Part A MFPH Examination – Paper IIB specimen
Specimen section 1
You are a public health advisor in an inner city community within a large metropolitan area of a developed country. In recent years, a ‘congestion charge’ has been introduced which requires drivers of private vehicles to pay a daily fee for driving into the city centre. Traffic census data indicate that this has resulted in a 20% decline in car and light van traffic within the congestion charge zone. The following statistics have been compiled from one of the primary care health centres situated within the congestion charge zone:
Patients attending the primary care centre for asthma during: | |||
12 months before the congestion charge was introduced |
450 | ||
12 months after the congestion charge was introduced | 500 | ||
Primary care consultations for acute asthma attacks during: | |||
12 months before the congestion charge was introduced | 175 | ||
12 months after the congestion charge was introduced | 125 |
Questions
(a) What further single item of information would you require to estimate the annual period prevalence of asthma in this area, after the introduction of the congestion charge zone? (1 mark)
(b) Describe and calculate a suitable measure for comparing the occurrence of acute asthma attacks before and after the introduction of the congestion charge. (2 marks)
(c) State two assumptions you have used in your calculation in (b). (2 marks)
(d) Calculate an appropriate statistical test to determine whether the change in incidence of acute asthma attacks around the time of introduction of the congestion charge was statistically significant at the 5% level. (3 marks)
(e) Write no more than four sentences for inclusion in your public health department’s annual report, summarising your conclusions regarding the effect of the congestion charge policy on the burden of asthma locally. (2 marks)
Specimen section 2
Results relating to the survival of successive cohorts of women diagnosed with breast cancer were recently published from a Western European country and are illustrated in the figure. A national programme of breast cancer screening was introduced in 1989.
Figure. Breast cancer specific survival in 5-year cohorts defined by date of diagnosis between 1974 and 1999
Questions
(a) Choose the single answer that best defines “breast cancer specific survival” (1 mark)
A: The proportion of women who survive for a specified period without developing breast cancer.
B: The proportion of breast cancer patients who survive for a specified period after their date of diagnosis.
C: The proportion of breast cancer patients who survive for a specified period after the date of diagnosis with breast cancer, or whose cause of death is not certified as breast cancer.
D: The proportion of breast cancer patients who survive for a specified period after the date of diagnosis with breast cancer, or who die from non-accidental causes.
E: The proportion of breast cancer patients who survive for a specified period relative to the proportion of the general population of a similar age who survive for the same period.
(b) Give three possible explanations for the larger change between the 1985-1989 and the 1990-1994 cohorts compared with that between the other cohorts. (3 marks)
(c) Describe two other important features of the data shown in the figure. (2 marks)
Further survival information is provided in the table below.
Table. Overall survival (%) in the 1980-1984 and 1990-1994 diagnostic cohorts at 5, 10 and 15 years of follow-up
% Survival at: | 1980-1984 | 1990-1994 | Proportional risk reduction |
5 years | 73 | 88 | 0.56 |
10 years | 55 | 80 | 0.56 |
15 years | 46 | 78 | 0.59 |
(d) What does the term ‘proportional risk reduction’ mean and how was it calculated? (2 marks)
(e) Write no more than four sentences for inclusion in a press release to your local newspaper, summarising the findings given in the table above, and their interpretation. (2 marks)
Specimen section 3
Results were recently published from a register of visual impairment in childhood in a developed country. Only children notified up to the age of 10 years were eligible for inclusion on the register. Between 1984 and 1998, a total of 691 children with visual impairment were notified to the register (see table below), of whom 130 have subsequently died, with 58% dying before they reached their fifth birthday.
