Sunday, March 16, 2014

Health behavior interventions prevent incidence and death from cancer

Flickr/NatalieMaynor
At the annual meeting of the American Society for Preventive Oncology, I had the privilege of presenting the evidence that supports the potential for health behaviors and vaccines to have a huge payoff for prevention of cancer throughout the world. My slides from that talk are now available.

Questions that I addressed include the challenge of “where is prevention delivered" and “how long will we wait to accrue the benefits of prevention”. We have previously documented many barriers to preventing cancer by acting on what we already know (1). In this presentation, I focused more on the global cancer prevention challenges since lifestyle interventions will pay off at a lower cost and greater return than building health services to diagnose and treat the ever-increasing burden of cancer (2).

Tobacco control remains the highest priority in high-income countries and in low and middle-income countries to prevent the 30% or more of cancer that is caused by smoking cigarettes (3). Data from the prospective Nurses’ Health Study demonstrate that cessation from smoking provides greater benefits through reduction of lung cancer mortality than does CT screening (4). More importantly, smoking cessation reduces total mortality by 50% overall, and within 15 years of stopping smoking (4). On the other hand, screening for lung cancer reduces lung cancer mortality, but obviously does not reduce mortality from heart disease and stroke, or the many cancers at other sites (such as bladder and kidney) that are caused by smoking but are not detected by lung cancer screening.

Infections are a major cause of cancer in all countries (5). In high-income countries around 7% of cancers are caused by infections. However in low and middle-income countries the contribution of infections increases to approximately 25%. Vaccines clearly reduce cancer risk. Hepatitis B vaccine, now widespread, reduces liver cancer (6).

Beyond smoking cessation (7) and vaccination programs what should our prevention priorities be? Recent evidence following women prospectively after they were classified according to how closely they adhere to the American Cancer Society nutrition and physical activity guidelines (8) shows that those who are normal weight, eat mainly a plant-based diet, limit their alcohol intake, and are physically active, have significantly reduced incidence of cancer (9). During 12 years of follow-up within this cohort, women adhering to the ACS guidelines had a 22% reduction in diagnosis of new cases of breast cancer and 52% reduction in colon cancer (after adjusting for all other risk factors). Importantly, following the ACS guidelines also significantly reduced mortality (9).

In our research published last year, we also showed that avoiding a known breast carcinogen leads to lower risk of cancer (10). Following the women in the Nurses’ Health Study II, those who avoided alcohol in their adolescent years and before their first pregnancy, had significantly lower risk both of premalignant or precursor breast lesions (proliferative benign breast disease) and of invasive breast cancer through the premenopausal years. Avoiding carcinogens keeps risk low.

Valuing the payoff from prevention
This is complex. One such estimated for childhood vaccination uses the example of South Africa. Benefit gains include healthcare cost savings, productivity of parents attending to the care of sick children, productivity of the children as they grow to attend school and then enter the workforce (11). Externalities in the community are achieved even by the unvaccinated community members. This is due to the overall increases in wellness. These benefits have to be added to the reduction in incidence and mortality of disease as a direct consequence of vaccination. The same range of benefits accrue for hepatitis vaccination where data from Asian countries clearly show that vaccination reduces sickness, time lost from work and associated productivity, mortality, etc. Vaccination reduces the cost of health services and increases life expectancy (12, 13).

This same approach applies to the benefits of quitting smoking and is summarized in the Surgeon General’s Report released earlier in 2014(3). When smokers quit smoking their quality of life improves significantly. For the employer, absenteeism is lower in never smokers than in current smokers, and health care costs are reduced with smoking cessation, as is the subsequent risk of many chronic conditions. These benefits accrued over decades.

Alcohol a known carcinogen
While prevention messages support strategies to reduce alcohol consumption, the risks and benefits of consumption vary disproportionately by age. The societal hazards of alcohol intake include motor vehicle accidents, risky sexual behavior, violence and injuries. The adverse effects accrue in adolescent and early adult years. The risks of cancer and benefits of cardiovascular protection are observed decades later, after the consequences and toll on society due to motor vehicle accidents and alcohol related deaths.

