Development and validation of a lung cancer risk prediction model for African-Americans

Our plain-English summary of Development and validation of a lung cancer risk prediction model for African-Americans, by C.J. Etzel, S. Kachroo, M. Liu, et al (Cancer Prevention Research, 2008).

The study

• Authors: C.J. Etzel, S. Kachroo, M. Liu, A. D'Amelio, Q. Dong, M.L. Cote, A.S. Wenzlaff, W.K. Hong, A.J. Greisinger, A.G. Schwartz, M.R. Spitz
• Journal: Cancer Prevention Research
• Published: 2008;1(4):255-65
• Cited by: 95 articles, as counted by NIH iCite
• Read it: PubMed · Publisher · Free full text

Abstract

Because existing risk prediction models for lung cancer were developed in white populations, they may not be appropriate for predicting risk among African-Americans. Therefore, a need exists to construct and validate a risk prediction model for lung cancer that is specific to African-Americans. We analyzed data from 491 African-Americans with lung cancer and 497 matched African-American controls to identify specific risks and incorporate them into a multivariable risk model for lung cancer and estimate the 5-year absolute risk of lung cancer. We performed internal and external validations of the risk model using data on additional cases and controls from the same ongoing multiracial/ethnic lung cancer case-control study from which the model-building data were obtained as well as data from two different lung cancer studies in metropolitan Detroit, respectively. We also compared our African-American model with our previously developed risk prediction model for whites. The final risk model included smoking-related variables [smoking status, pack-years smoked, age at smoking cessation (former smokers), and number of years since smoking cessation (former smokers)], self-reported physician diagnoses of chronic obstructive pulmonary disease or hay fever, and exposures to asbestos or wood dusts. Our risk prediction model for African-Americans exhibited good discrimination [75% (95% confidence interval, 0.67-0.82)] for our internal data and moderate discrimination [63% (95% confidence interval, 0.57-0.69)] for the external data group, which is an improvement over the Spitz model for white subjects. Existing lung cancer prediction models may not be appropriate for predicting risk for African-Americans because (a) they were developed using white populations, (b) level of risk is different for risk factors that African-American share with whites, and (c) unique group-specific risk factors exist for African-Americans. This study developed and validated a risk prediction model for lung cancer that is specific to African-Americans and thus more precise in predicting their risks. These findings highlight the importance of conducting further ethnic-specific analyses of disease risk.

In plain English

This case-control study built and tested a lung cancer risk prediction model specifically for African-Americans. The authors interviewed 491 African-Americans with lung cancer and 497 matched African-American controls in Houston, recruited 1995 to 2005. Asbestos exposure meant self-reported exposure (8 hours weekly for a year) or work in an asbestos-related industry; no fiber type was specified. This exposure was associated with higher lung cancer risk (odds ratio 1.58; 95% CI 1.18-2.12), as were smoking, COPD and wood dusts. In the final model, asbestos exposure carried a relative risk of 1.46 (95% CI 1.04-2.04). Interactions between smoking and asbestos or dusts were not statistically significant. The model's ability to separate cases from controls (area under the curve) was good in 156 further Houston participants, at 75% (95% CI 0.67-0.82). It was moderate in 325 Detroit participants, at 63% (95% CI 0.57-0.69). The authors concluded it discriminated well except among early-onset cases. They also concluded it outperformed a model built mainly in whites, a comparison possible only among ever smokers. They noted small samples and unconfirmed self-reported exposures.

We wrote this plain-English summary from the full article with the help of AI, and a second AI model checked each sentence against the article. It is not the authors' wording; the abstract and the article are their own account.

What the study did and found

• Design: Case-control study used to develop a multivariable lung cancer risk prediction model, with internal and external validation
• Who was studied: 491 African-American lung cancer cases (M. D. Anderson Cancer Center and Michael E. DeBakey VA Medical Center, Houston) and 497 African-American controls from Houston community centers and the Kelsey-Seybold Clinic. Controls were matched on age (within 5 years), sex and ethnicity. Participants were recruited from 1995 to 2005. Validation used 156 further Houston participants (89 cases, 67 controls; enrolled May 2005 to December 2007) and 325 participants from two Detroit studies (172 cases, 153 controls).
• Exposure: Asbestos exposure, classified by self-report (at least 8 hours per week for a year) or by having held a job in a documented asbestos-related industry; no fiber type specified. Also studied: smoking, wood dusts, synthetic vitreous fibers, toluene and/or xylene, other workplace exposures, medical conditions and family history.
• Main results:
  • Self-reported asbestos exposure was more common among cases (210, 44.4%) than controls (151, 30.8%).
  • Asbestos exposure was associated with increased lung cancer risk: OR 1.58 (95% CI 1.18-2.12), adjusted for age, sex and smoking status when possible.
  • Wood dusts (OR 1.50; 95% CI 1.09-2.05), synthetic vitreous fibers (OR 2.27; 95% CI 1.44-3.60) and toluene and/or xylene (OR 1.40; 95% CI 1.02-1.92) were also associated with elevated risk.
  • Compared with never smokers, current smokers had OR 6.20 and former smokers had OR 3.38. Physician-diagnosed COPD had OR 6.38 (95% CI 3.24-12.59).
  • Interactions between smoking variables and asbestos or dusts did not reach statistical significance.
  • In the final age- and sex-adjusted model, asbestos-exposed participants had a relative risk of 1.46 (95% CI 1.04-2.04). Dusts had 1.38 (95% CI 0.97-1.96) and hay fever 0.66 (95% CI 0.43-1.01).
  • Discrimination (area under the curve) was 75% (95% CI 0.67-0.82) in the internal validation group of 89 cases and 67 controls. The authors called this good discrimination.
  • Discrimination was 63% (95% CI 0.57-0.69) in the external Detroit validation group of 172 cases and 153 controls. The authors called this more moderate.
  • Among ever smokers, the African-American model's area under the curve was 79% (95% CI 0.70-0.88) internally and 66% (95% CI 0.61-0.71) externally. The Spitz model, developed in whites, scored 67% (95% CI 0.57-0.77) and 59% (95% CI 0.52-0.65).
• The authors' conclusion: The authors concluded that their model discriminated well between cases and controls except for a subgroup of early-onset lung cancer cases. They also concluded it outperformed a similar model developed primarily for white populations.
• Limitations the authors state:
  • The validation sample was small.
  • The study was hospital based and controls came only from the Houston area, so results may vary elsewhere.
  • The overall sample was small, so the odds ratio estimates were less precise than in the authors' study of white cases.
  • Self-reported comorbidities and exposures could not be confirmed.
  • The Spitz model could be compared only among ever smokers, because data on environmental tobacco smoke for never smokers were limited.

Topics

The National Library of Medicine indexes this study under subjects our site covers: Lung cancer.

Medical terms in this study, explained in our Lexicon: Lung Cancer, Case-Control Study, confidence interval.

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