Lung Cancer and Smoking Case Study Discussion

Lung Cancer & Smoking Case Study A causal relationship between cigarette smoking and lung cancer was first suspected in the 1920s on the basis of clinical observations. To test this apparent association, numerous epidemiologic studies were undertaken between 1930 and 1960. Two studies were conducted by Richard Doll and Austin Bradford Hill in Great Britain. The first was a case-control study begun in 1947 comparing the smoking habits of lung cancer patients with the smoking habits of other patients. The second was a cohort study begun in 1951 recording causes of death among British physicians in relation to smoking habits. This case study deals first with the case-control study, then with the cohort study. Data for the case-control study were obtained from hospitalized patients in London and vicinity over a 4-year period (April 1948 – February 1952). Initially, 20 hospitals, and later more, were asked to notify the investigators of all patients admitted with a new diagnosis of lung cancer. These patients were then interviewed concerning smoking habits, as were controls selected from patients with other disorders (primarily non-malignant) who were hospitalized in the same hospitals at the same time. Data for the cohort study were obtained from the population of all physicians listed in the British Medical Register who resided in England and Wales as of October 1951. Information about present and past smoking habits was obtained by questionnaire. Information about lung cancer came from death certificates and other mortality data recorded during ensuing years. Question 1: What makes the first study a case-control study? Question 2: What makes the second study a cohort study? The remainder of Part I deals with the case-control study. Question 3: Name three other sources where cases might have been found and three other sources where controls may have been found. Question 4: Give four (4) reasons as to why hospitals may have been chosen as the setting for this study. Question 5: What are the advantages of selecting controls from the same hospitals as cases? Question 6: Do you believe the hospitalized persons with lung cancer (cases) are representative (similar) of all patients with lung cancer? Explain your answer. Question 7: Do you believe the hospitalized persons without lung cancer (controls) are representative (similar) to people in the general population? Explain your answer. Question 8: How may these representativeness issues affect interpretation of the study’s results? Please discuss how it could affect the odds ratio results for this case-control study. Over 1,700 patients with lung cancer, all under age 75, were eligible for the case-control study. Lung Cancer and Smoking Case Study Discussion

About 10% of these persons were not interviewed because of death, discharge, severity of illness, or inability to speak English. An additional group of patients were interviewed but later excluded when initial lung cancer diagnosis proved mistaken. The final study group included 1,530 cases. The following table shows the relationship between cigarette smoking and lung cancer among male cases and controls. Table 1. Smoking status before onset of the present illness, lung cancer cases and matched controls with other diseases, Great Britain, 1948-1952. Cases Cigarette smoker Controls 1,522 1,462 Non-smoker 8 68 Total 1,530 1,530 NOTE: For #9-#14, show equations along with your answers. Question 9: From this table, calculate the proportion of cases and controls who smoked. Proportion smoked, cases: Proportion smoked, controls: Question 10: What do you infer from these proportions? Question 11a: Calculate the odds of smoking among the cases. Divide # of cases who smoked by the # of cases who did not smoke. Question 11b: Calculate the odds of smoking among the controls. Divide # of controls who smoked by the # of controls who did not smoke. Question 12: Calculate the ratio of these odds (divide the odds). How does this compare with the cross-product ratio (this is the Odds Ratio equation from Ch. 6)? Question 13: What do you infer from the odds ratio about the relationship between smoking and lung cancer? Make a statement using the actual OR. Table 2 shows the frequency distribution of male cases and controls by average number of cigarettes smoked per day. Table 2. Most recent amount of cigarettes smoked daily before onset of the present illness, lung cancer cases and matched controls with other diseases, Great Britain, 1948-1952. Daily number of cigarettes # Cases # Controls 8 68 1-14 622 785 15-24 498 482 25+ 402 195 All smokers 1,522 1,462 Total 1,530 1,530 0 Odds Ratio referent Question 14: Compute the odds ratio by category of daily cigarette consumption, comparing each smoking category to nonsmokers. Question 15: What do these results tell you? Although the study demonstrates a clear association between smoking and lung cancer, cause-and-effect is not the only explanation. Question 16: What are the other possible explanations for the apparent association? Include and explain specific to this study at least three types of bias in your answer. The next section of this case study deals with the cohort study. Data for the cohort study were obtained from the population of all physicians listed in the British Medical Register who resided in England and Wales as of October 1951. Questionnaires were mailed in October 1951, to 59,600 physicians. The questionnaire asked the physicians to classify themselves into one of three categories: 1) current smoker, 2) ex-smoker, or 3) nonsmoker. Smokers and Question 17: ex-smokers were asked the amount they smoked, their method of smoking, the age they started to smoke, and, if they had stopped smoking, how long it had been since they last smoked. Nonsmokers were defined as persons who had never consistently smoked as much as one cigarette a day for as long as one year. Usable responses to the questionnaire were received from 40,637 (68%) physicians, of whom 34,445 were males and 6,192 were females. How might the response rate of 68% affect the study’s results? The next section of this case study is limited to the analysis of male physician respondents, 35 years of age or older. were from cytology, bronchoscopy, or X-ray alone; and only 1% were from just case history, physical examination, or death certificate. The occurrence of lung cancer in physicians responding to the questionnaire was documented over a 10-year period (November 1951 through October 1961) from death certificates filed with the Registrar General of the United Kingdom and from lists of physician deaths provided by the British Medical Association. All certificates indicating that the decedent was a physician were abstracted. For each death attributed to lung cancer, medical records were reviewed to confirm the diagnosis. Of 4,597 deaths in the cohort over the 10-year period, 157 were reported to have been caused by lung cancer; in 4 of the 157 cases this diagnosis could not be documented, leaving 153 confirmed deaths from lung cancer. Diagnoses of lung cancer were based on the best evidence available; about 70% were from biopsy, autopsy, or sputum cytology (combined with bronchoscopy or X-ray evidence); 29% The following table shows numbers of lung cancer deaths by daily number of cigarettes smoked at the time of the 1951 questionnaire (for male physicians who were nonsmokers and current smokers only). Person-years of observation (“person-years at risk”) are given for each smoking category. The number of cigarettes smoked was available for 144 of the persons who died from lung cancer. Table 3. Number and rate (per 1,000 person-years) of lung cancer deaths by number of cigarettes smoked per day, Doll and Hill physician cohort study, Great Britain, 1951-1961. Daily number of cigarettes smoked Deaths from lung cancer Personyears at risk 0 3 42,800 1-14 23 38,600 15-24 56 38,900 25+ 62 25,100 Lung Cancer and Smoking Case Study Discussion