Some question whether weight loss prevents cancer
A recent meta-analysis shows significant benefits for weight loss after bariatric surgery (14). The reduction in cancer is significant in women but not men. The limited number of cancer cases precludes an analysis of risk reduction according to cancer site. In a previous analysis, we showed that bariatric surgery and the subsequent associated weight loss is cost-effective and can be cost saving (15).

In contrast with the benefits of prevention, we currently spend billions of dollars on cancer care in the United States. Hassett and Elkin estimate we spent 125 billion on cancer care in 2010 (16). Furthermore, 13% of all cancer expenditures were for breast cancer. Given the increasing burden of cancer at a system or societal level, these costs are not sustainable for the US or, in fact, for low and middle-income countries (2, 16). In a detailed analysis of the cost-effectives of cancer care, Greenberg et al estimated that the incremental cost for treatment and improved outcomes generating an additional year of life is $27,000 for breast cancer and more for an additional year of life for treatment of patients with other cancer diagnoses (17). With the number of new cases of cancer in the US continuing to increase each year as our population ages (18), the growth in health-care costs for cancer is viewed as unsustainable (16). Cost related decisions are therefore inevitable. At the global level, even greater emphasis on effective low-cost treatment and broad access to this treatment becomes a top priority (2).

Cancer prevention works
Garnering greater resources and priority to implement effective cancer prevention must be our highest priority.


References
1. G. A. Colditz, K. Y. Wolin, S. Gehlert, Applying what we know to accelerate cancer prevention. Sci Transl Med 4, 127rv124 (2012); published online EpubMar 28 (10.1126/scitranslmed.3003218).

2. K. Chalkidou, P. Marquez, P. K. Dhillon, Y. Teerawattananon, T. Anothaisintawee, C. A. Gadelha, R. Sullivan, Evidence-informed frameworks for cost-effective cancer care and prevention in low, middle, and high-income countries. Lancet Oncol 15, e119-e131 (2014); published online EpubMar (10.1016/S1470-2045(13)70547-3).

3. U.S. Department of Health and Human Services, "The Health Consequences of Smoking—50 Years of Progress: A Report of the Surgeon General. ," (U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health,, Atlanta, GA, 2014.).

4. S. A. Kenfield, M. J. Stampfer, B. A. Rosner, G. A. Colditz, Smoking and smoking cessation in relation to mortality in women. JAMA 299, 2037-2047 (2008); published online EpubMay 7 (10.1001/jama.299.17.2037).

5. C. de Martel, J. Ferlay, S. Franceschi, J. Vignat, F. Bray, D. Forman, M. Plummer, Global burden of cancers attributable to infections in 2008: a review and synthetic analysis. Lancet Oncol 13, 607-615 (2012); published online EpubJun (10.1016/S1470-2045(12)70137-7).

6. M. H. Chang, S. L. You, C. J. Chen, C. J. Liu, C. M. Lee, S. M. Lin, H. C. Chu, T. C. Wu, S. S. Yang, H. S. Kuo, D. S. Chen, Decreased incidence of hepatocellular carcinoma in hepatitis B vaccinees: a 20-year follow-up study. Journal of the National Cancer Institute 101, 1348-1355 (2009); published online EpubOct 7 (10.1093/jnci/djp288).

7. J. M. Lightwood, A. Dinno, S. A. Glantz, Effect of the California tobacco control program on personal health care expenditures. PLoS Med 5, e178 (2008); published online EpubAug 26 (10.1371/journal.pmed.0050178).

8. L. H. Kushi, C. Doyle, M. McCullough, C. L. Rock, W. Demark-Wahnefried, E. V. Bandera, S. Gapstur, A. V. Patel, K. Andrews, T. Gansler, N. American Cancer Society, C. Physical Activity Guidelines Advisory, American Cancer Society Guidelines on nutrition and physical activity for cancer prevention: reducing the risk of cancer with healthy food choices and physical activity. CA Cancer J Clin 62, 30-67 (2012); published online EpubJan-Feb (10.3322/caac.20140).