Table. Characteristics of the children with any degree of visual impairment (moderate, severe or blind) born between 1984 and 1998
Number of cases on the register n=691 | Number of live births in the catchment population n=520,240 | |
Singleton or multiple birth: | ||
Multiple | 35 | 13,239 |
Singleton | 656 | 507,001 |
Sex of child: | ||
Male | 415 | 266,542 |
Female | 276 | 253,698 |
Questions
(a) Calculate the overall case fatality of childhood visual impairment. (1 mark)
(b) Calculate the cumulative incidence ratio for any degree of visual impairment in males compared with females. (2 marks)
(c) The cumulative incidence ratio for multiple births compared to singleton births is 2.0 (95% confidence interval 1.5 to 2.9). In no more than three sentences, explain what this statement means and comment on the statistical significance of this result. (3 marks)
The results from this analysis of registered cases were compared with data from a cross-sectional study of children whose visual acuity was measured when they were 10 years old. Assuming that both sets of data are representative of the same national population:
(d) Explain in one or two sentences how and why the two sets of results might differ in their estimate of the incidence of blindness? (2 marks)
(e) Explain in one or two sentences how and why the two sets of results might differ in their estimate of the incidence of moderate visual impairment? (2 marks)
Specimen section 4
Your healthcare organisation is providing funding for the drug trastuzumab for the treatment of HER2 positive cases of breast cancer. This costs £25,000 per course of treatment. Testing of breast cancer tissue to determine HER2 status involves the use of immuno-histochemistry (IHC) which is a tissue stain test, and/or fluorescent in situ hybridisation (FISH) which is a genetic test. Your healthcare organisation currently uses IHC which costs £40 per test. FISH is more expensive at £150 per test but is less prone to observer variation.
You have been asked to conduct a review and report on the implications of different testing regimens. For the purposes of your review all the breast cancer biopsy specimens tested during one year were subjected to FISH testing in addition to IHC. The results are shown in the table below.
Table. Annual number of biopsy specimens by immuno-histochemistry (IHC) category and proportion of FISH positive results within each IHC category
Immuno-histochemistry result | Number of biopsies from your local laboratory with this IHC result | Percentage of positive FISH results for biopsies within each IHC category |
Negative | 22,500 | 1% |
Weakly positive | 3,600 | 50% |
Strongly positive | 3,900 | 94% |
The current policy is that all women with "strongly positive" IHC results are offered treatment with trastuzumab.
Questions
(a) Assuming that FISH is the reference (gold) standard for HER2 positivity, what is the positive predictive value of a "strongly positive" IHC result? (1 mark)
(b) Compare the cost of performing FISH tests on all "strongly positive" IHC specimens with the saving in treatment costs that would be expected from applying this 2-step approach. (2 marks)
(c) Assuming that FISH is the reference (gold) standard for HER2 positivity, calculate the sensitivity of the test programme to detect HER2 positive cases if:
(i) Only "strongly positive" IHC results are considered test positive (1 mark)
(ii) Both "strongly positive" and "weakly positive" IHC results are considered test positive (1 mark)
(iii) All specimens are tested by FISH instead of IHC (1 mark)
(d) Assuming FISH is the gold standard for HER2 positivity, calculate the marginal test-associated cost of identifying one HER2 positive case if all specimens were tested by FISH, instead of the current policy of testing all specimens by IHC and treating only those that are strongly IHC positive. (3 marks)
(e) What single additional piece of information would be most important to complete an economic evaluation of whether to test all specimens by FISH, instead of IHC? (1 mark)
Model answer to specimen section 1
(a) | Catchment population, registered population or population at risk | |||||||
(b) | Incidence (episodes/spells) ratio = 125/175 = 0.71, or a 29% relative reduction. A ratio measure is preferable to a difference measure as it has no units and we lack a population denominator. | |||||||
(c) | Population remains constant (in size and demographic structure) over the 2 years. Proportion of all acute attacks presenting in general practice remains constant | |||||||
(d) |
The numbers of acute asthma attacks can be considered as Poisson variables with variance = count. The difference between the counts can then be compared to the variance of the difference (variance of the difference = sum of the variances = sum of the counts). A Wald test (SND or z-test) or chi-square test can then be constructed and tested for statistical significance with reference to standard tables.
