BACKGROUND-The effect of screening with prostate-specific-antigen (PSA) testing and digital rectal examination on the rate of death from prostate cancer is unknown. This is the first report from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial on prostate-cancer mortality.

BACKGROUND The National Lung Screening Trial (NLST) used risk factors for lung cancer (e.g., ≥30 pack-years of smoking and <15 years since quitting) as selection criteria for lung-cancer screening. Use of an accurate model that incorporates additional risk factors to select persons for screening may identify more persons who have lung cancer or in whom lung cancer will develop. METHODS We modified the 2011 lung-cancer risk-prediction model from our Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial to ensure applicability to NLST data; risk was the probability of a diagnosis of lung cancer during the 6-year study period. We developed and validated the model (PLCOM2012) with data from the 80,375 persons in the PLCO control and intervention groups who had ever smoked. Discrimination (area under the receiver-operating-characteristic curve [AUC]) and calibration were assessed. In the validation data set, 14,144 of 37,332 persons (37.9%) met NLST criteria. For comparison, 14,144 highest-risk persons were considered positive (eligible for screening) according to PLCOM2012 criteria. We compared the accuracy of PLCOM2012 criteria with NLST criteria to detect lung cancer. Cox models were used to evaluate whether the reduction in mortality among 53,202 persons undergoing low-dose computed tomographic screening in the NLST differed according to risk. RESULTS The AUC was 0.803 in the development data set and 0.797 in the validation data set. As compared with NLST criteria, PLCOM2012 criteria had improved sensitivity (83.0% vs. 71.1%, P<0.001) and positive predictive value (4.0% vs. 3.4%, P = 0.01), without loss of specificity (62.9% and. 62.7%, respectively; P = 0.54); 41.3% fewer lung cancers were missed. The NLST screening effect did not vary according to PLCOM2012 risk (P = 0.61 for interaction). CONCLUSIONS The use of the PLCOM2012 model was more sensitive than the NLST criteria for lung-cancer detection.

After 13 years of follow-up, there was no evidence of a mortality benefit for organized annual screening in the PLCO trial compared with opportunistic screening, which forms part of usual care, and there was no apparent interaction with age, baseline comorbidity, or pretrial PSA testing.

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Bacterial pneumonia is more frequent in HIV-positive persons than in seronegative controls, and the risk is highest among those with CD4 lymphocyte counts below 200 per cubic millimeter and among injection-drug users.

Martin Tammemägi and colleagues evaluate which risk groups of individuals, including nonsmokers and high-risk individuals from 65 to 80 years of age, should be screened for lung cancer using computed tomography. Please see later in the article for the Editors' Summary

chronic cough are presented in algorithmic form (Fig 1-3). Guidelines with algorithms for evaluating chronic cough in pediatric patients < 15 years of age are presented in the section entitled "Guidelines for Evaluating Chronic Cough in Pediatrics" 2,4 [Fig 4, 5]. For a full discussion on how to use the algorithms, please refer to these sections. Summary and Recommendations Recommendations for each section of these guidelines are listed under their respective section titles. For an in-depth discussion or clarification of each recommendation, readers are encouraged to read the specific section in question in its entirety. Methodology and Grading of the Evidence for the Diagnosis and Management of Cough 5 • The recommendations were graded, by consensus by the panel, using the American College of Chest Physicians Health and Science Policy Grading System, which is based on the following two components: quality of evidence; and the net benefit of the diagnostic and therapeutic procedure. • The quality of evidence is rated according to the study design and strength of other methodologies used in the included studies.

The PLCO lung cancer risk models demonstrate high discrimination and calibration.