9. C. A. Thomson, M. L. McCullough, B. C. Wertheim, R. T. Chlebowski, M. E. Martinez, M. L. Stefanick, T. E. Rohan, J. E. Manson, H. A. Tindle, J. Ockene, M. Z. Vitolins, J. Wactawski-Wende, G. E. Sarto, D. S. Lane, M. L. Neuhouser, Nutrition and Physical Activity Cancer Prevention Guidelines, Cancer Risk, and Mortality in the Women's Health Initiative. Cancer Prev Res (Phila) 7, 42-53 (2014); published online EpubJan (10.1158/1940-6207.CAPR-13-0258).

10. Y. Liu, G. A. Colditz, B. Rosner, C. S. Berkey, L. C. Collins, S. J. Schnitt, J. L. Connolly, W. Y. Chen, W. C. Willett, R. M. Tamimi, Alcohol intake between menarche and first pregnancy: a prospective study of breast cancer risk. Journal of the National Cancer Institute 105, 1571-1578 (2013); published online EpubOct 16 (10.1093/jnci/djt213).

11. T. Barnighausen, D. E. Bloom, D. Canning, J. O'Brien, Accounting for the full benefits of childhood vaccination in South Africa. S Afr Med J 98, 842, 844-846 (2008)

12. H. F. Hung, T. H. Chen, Probabilistic cost-effectiveness analysis of the long-term effect of universal hepatitis B vaccination: an experience from Taiwan with high hepatitis B virus infection and Hepatitis B e Antigen positive prevalence. Vaccine 27, 6770-6776 (2009); published online EpubNov 12 (10.1016/j.vaccine.2009.08.082).

13. S. Q. Lu, S. M. McGhee, X. Xie, J. Cheng, R. Fielding, Economic evaluation of universal newborn hepatitis B vaccination in China. Vaccine 31, 1864-1869 (2013); published online EpubApr 3 (10.1016/j.vaccine.2013.01.020).

14. M. C. Tee, Y. Cao, G. L. Warnock, F. B. Hu, J. E. Chavarro, Effect of bariatric surgery on oncologic outcomes: a systematic review and meta-analysis. Surgical endoscopy 27, 4449-4456 (2013); published online EpubDec (10.1007/s00464-013-3127-9).

15. S. H. Chang, C. R. Stoll, G. A. Colditz, Cost-effectiveness of bariatric surgery: should it be universally available? Maturitas 69, 230-238 (2011); published online EpubJul (10.1016/j.maturitas.2011.04.007).

16. M. J. Hassett, E. B. Elkin, What does breast cancer treatment cost and what is it worth? Hematology/oncology clinics of North America 27, 829-841, ix (2013); published online EpubAug (10.1016/j.hoc.2013.05.011).

17. D. Greenberg, C. Earle, C. H. Fang, A. Eldar-Lissai, P. J. Neumann, When is cancer care cost-effective? A systematic overview of cost-utility analyses in oncology. J Natl Cancer Inst 102, 82-88 (2010); published online EpubJan 20 (10.1093/jnci/djp472).

18. B. Edwards, H. L. Howe, L. Ries, M. J. Thun, H. M. Rosenberg, R. Yancik, P. A. Wingo, A. Jemal, E. G. Feigal, Annual report to the Nation on the State of Cancer, 1973-1999, Featuring implications of age and aging on the U.S. cancer burden. Cancer 94, 2766-2792 (2002).

Friday, February 21, 2014

Take a Tour of the Zuum Risk Assessment App

With some exciting projects coming down the pike for our Zuum risk assessment app for iPad, it seemed a great time to re-introduce Zuum with a video demonstration of all that it does.  Its engaging interface and strong evidence base make it a unique addition to the field of mHealth offerings.  With just a 2 - 3 minute questionnaire, the app provides a risk estimate of six major diseases, details the factors that make up the risk of each disease, and puts together a personalized prevention plan.   Coming out of Washington University School of Medicine, Zuum is also free of the types of conflicts linked with many other apps.  Users' information is never sold, leased, or shared with third parties.