Difference = 175-125 = 50 |
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Another valid approach would be to test the incidence ratio (but this requires use of logarithms to base e (ln), not available on the calculators provided):
ln (count1/count2) = ln (count1 – ln (count2)Then compare ln(125/175) to Var(ln(ratio)) by SND or Chisq approach as above. |
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(e) | Interpret as statistically significant, compare with relatively unchanged prevalence (500 v 450, assuming constant population), consider alternative explanations and suggest comparison with trends in an area outside the CC zone. |
Model answer to specimen section 2
(a) | C | |||||||
(b) | Improvements in treatment (new drugs, changes in clinical guidelines and practice). Earlier diagnosis (lead-time bias) and detection of slower-growing prevalent cases (length bias), both resulting from increased coverage of breast cancer screening. | |||||||
(c) | Steady improvement in survival in successive cohorts. Similar trends at all durations of follow-up (1-10 years), consistent with (approximately) proportional hazards. | |||||||
(d) | Relative reduction in cumulative risk of mortality. Percentage survival needs to be converted to percentage dying (over 5, 10, 15 years) and then express the reduction in mortality risk as a proportion of the original mortality risk. For example, for 5-year data:
1980-1984 5-year mortality risk = 100-73 = 27% |
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(e) | Explain what is meant by overall survival. Describe survival chances for women in each cohort. Note that improvement is sustained throughout 15 years. Comment on the consistency of the proportional risk reductions. |
Model answer to specimen section 3
(a) | 130/691 = 18.8% | |||||||
(b) | (415/266,542) / (276/253,698) = 1.43 | |||||||
(c) | Comment on the magnitude and direction of effect ("doubling of risk among multiple births"). 95% probability / confidence that the true value lies within this range (or, if the study was repeated 100 times, expect 95 results within this range). 95% confidence interval does not include 1, so p<0.05 (in fact, lower 95% CL considerably greater that 1, so p can be deduced to be much less than 0.05). | |||||||
(d) | Cross-sectional survey does not include children who die before 10 years, and the mortality is high among visually impaired children. Thus, lifetime prevalence at 10 will be less than cumulative incidence as measured by the register (assuming that all blind children are registered, which is probably a reasonable assumption). | |||||||
(e) | Ascertainment of moderate visual impairment at the cross-sectional survey could be more comprehensive, and would pick up (live) cases missed off the register, leading to a higher lifetime prevalence than registered cumulative incidence. |
Model answer to specimen section 4
(a) | 94%, as shown in the table. | |||||||
(b) | Extra FISH tests | 3,900 | @ | £150 | £ 585,000 extra costs | |||
HER2-ves untreated | 234 | @ | £25,000 | £5,850,000 costs saved | ||||
(234 = 6% of 3,900) | £5,265,000 net saving | |||||||
The saving in unnecessary / ineffective treatment costs clearly outweighs the costs of the additional FISH tests, despite the high PPV in this "strongly positive" IHC group. | ||||||||
(c) | FISH+ | FISH- | ||||||
IHC negative | 22,500 | x | 1% | = | 225 | 22,275 | ||
IHC weak + | 3,600 | x | 50% | = | 1,800 | 1,800 | ||
IHC strong + | 3,900 | x | 94% | = | 3,666 | 234 | ||
Total | 30,000 | 5,691 | 24,309 | |||||
(i) | Sensitivity of IHC strong positive = 3,666/5,691 = 64.4% | |||||||
(ii) | Sensitivity of IHC strong or weak = 5,466/5,691 = 96.0% | |||||||
(iii) | Sensitivity of FISH testing (gold standard) = 100% (by definition) | |||||||
(d) | The current (IHC test) regimen detects 3,666 HER2 positive cases (table above) and costs 30,000 x £40 = £1,200,000 = £1.2M. If all 30,000 specimens were tested with FISH (the gold standard), there would be no need for preliminary IHC testing. All 5,691 HER2 positives would be detected at a cost of 30,000 x £150 = £4,500,000 = £4.5M. Thus, 5,691-3,666 = 2,025 extra cases would be detected at an additional cost of £3.3M. The marginal cost per additional HER2 positive case is: 3.3M/2,025 = £1,629.63 per case. |
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(e) | The single most important piece of information would be the benefits (in terms of improved survival and/or quality of life) for HER2-positive women undergoing treatment with trastuzumab. |