Tanner J. Caverly, MD, MPH; Pianpian Cao, MPH; Rodney A. Hayward, MD; Rafael Meza, PhD
Although screening with low-dose computed tomography (LDCT) can reduce lung cancer mortality, the benefits may differ according to the balance of a patient's risk for lung cancer, risk for dying of lung cancer or other causes, and personal preferences with regard to screening. This study evaluated each of these variables to help guide physician–patient discussions about whether to pursue LDCT screening for lung cancer.
Ann Intern Med. 2018;169(1):1-9. doi:10.7326/M17-2561
Hormuzd A. Katki, PhD; Stephanie A. Kovalchik, PhD; Lucia C. Petito, PhD; Li C. Cheung, PhD; Eric Jacobs, PhD; Ahmedin Jemal, PhD; Christine D. Berg, MD; Anil K. Chaturvedi, PhD
Guidelines recommend the use of individualized risk models to refer ever-smokers for lung cancer screening, but the performance of different models in selecting ever-smokers for screening is unknown. In this study, the authors compared the U.S. screening populations selected by 9 lung cancer risk models and examined the predictive performance of the models in 2 large, population-based U.S. cohorts.
Ann Intern Med. 2018;169(1):10-19. doi:10.7326/M17-2701
Steve Yadlowsky, MS; Rodney A. Hayward, MD; Jeremy B. Sussman, MD, MS; Robyn L. McClelland, PhD; Yuan-I Min, PhD; Sanjay Basu, MD, PhD
Current guidelines recommend aspirin, statins, and antihypertensive drugs to prevent coronary artery disease in high-risk persons. Deciding whether risk is high enough to warrant these interventions requires calculating a person's 10-year risk for coronary artery disease using pooled cohort equations, which have been controversial since their release in 2013. This study describes similar equations developed using more modern patient cohorts and modified methods that avoid some statistical problems.
Ann Intern Med. 2018;169(1):20-29. doi:10.7326/M17-3011
Sabina De Geest, PhD, RN; Leah L. Zullig, PhD, MPH; Jacqueline Dunbar-Jacob, PhD, RN; Remon Helmy, MSc; Dyfrig A. Hughes, MRPharmS, PhD; Ira B. Wilson, MD, PhD; Bernard Vrijens, PhD
This guideline, structured around 4 minimum criteria and 17 items reflecting best practice, aims to help researchers improve the quality of reporting medication adherence research.
Ann Intern Med. 2018;169(1):30-35. doi:10.7326/M18-0543
Ian A. Scott, MBBS, MHA, MEd
Machine learning, which converts complex data into algorithms, challenges the traditional epidemiologic approach of evidence-based medicine. This commentary discusses intersections between these approaches, including their differences, strengths, and limitations, and suggests areas of reconciliation.
Ann Intern Med. 2018;169(1):44-46. doi:10.7326/M18-0115
Marian E. Betz, MD, MPH; Alexander D. McCourt, JD, MPH; Jon S. Vernick, JD, MPH; Megan L. Ranney, MD, MPH; Donovan T. Maust, MD, MS; Garen J. Wintemute, MD, MPH
Many support limiting firearm access for persons whose mental illness would place them or others at heightened risk, but less attention has been paid to progressive cognitive impairment and firearm access. For persons with dementia, discussions about firearm access strongly parallel discussions about driving. This commentary discusses when persons with dementia need to “give up the keys,” whether they are to a gun safe or a car, and how to do so.
Ann Intern Med. 2018;169(1):47-49. doi:10.7326/M18-0140
N. Lance Downing, MD; David W. Bates, MD, MSc; Christopher A. Longhurst, MD, MS
The widespread adoption of electronic health records (EHRs) has been perceived as driving physician dissatisfaction and burnout. The authors of this essay present data comparing EHR use in other countries with that in the United States and offer a possible explanation of, and solutions to, a root cause of dissatisfaction with EHRs.