 

Tuesday, February 4, 2014

Preventing Cancer Today. Over 50% of New Cancer Cases Can be Prevented by acting on What We Know Right Now

by Graham A. Colditz, MD, DrPH

Much attention is being placed today on the global burden of cancer and the power for prevention to have an enormous benefit for the world through reducing cancer incidence, diagnosis, treatment, pain, and suffering.

A reminder on numbers that have been around for some time – more than half of cancer is diagnosed in low and middle income countries, where access to care is often limited.

Data from the World Health Organization for 2012 (1) show that an estimated 14 million new cases of cancer were diagnosed, and the number is rising every year. The most common cancers diagnosed were those of the:
  • lung (1.8 million cases, 13.0% of the total)
  • breast (1.7 million, 11.9%)
  • colorectal cancer (1.4 million, 9.7%)

Of course, breast cancer is the leading cause of cancer diagnosis among women, where it accounts for 25% of all cancer diagnosed. The 11.9% misleads as these cases occur in about half the population (25% is more accurate: 1.7 million breast cancer cases among the total of all new cancer cases diagnosed among women, 6.7 million total new cases = 25%).

We should be outraged that so few resources and little prevention effort is going to this disease. Much is focused on high-risk women and those at older ages, such as after 50 (2). But some 25% of all breast cancers are diagnosed among women under age 50. We must start prevention far earlier in life to reduce the burden of this disease.

Prevention works.

Cigarette smoking has declined and lung cancer mortality has decreased by one third in the past 20 years. Mortality from lung cancer peaked at 91.1 per 100000 men in 1990 and has declined to 60.3 per 100,000 men in 2010. This is one third fewer lung cancer deaths (3). Stopping smoking reduces lung cancer but also death from heart disease, stroke, and many other cancers too. It is time we focused the same attention on prevention of breast and other cancers, while maintaining our program of prevention of smoking (4). Alcohol, a known carcinogen and cause of breast cancer, needs more attention. We have shown that intake during adolescent and early adult years is significantly related to increased risk of invasive breast cancer and also premalignant breast lesions (5,6).

The World Health Organization recommends policies to limit alcohol intake and to encourage a healthy diet as “best buys” for prevention of chronic diseases (7). For breast cancer, the leading malignancy in women, we must refine the focus of the recommendations and recognize that prevention messages and action must begin early in life and be sustained. We must help women understand that breast cancer prevention strategies will vary according to their age, and that some prevention (childhood diet and exercise) is under the control of mothers and grandparents. Avoidance of alcohol, for example, may be particularly beneficial for young women (6). Improving the presentation of prevention messages for each stage of a women’s life is a top priority.

Today, we should focus again on cancer prevention and the potential for action with what we know already. For more details, visit our recent post in the Huffington Post - 
Half of Cancers Are Preventable: Lower Your Risk With These 8 Steps.

Additional resources for cancer prevention can be found on our page: Preventing Cancer - Today.

References

1. International Agency for Research on Cancer. GLOBOCAN 2012: estimated cancer incidence, mortality and prevalence worldwide in 2012. 2012; Section on Cancer Information. Available at: http://globocan.iarc.fr/Pages/fact_sheets_cancer.aspx. Accessed Jan 26, 2014, 2014.

2. Visvanathan K, Hurley P, Bantug E, et al. Use of pharmacologic interventions for breast cancer risk reduction: American Society of Clinical Oncology clinical practice guideline. J Clin Oncol. Aug 10 2013;31(23):2942-2962.

3. National Center for Health Statistics. Health, United States, 2012: With Special Feature on Emergency Care. Hyattsville, MD: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention; 2013.

4. Koh HK, Sebelius KG. Ending the tobacco epidemic. JAMA. Aug 22 2012;308(8):767-768.

5. Liu Y, Tamimi RM, Berkey CS, et al. Intakes of alcohol and folate during adolescence and risk of proliferative benign breast disease. Pediatrics. May 2012;129(5):e1192-1198.

