Lung Cancer HealthRisk Assessment

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Medically Reviewed By: Expert-24 Medical Review Board on March 27, 2014 | References

HEALTHTOOLS™ (HEALTHRISK™ AND HEALTHAGE™) DOES NOT PROVIDE MEDICAL ADVICE. It is intended for informational purposes only. It is not a substitute for professional medical advice, diagnosis or treatment. Never ignore professional medical advice in seeking treatment because of something you have read on the site. If you think you may have a medical emergency, immediately call your doctor or dial 911.

Expert Review Panel – Expert-24 Ltd

Terms of reference

The aim of the Expert Review Panel is to ensure that all Expert-24 clinical and epidemiological content is robust, independent and up to date.


Medical Director and Editor

Dr. Timothy Dudley

Chairman of the Expert Review Panel

Dr. Robin Christie

Current authors and reviewers for the Health Risk Assessment

Dr. Martin Dawes

Dr. Jonathan Mant

Emeritus authors and reviewers for the Health Risk Assessment

The following individuals were deeply involved in the creation of the health risk assessment at its inception, but are no longer active reviewers on the panel:

Dr. John Fletcher

Dr. Emma Boulton

Professor Larry Ramsay

Professor Klim McPherson

Patient-centered health risk using an Evidence Based Medicine approach

Who created it and how often is it reviewed and updated?

This health risk assessment is brought to you by Expert-24 Limited. Expert-24 Ltd has full editorial control over content and strives to ensure that the content is: 

Why is this health risk assessment different than others?

Most health risk assessments say if a person is at high, medium or low risk of either dying from or developing a given medical condition. Most also indicate what lifestyle factors contribute to this risk. What they do not say is the magnitude of each risk for an individual and how much that person’s risk will decrease if they change their lifestyle. For example, if one is at moderate risk of two diseases, say bowel cancer and heart disease, most people would be unaware that their risk of heart disease is still five times higher than their risk of bowel cancer. 

In order to construct an electronic risk assessment tool for health and disease states, it is necessary to provide supporting research evidence and a method of encapsulating the best estimate of relative risk. For each medical condition, it is necessary to present credible estimates of risk, based on evidence from relevant, peer reviewed medical research. Important features of the risk assessment tool are: 

The aim of this project is to provide healthy people with a quantitative assessment of their personal risk of developing some important diseases and some of the factors that influence their risk. This is an ambitious task and we would not claim to have produced the definitive approach. Although we believe this is the most informative collection of disease prediction equations available at the present time they do have limitations. The ones we are aware of are outlined below.

What exactly does a given percentage risk mean?

Someone looking at their risk of lung cancer until the age of 50 should read this model as saying, "Assuming survival to age 50 the chance of developing lung cancer during that time would be (some predicted value)". This approach has the appeal that changing risk factors will have the expected impact on cumulative risk and the mathematics remains transparent. We chose the risk of developing a certain condition rather than the risk of dying from it because for many people the fear of living and dealing with a disabling disease is as frightening as dying from it. 

This is different than lifetime risk calculations, which generally calculate the risk of dying from a given condition. Lifetime risk must take account of the fact that we all die of something in the end and calculating the relative contribution of common competing causes of death at various ages is difficult. Not only that, but the interpretation by users is complex. For example, a user of an interactive model predicting lifetime risk of lung cancer would see their individual risk of lung cancer fall with increasing cigarette consumption, because they would be dying of heart disease and chronic lung disease before they could get lung cancer.

How accurate are these percentages?

These models are good for illustrating the change in risk due to the presence or absence of single risk factors for prediction times of up to 5 years. They are likely to be reasonably good for 15 or 20 years and for combinations of several risk factors. For longer prediction times and varying more than, say, four risk factors the results should be regarded as illustrative rather than precise. The absolute level of risk for an individual may also be wide of the mark because the majority of overall risk remains unexplained in most research studies. This is why "confidence intervals" have not been included. That said these prediction equations do calculate the best estimate of risk that can be provided on the data given. 

Is this useful in the end? We believe it is. We believe that putting some quantification on risk allows users to explore the possible impact on their health of altering what they do. We find this approach more informative than a bland statement of "high risk" that is often value laden or that a certain action will "cut down" a risk without any indication of by how much.

Is risk really reversible?

This is a difficult question to answer, but in many cases the answer seems to be, "yes". This is good news for people with high risks who are older. Intuition might tell you that you are constantly doing damage to your body that accumulates over time, and in many cases that may be true. An example of this is in skin cancer, where the earlier and more often you are badly burned in life, the higher your risk of skin cancer. Staying out of the sun when you are old cannot reverse this risk. 
However, there is good evidence that for heart disease, for example, your risks can be significantly reduced no matter what your age. Cholesterol reduction by medications called "statins" reduces the risk of heart attack, angina or sudden death from heart problems by up to 30%, and this is entirely independent of age. Similarly, blood pressure reduction by drugs reduces the risk of stroke and heart disease by 25% - again entirely independent of age. Because in general it is older people who have the highest risks, they actually stand to benefit the most from treatment. 

The risk for developing heart disease in tobacco users has been shown to decline to a level comparable with a person who has never smoked within 2-3 years of giving up. Furthermore, the risk of having a stroke is reversed after 5-10 years of stopping. Studies have also shown that life expectancy improves even in people who stop smoking later in life (i.e. at 65 years or older). 

The reduction of risk that can be obtained from changing lifestyle habits such as diet, alcohol consumption and exercise is largely unknown. Therefore, the amount of risk reduction that can be expected from optimizing these habits needs to be viewed with caution. Certainly they should not take the place of blood pressure control, cholesterol control, and smoking cessation as goals.

How good is the evidence?