Ann Intern Med. 2018;169(1):50-51. doi:10.7326/M18-0139
Louise Davies, MD, MS; Diana B. Petitti, MD, MPH; Lynn Martin, PhD; Meghan Woo, ScD, ScM; Jennifer S. Lin, MD, MCR
This special article defines overdiagnosis in cancer screening, identifies approaches to estimating overdiagnosis, shows how variation in estimates can arise, and describes best practices for communicating the potential for harm due to overdiagnosis.
Ann Intern Med. 2018;169(1):36-43. doi:10.7326/M18-0694
Michael K. Gould, MD, MS
Caverly and colleagues' modeling analysis explored the importance of disutilities in the lung cancer screening decision. The editorialist discusses the unavoidable tensions among the various goals of screening, the role of patient preferences, and how physicians can incorporate Caverly and colleagues' findings into their discussions with patients about lung cancer screening.
Ann Intern Med. 2018;169(1):52-53. doi:10.7326/M18-1350
Martin C. Tammemägi, DVM, MSc, PhD
Katki and colleagues compared the performance of 9 lung cancer risk models in a representative sample of the U.S. population and investigated the similarities and differences in the populations of ever-smokers selected for screening by each model. The editorialist discusses issues that will require attention if the models are to be implemented in routine clinical practice.
Ann Intern Med. 2018;169(1):54-55. doi:10.7326/M18-0986
Andrew Paul DeFilippis, MD, MSc; Patrick Trainor, MS, MA
Yadlowsky and colleagues evaluated 2 approaches for improving the pooled cohort equations to estimate cardiac risk. The editorialists discuss the findings and the need to develop increasingly accurate tools for cardiac risk estimation in specific patient populations.
Ann Intern Med. 2018;169(1):56-57. doi:10.7326/M18-1175
Christopher K. Migliore, MD, MS
The case I was presenting wasn't a mystery. To be honest, I had no idea why my pathology colleague chose it.
Ann Intern Med. 2018;169(1):58. doi:10.7326/M18-0706
Ann Intern Med. 2018;169(1):60-61. doi:10.7326/L17-0629
Ann Intern Med. 2018;169(1):61-62. doi:10.7326/L17-0748
Ann Intern Med. 2018;169(1):62-64. doi:10.7326/M18-0503
Ann Intern Med. 2018;169(1):64. doi:10.7326/L18-0166
Ann Intern Med. 2018;169(1):65. doi:10.7326/L18-0102
Ann Intern Med. 2018;169(1):65. doi:10.7326/L18-0103
Ann Intern Med. 2018;169(1):65-66. doi:10.7326/L18-0104
Ann Intern Med. 2018;169(1):66. doi:10.7326/L18-0105
Ann Intern Med. 2018;169(1):66-67. doi:10.7326/L18-0181
Ann Intern Med. 2018;169(1):67. doi:10.7326/L18-0180
Ann Intern Med. 2018;169(1):67-68. doi:10.7326/L18-0182
Ann Intern Med. 2018;169(1):68. doi:10.7326/L18-0302
Judith Brice, MD
Ann Intern Med. 2018;169(1):46. doi:10.7326/M17-2432
Jonathan Zuckerman, MD
Ann Intern Med. 2018;169(1):59. doi:10.7326/M18-0129
Christina L. Master, MD; Andrew R. Mayer, PhD; Davin Quinn, MD; Matthew F. Grady, MD
Ann Intern Med. 2018;169(1):ITC1-ITC16. doi:10.7326/AITC201807030
Darren B. Taichman, MD, PhD
Ann Intern Med. 2018;169(1):ED1. doi:10.7326/AFED201807030
Jade R. Blue, BA(Hons)
Take a break and read more of Jade Blue's comical and poignant descriptions of her journey with breast cancer.
Ann Intern Med. 2018;169(1):W1-W5. doi:10.7326/G17-0019
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