6. Liu Y, Colditz GA, Rosner B, et al. Alcohol intake between menarche and first pregnancy: a prospective study of breast cancer risk. Journal of the National Cancer Institute. Oct 16 2013;105(20):1571-1578.

7. World Health Organization. Global Action Plan for Prevention and Control of Noncommunicable Diseases, 2013-2020. http://www.who.int/cardiovascular_diseases/15March2013UpdatedRevisedDraftActionPlan.pdf: World Health Organization,; March 15, 2013 2013.

Thursday, November 21, 2013

(Video) Nuts Cut Risk of Cancer, Heart Disease, and Early Mortality

Earlier this month, we posted about recent findings linking nut consumption with a lower risk of benign breast disease in young women.  Further confirming the power of nuts, new results from a large study published in the New England Journal of Medicine reports that men and women who are frequent nut eaters (7 or more time per week) have a lower risk of heart disease and cancer, as well as a 20 percent lower risk of early death than those who rarely eat nuts (less than once per week).

We could further summarize the findings, but this short animated video put out by the Journal does a very good job.

Overall, the evidence is quite compelling that nuts are an important part of a healthy diet and healthy lifestyle.  Just a few ounces of whole nuts or peanut butter a week can have real benefits, and you don't need to be fixated on peanuts.  Other types of nuts or nut-butters have benefits as well and also taste great. So, more than ever, you have license to go nuts.

Wednesday, November 20, 2013

Obesity shortening life among breast cancer survivors, national US data

Obesity is a strong driver for postmenopausal breast cancer. Consistent data from around the world show that overweight and obese women are at increased risk of breast cancer through their postmenopausal years. It is estimated that obesity causes more than 10% of postmenopausal breast cancer. Mechanisms for this include higher circulating estrogen levels among overweight and obese women compared to lean women, and insulin pathways. After menopause the ovaries are less active, and fat cells produce estrogen. Obesity is also related to mortality from many other causes (heart disease, stroke, diabetes, etc.). To put the breast cancer burden in context and evaluate the population health impact of breast cancer on lifespan Dr. Chang and colleagues draw on US National Health Interview Survey data and the linked mortality data. They then estimate life expectancy for women who are normal weight and obese, and the life years lost to breast cancer (see report).

The national data show that the life years lost among women diagnosed with breast cancer are greater for younger women than those diagnosed at older ages. This makes good sense. In addition, obese women with breast cancer had greater loss of life than non-obese women. For example, women who were obese and diagnosed with breast cancer before age 50 lost on the average 9.8 years compared to non-obese women who lost 7.8 years. For women diagnosed after age 70 obese women lost approximately 5 years and the nonobese 3.7 years. This pattern was also seen in analysis of African American women.

Choosing measures for evaluation of population level health remains an area that the National Academy of Sciences continues to address. They have recommended life expectancy and quality of life as appropriate measures for population health. This report, evaluating life years lost associated with breast cancer applies this framework. The data clearly support a greater emphasis on the prevention and control of obesity given its impact on this the second most common cause of cancer mortality in women.

Monday, November 4, 2013

Prevention's True Potential in the Ongoing "War on Cancer"


The latest in the New York Times' Retro Report series tackles the launch and subsequent progress of the Nixon administration's 1971 National Cancer Act, dubbed the "War on Cancer."  The ultimate hope of the act was that - with an economic and human power push similar to that used with the first moon landing in the late 60s - cancer as a disease could be controlled and cured nationally in just a handful of years.

As the incisive video reports, the reality has been quite different. No overall cure arose in 5, 10, or even 40 years. And for most of those years, in fact, cancer seemed to be a disease continually on the rise.

More recently, however, there have been positive signs - most notably a downward trend in overall death rates from the disease.  Some of these gains have certainly come from new and improved treatments, and some from factors related to prevention and screening - drops in smoking, fewer women using post-menopausal hormones, and improving rates of screening for breast, colon, and cervical cancer.

