disease that is usually at an incurable, advanced stage. The recently reported NLST (National Lung Screening Trial) showed a 20% decrease in deaths from lung cancer in high-risk persons undergoing screening with low-dose computed tomography of the chest compared with chest radiography. The high-risk group included in the trial comprised asymptomatic persons aged 55 to 74 years, with smoking history of at least 30 pack-years. Screening with low-dose computed tomography detected more cases of early-stage lung cancer and fewer cases of advanced-stage cancer, confirming that screening has shifted the stage of cancer at diagnosis and provides more persons with the opportunity for curative treatment. Although computed tomography screening has risks and limitations, the 20% decrease in deaths is the single most dramatic decrease ever reported for deaths from lung cancer, with the possible exception of smoking cessation. Physicians should offer computed tomography screening for lung cancer to patients who fit the high-risk profile defined in the NLST.
    Annals of internal medicine 09/2011; 155(8):540-2. DOI:10.1059/0003-4819-155-8-201110180-00367 · 17.81 Impact Factor
Show more

Similar Publications