All smokers 141 102,600 Total 144 145,400 Question 18: Mortality rate per 1000 person-years Rate Ratio 0.07 referent Rate Difference per 1000 person-years Referent Compute lung cancer mortality rates, rate ratios, and rate differences for each smoking category. What do each of these measures mean (definitions)? NOTE: For 19, 20, 22, and 23 you MUST show the equations along with the answers. Question 19: What proportion of lung cancer deaths among all smokers can be attributed to smoking? (Hint: use the equation for Etiologic Fraction [also known as Attributable Risk Percent]) Question 20: If no one had smoked, how many deaths from lung cancer would have been averted? The cohort study also provided mortality rates for cardiovascular disease among smokers and nonsmokers. The following table presents lung cancer mortality data and comparable cardiovascular disease mortality data. Table 4. Mortality rates (per 1,000 person-years), rate ratios, and excess deaths from lung cancer and cardiovascular disease by smoking status, Doll and Hill physician cohort study, Great Britain, 1951-1961. Mortality rate per 1,000 person-years Attributable risk percent among smokers Smokers Non-smokers All Rate ratio Excess deaths per 1,000 person-years Lung cancer 1.37 0.07 0.99 19.6 1.3 95% Cardiovascular disease 9.51 9.51 7.32 7.32 8.87 8.87 1.3 1.3 2.19 2.19 23% 23% Question 21: Which cause of death has a stronger association with smoking? Why? (you need to use the RRs and ARs to make your case and interpret them correctly in your statements) In calculating the attributable risk percent, the excess lung cancer deaths attributable to smoking is expressed as a percentage of all lung cancer mortality among all smokers. The attributable risk percent of 95% for smoking may be interpreted as the proportion of lung cancer deaths among smokers that could have been prevented if they had not smoked. A similar measure, the population attributable risk percent expresses the excess lung cancer deaths attributable to smoking as a percentage of all lung cancer mortality among the entire population. From a prevention perspective, the population attributable risk percent for a given exposure can be interpreted as the proportion of cases in the entire population that would be prevented if the exposure had not occurred. The population attributable risk percent is often used in assessing the cost-effectiveness and costbenefit of community-based intervention programs. One formula for the population attributable risk percent is: PAR% = (Incidence in entire population – Incidence in unexposed) / Incidence in entire population Question 22: Calculate the population attributable risk percent for lung cancer mortality and for cardiovascular disease mortality. How do they compare? How do they differ from the attributable risk percent? Lung Cancer and Smoking Case Study Discussion

Question 23: How many lung cancer deaths per 1,000 persons per year are attributable to smoking among the entire population? How many cardiovascular disease deaths? What do these results tell you? The following table shows the relationship between smoking and lung cancer mortality in terms of the effects of stopping smoking. Table 5. Number and rate (per 1,000 person-years) of lung cancer deaths for current smokers and exsmokers by years since quitting, Doll and Hill physician cohort study, Great Britain, 1951-1961. Cigarette smoking status Lung cancer deaths Rate per 1000 person-years 141 1.37 19.6 5 7 3 2 0.67 0.49 0.18 0.19 9.6 7.0 2.6 2.7 3 0.07 1.0 (ref) Current smokers For ex-smokers, years since quitting: <5 years 5-9 years 10-19 years 20+ years Nonsmokers Rate Ratio Question 24: Using the rate ratios from above, what does the trend imply for the practice of public health and preventive medicine? Question 25: Look back and compare the odds ratios (ORs) from the case-control and the rate ratios (RRs) from the cohort study. Comment on the similarities and differences between the studies in the computed measures of association. Question 26: Which of the studies (case-control or cohort) has a larger sample size, costs more, and takes longer to complete? For the first six issues below, cite which study is best to use (case-control or cohort study). For the last 3 types of bias, cite which study is less likely to have that particular type of bias (case-control or cohort). Answer 26 1) Study a rare disease 2) Study a rare exposure 3) Study multiple exposures 4) Study multiple outcomes 5) Study progression of illness 6) Calculate disease rates 7) Recall bias 8) Loss to follow-up 9) Selection bias Question 27: Which type of study (cohort or case-control) would you have done first? Why? What would your second study be and why? Question 28: Which of the following criteria for causality are met by the evidence presented from these two studies? Answer 28 YES Strong association Consistency among studies Exposure precedes disease Dose-response effect Biologic plausibility NO … Lung Cancer and Smoking Case Study Discussion