Lung cancer risk
Lung cancer risk calculator for people who smoke or used to
This calculator uses the PLCOm2012 model, built from a large US screening trial, to estimate the chance of being diagnosed with lung cancer in the next 6 years. It is for people aged 55 to 74 who have ever smoked.
About you
Best estimates are fine. Nothing you enter leaves this page.
What you will see
Your estimated chance of a lung cancer diagnosis in the next 6 years, and how it compares with the levels used in the study.
Educational only, not medical advice. This calculator does not decide whether you should be screened.
Source
PLCOm2012 model: Tammemagi MC et al., N Engl J Med 2013, Table 2 (coefficients, centering values and formula). We use the published numbers exactly.
Validated in
Built in 36,286 people who had ever smoked in the control group of the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial, and validated in 37,332 people who had ever smoked in its intervention group. The authors also checked it in 51,033 National Lung Screening Trial (NLST) participants, where it separated people less well, and used NLST data to look at whether the benefit of CT screening differed by risk. All were aged 55 to 74 at entry.
Limits
Only for ages 55 to 74 and only for people who have ever smoked. Not for anyone with symptoms or a past lung cancer. Trial participants had a higher socioeconomic status than the US population. It is not a screening guideline.
Risk score versus screening rules
This calculator does not tell you whether you qualify for lung cancer screening. The USPSTF decides eligibility using age and pack-years, not this score: it recommends a yearly low-dose CT scan for adults aged 50 to 80 with at least 20 pack-years who smoke now or quit within the past 15 years (USPSTF 2021). To check those criteria, use the lung cancer screening eligibility check. The American Cancer Society's 2023 guideline also uses age and pack-years, with no limit on years since quitting (ACS 2023).
What PLCOm2012 adds is a more detailed estimate. It weighs things the screening rules leave out, such as COPD, family history and body mass index (Tammemagi 2013).
What the model uses
In the study, the risk of lung cancer rose with age, lower education, lower body mass index, COPD, a personal history of cancer, a family history of lung cancer, smoking now rather than in the past, more cigarettes a day, more years of smoking and, in people who quit, fewer years since quitting (Tammemagi 2013). The effect of cigarettes a day levels off: each extra cigarette adds less risk as the number goes up (Tammemagi 2013).
| Input | Odds ratio in the study |
|---|---|
| Each extra year of age | 1.081 |
| COPD (yes vs no) | 1.427 |
| Personal history of cancer | 1.582 |
| Family history of lung cancer | 1.799 |
| Smoking now (vs quit) | 1.297 |
| Each extra year of smoking | 1.032 |
| Each extra year since quitting | 0.970 |
| Each step up in education (6 levels) | 0.922 |
| Each 1-unit higher BMI | 0.973 |
Source: Table 2 of Tammemagi 2013 (Tammemagi 2013). An odds ratio above 1 means higher risk.
Why it asks about race and education
The model includes the race or ethnic group participants reported in the trial, and their education level, because both changed the predicted risk in that data (Tammemagi 2013). Education stands in for socioeconomic status, which the study linked with lung cancer risk (Tammemagi 2013). These terms describe patterns in the trial population, not biology, and some groups were small: the Hispanic, Asian and Native Hawaiian or Pacific Islander estimates have wide confidence intervals, and American Indian or Alaska Native participants were given the same value as the White reference group (Tammemagi 2013).
How to read the number
Your result is the estimated chance of being diagnosed with lung cancer within 6 years. For a reclassification analysis, the study used three levels: under 1.0%, 1.0% to under 2.0%, and 2.0% or more (Tammemagi 2013). To compare the model with the National Lung Screening Trial criteria, the authors picked a cutoff of 1.3455%, because that selected the same number of people as those criteria. With equal numbers selected, the model picked up more of the lung cancers (sensitivity 83.0% vs 71.1%) (Tammemagi 2013). These are study levels, not treatment advice.
Common questions
I never smoked. Can I use this?
No. The model was built only in people who had ever smoked (Tammemagi 2013).
I am 52 or 78. Why can I not enter my age?
Everyone in the trials was 55 to 74 at entry, and the authors say the model's accuracy outside that range is uncertain (Tammemagi 2013).
I have a cough or chest pain. Should I use this?
No. General safety advice (not part of the USPSTF recommendation): a cough that will not go away, coughing up blood or unexplained weight loss are reasons to see a doctor now, whatever a calculator says.
Quitting lowers your risk over time: in the model, each year since quitting lowers the estimate (Tammemagi 2013). For help, see the quit smoking help check. Also see the COPD screening check.
Sources
- Tammemagi MC, Katki HA, Hocking WG, et al. Selection criteria for lung-cancer screening. N Engl J Med. 2013;368(8):728-736. Free full text: PMC3929969. doi.org/10.1056/NEJMoa1211776
- US Preventive Services Task Force. Screening for Lung Cancer: US Preventive Services Task Force Recommendation Statement. JAMA. 2021;325(10):962-970. www.uspreventiveservicestaskforce.org/uspstf/recommendation/lung-cancer-screening
- Wolf AMD, Oeffinger KC, Shih TY, et al. Screening for lung cancer: 2023 guideline update from the American Cancer Society. CA Cancer J Clin. 2024;74(1):50-81. doi.org/10.3322/caac.21811
Written and maintained by the uncovermyrisk.com editorial team. We do not have a medical reviewer; every claim links to its primary source above. Last reviewed: 2026-10-31. Spotted an error? See About.