Our aim in searching for evidence was to identify up to ten high quality, relevant research studies for each topic. We used Medline to search using free text, MeSH terms and thesaurus search terms specific to each medical condition. To narrow the documents we used filters using "risk" and study design type; cohorts, case control, longitudinal, follow up. Searches were limited to studies published in English language and human studies. Although a comprehensive systematic review of the literature on each disease was not possible due to the scope of this project, we feel that the evidence used represents a reasonable cross-section of high-quality literature on the subjects in question. 
What we have done is to seek out plausible values of relative risk to use in the prediction equations. We have used an approach that searches for high quality research studies and have then applied our judgment tempered by Austin Bradford Hill's criteria for causation when selecting which risks to use. Hill's criteria are: strength, consistency, specificity, temporality, biological gradient, plausibility, coherence, experimental evidence and analogy. 

If this sometimes appears somewhat subjective then that is because at times it is a matter of judgment. The judgments have seldom altered the relative risk by more than a small amount. For each risk factor we had to choose a value to use in the model and have been faced at times with a range from which to choose. While a meta-analysis may provide the best point estimate, one is not always available and would be spurious to conduct on the sample of studies we have used for each condition. Given the level of uncertainty surrounding an individual's absolute personal risk we are comfortable with a comparatively lesser degree of uncertainty regarding a risk factor's relative risk.

What is the mathematical model that is used?

The actual mathematical and statistical models and risk coefficients that are used to determine risk are proprietary at this time, but have been validated by the authors and reviewers to be appropriate for use in this setting. 

References: Lung Cancer

Most recently reviewed:

  2. Gonzalez CA and Riboli E. Diet and Cancer Prevention: Contributions from the European Prospective Investigation into Cancer and Nutrition Study. Euro J Cancer 46 (2010) 2555 –2562.

Guidelines reviewed annually:

  1. NHS Information for patients on the nature of cancer.
  2. NHS Cancer screening programmes.

Selected articles from previous reviews:

  1. The International Early Lung Cancer Action Program Investigators, Henschke CI, Yankelevitz DF, et al. Survival of patients with stage I lung cancer detected on CT screening. N Engl J Med 2006;355:1763-1771.
  2. Wilson DO, Weissfeld JL, Fuhrman CR, et al. The Pittsburgh Lung Screening Study (PLuSS): outcomes within 3 years of a first computed tomography scan. Am J Respir Crit Care Med 2008;178(9):956-961.
  3. Yun YH, et al. "Cigarette smoking and cancer incidence risk in adult men: National Health Insurance Corporation Study" Cancer Detect Prev. 2005 29(1):15-24.
  4. Zhang B, et al. "Smoking cessation and lung cancer mortality in a cohort of middle-aged Canadian women", Ann Epidemiol April 2005, 15(4):302-9
  5. Lee PN, Sanders E "Does increased cigarette consumption nullify any reduction in lung cancer risk associated with low-tar filter cigarettes?", Inhal Toxicol 16/03/05, 16(13):817-33
  6. Clifford GM, et al. "Cancer risk in the Swiss HIV Cohort Study: associations with immunodeficiency, smoking, and highly active antiretroviral therapy." J Natl Cancer Inst March 16, 2005, 97(6):425-32
  7. Marugame T, et al. "Lung cancer death rates by smoking status: comparison of the Three-Prefecture Cohort study in Japan to the Cancer Prevention Study II in the USA" Cancer Sci. Feb 2005, 96(2):120-6
  8. Vineis P, et al. "Environmental tobacco smoke and risk of respiratory cancer and chronic obstructive pulmonary disease in former smokers and never smokers in the EPIC prospective study." BMJ May 2, 2005, 330(7486):277
  9. Eichholzer M, et al. "Body mass index and the risk of male cancer mortality of various sites: 17-year follow-up of the Basel cohort study." Swiss Med Wkly Jan 8, 2005, 135(1-2):27-33
  10. Mannisto S, et al "Dietary carotenoids and risk of lung cancer in a pooled analysis of seven cohort studies" Cancer Epidemiol Biomarkers Prev Jan 2004, 13(1):40-8
  11. Riboli E, Norat T "Epidemiologic evidence of the protective effect of fruit and vegetables on cancer risk." Am J Clin Nutr Sep 2003, 78(3 Suppl):559S-569S.
  12. Bilello, K.S., "Epidemiology, etiology, and prevention of lung cancer", Clinics in Chest Medicine, 01 March 2002; 23(1): 1-25.
  13. Reid, M.E. et al, "Selenium supplementation and lung cancer incidence: an update of the nutritional prevention of cancer trial", Cancer Epidemiology, Biomarkers and Prevention, 2002 Nov;11(11):1285-91.
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  18. Doll et al, "Mortality in relation to smoking:22 years observations on female British doctors", BMJ 5/4/80 p 967-971
  19. Kreuzer et al, "Lung cancer in non smoking men - results of a case control study in Germany", British Journal of Cancer 2001 84:134-140
  20. Wald et al, "Does breathing other peoples smoke cause lung cancer?", BMJ 8 November 1986 293:121-1222
  21. Gustavsson et al "Occupational exposure and lung cancer risk: A population based case referent study in Sweden", American Journal of Epidemiology 152: 32-40
  22. Bromen et al, "Aggregation of lung cancer in families: Results from a population based case control study in Germany", American Journal of Epidemiology 152:497-505
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  24. Yuan et al, "Morbidity and mortality in relation to cigarette smoking in Shanghai, China: A prospective male cohort study", JAMA 1996:275 1646-1650
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  27. Katsoyanni et al, "A case control study of air pollution and tobacco smoking in lung cancer among women in Athens Preventive medicine", 1991 20 271-8
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