And it is this progress in prevention that makes the closing sentence of the video's accompanying article written by Gina Kolata very strange.  She closes the piece saying that prevention is the area least understood when it comes to the fight against cancer:
"The biggest challenge, prevention, remains. And other than stopping smoking, nothing yet has been terribly promising."
The reality, though, could not be be farther from the truth.  The real hope in controlling cancer - especially from a practical standpoint - is through prevention, and there is compelling evidence that over half of all cancer cases (and 75 percent of some specific kinds of cancer) could be prevented by things we already know and that we can all do:  such as exercising, maintaining a healthy weight, avoiding smoking, eating a healthy diet, avoiding too much alcohol, and getting appropriate screening tests.

Yes, the challenge in cancer prevention - as in most other important chronic diseases - is helping people put such behaviors into practice.  But to deny their potential benefits in the efforts to control cancer is careless and wrong.

To see just how much of an impact a healthy lifestyle can have on cancer risk, see these resources:

Wednesday, October 30, 2013

Rosner-Colditz model predicting breast cancer risk outperforms Gail in independent cohort.

Validation of breast cancer risk prediction models in an independent prospective data set is rare. We drew on prospective data from the Nurses’ Health Study and the California Teachers Study to validate the Rosner-Colditz breast cancer incidence model and compare it to the Gail model.1 (see report) The Rosner-Colditz model includes a range of established reproductive factors that are directly related to breast cancer risk, body mass index, and alcohol intake. 2 These are known causes of breast cancer. In particular, we include age at menopause and type of menopause (surgical or natural) – factors omitted from the Gail model. After aligning time periods for follow-up, we restricted populations to comparable age ranges (47 to 74), and followed them for incident invasive breast cancer (follow-up 1994 to 2008, Nurses’ Health Study [NHS]; and 1995 to 2009, California Teachers Study [CTS]). We identified 2026 cases during 540,617 person-years in NHS, and 1400 cases during 288,111 person-years in CTS.

To reflect application of a breast risk prediction model in clinical practice such as mammography screening services or primary care, we fit the Rosner–Colditz log incidence model and the Gail model using baseline data. We imputed future use of hormones based on type and prior duration of use and other covariates at the baseline. We assessed performance using area under the curve (AUC) and calibration methods. Participants in the CTS had fewer children, were leaner, consumed more alcohol, and were more frequent users of postmenopausal hormones. Incidence rate ratios for breast cancer showed significantly higher breast cancer in the CTS (IRR= 1.32, 95% CI 1.24 to 1.42). Parameters for the log-incidence model summarizing the relation for reproductive variables, history of benign breast disease, menopause and use of hormone therapy as well as alcohol, obesity, and family history, were comparable across the two cohorts. In the NHS the AUC was 0.60 (se 0.006) and applying the model to the CTS the performance in the independent data set (validation) was 0.586 (se 0.008). The Gail model gave values of 0.547 (se 0.008), a statistically significant 4% lower. For women 47 to 69, more typical of those for whom risk estimation would be indicated clinically, the AUC values for the log incidence model are 0.608 in NHS and 0.609 in CTS; and for Gail are 0.569 and 0.572. In both cohorts, performance of both models dropped off in older women 70 to 87.

We also assessed calibration – a measure of how well the model predicts incidence for a population. Calibration showed good estimation against SEER (used as a measure of US national incidence rates for breast cancer) with a non-significant 4% underestimate of overall breast cancer incidence when applying the model in the CTS population.


In sum, the Rosner-Colditz model performs consistently well when applied in an independent data set. Performance is stronger predicting incidence among women 47 to 69 and over a 5-year time interval. AUC values exceed those for Gail by 3 to 5% based on AUC when both are applied to the independent validation data set. Models may be further improved with addition of breast density or other markers of risk beyond the current model. Research in collaboration with the Breast Health Center is currently pursing these improvement.

Citations

1. Rosner, B.A. et al. Validation of Rosner-Colditz breast cancer incidence model using an independent data set, the California Teachers Study. Breast Cancer Res Treat (2013).


2. Colditz, G. & Rosner, B. Cumulative risk of breast cancer to age 70 years according to risk factor status: data from the Nurses' Health Study. Am J Epidemiol 152, 950-64. (2000).