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HSS4303B – Intro to Epidemiology Jan 18, 2010 – Mortality Rates, et al classes.deonandan.com/hss4303.

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Presentation on theme: "HSS4303B – Intro to Epidemiology Jan 18, 2010 – Mortality Rates, et al classes.deonandan.com/hss4303."— Presentation transcript:

1 HSS4303B – Intro to Epidemiology Jan 18, 2010 – Mortality Rates, et al classes.deonandan.com/hss4303

2 Epidemiologic measures Mortality Case fatality rates Years of potential life lost (YPLL) Survival Disability assisted life year (DALY) Disability Adjusted Life Expectancy (DALES) And other goodies

3 Crude Death Rate Deaths per year per 1000 people ->

4 Cancer related deaths What is the trend in the number of deaths from 1900 to 2000? What is the trend in the risk of death from 1900 to 2000?

5 Mortality rate Denominator must include all potential persons eligible to be included in the numerator Mortality rates can be calculated for specific groups of people such as children, age specific, postmenopausal, females, boys less than 10 years, etc. Specific rates Age specific Disease specific Cause specific

6 Specific mortality rates Children specific mortality rate Lung cancer specific mortality rate Children specific leukemia mortality rate

7 Case Fatality Rate Case fatality (CF) is the risk of death from a certain disease CF = Number of deaths / Number of diagnosed patients with the disease Ebola Virus is among the deadliest viruses with a case fatality rate of roughly 90%

8 Case fatality rate Mortality rate – Denominator is the entire population at risk of dying from the disease (with or at risk) – Measures risk of dying from the disease Case-fatality rate – Denominator is limited to those who already have the disease – Measures severity of disease – Measures benefits of new therapy

9 Mortality rates and case-fatality rates Assume a population of 100,000 people of which 20 are sick with disease X and in one year 18 of the 20 die from the disease Mortality rate in that year as a result of disease X: The case-fatality rate of disease X is: 18/100000 = 0.018% 18/20 = 90%

10 If a population of a country is 4.5 million and if in a given year 45000 deaths from all causes occurred in that country of which 30,000 deaths were AIDS related among 650,000 HIV infected people. What is the mortality rate from all causes? What is cause specific mortality rate for AIDS? What is case-fatality rate for AIDS? 45000/4500000 = 1% 30000/4500000 = 0.7% 30000/650000 = 4.6%

11 Mortality rates and incidence rates Mortality is an index of the severity of a disease Mortality can also be an index of the _____________ – Therefore mortality can be used an index of disease incidence Mortality is a good index of _______________ when: – The case fatality rate is high – The duration of disease is short – Mortality is a good index of incidence for pancreatic cancer because the survival is short and fatality rate is high Incidence?

12 Proportionate Mortallity Rate or Ratio (PMR) The number of deaths from a specific cause in a specific period of time per 100 deaths from all causes in the same time period. (The fraction of all deaths from a given cause in the study population divided by the same fraction from a standard population) A tool for investigating cause- specific risks when only data on deaths are available.

13 Proportionate mortality Rate/Ratio

14 If a population of a country is 4.5 million and if in a given year 45000 deaths from all causes occurred in that country of which 30,000 deaths were AIDS related among 650,000 HIV infected people. What is the mortality rate from all causes? What is cause specific mortality rate for AIDS? What is case-fatality rate for AIDS? What is the PMR? 45000/4500000 = 1% 30000/4500000 = 0.7% 30000/650000 = 4.6% 30000/45000 = 66.7%

15 Mortality rates in two communities Table 4-2. Comparison of Mortality Rate and Proportionate Mortality: I. Deaths from Heart Disease in Two Communities, A and B Community ACommunity B Mortality rate from all causes30/1,00015/1,000 Proportionate mortality from heart disease10%20% Mortality rate from heart disease3/1,000 What is the risk of dying from heart disease? Community ACommunity B Mortality rate from all causes3%1.5% Proportionate mortality from heart disease10%20% Mortality rate from heart disease0.3%

16 Mortality rates in two communities Raywatville and Gomesland are two adjacent communities. Raywatville has 1000 damn sexy residents. Gomesland has 1000 dignified residents. In Raywatville in 2007, 30 people died from all causes, while in the same year 15 died in Gomesland. That same year, in each community 3 of the deaths were due to heart disease. A) compute crude mortality rate s for both communities B) Compute PMR for heart disease both communities C) Compute specific mortality rate for heart disease for both communities D) What is the risk of dying of heart disease in each community? E) Which community has the greater risk of dying of heart disease?

17 RaywatvilleGomesland Mortality rate from all causes Proportionate mortality from heart disease Mortality rate from heart disease

18 RaywatvilleGomesland Mortality rate from all causes30/1,00015/1,000 Proportionate mortality from heart disease10%20% Mortality rate from heart disease3/1,000

19 RaywatvilleGomesland Mortality rate from all causes3%1.5% Proportionate mortality from heart disease10%20% Mortality rate from heart disease0.3% D) What is the risk of dying of heart disease in each community? E) Which community has the greater risk of dying of heart disease?

20 Early and Late Mortality

21 Let’s say there’s an intervention to try and prevent death caused by a disease. We distinguish between “early” and “late” mortality rates, to account for the lag in the intervention having an effect. 1.The early mortality rate, the total number of deaths in the early stages of an ongoing treatment, or in the period immediately following an acute treatment, divided by those at risk. 2.The late mortality rate, the total number of deaths in the late stages of an ongoing treatment, or a significant length of time after an acute treatment, divided by those at risk.

22 Example: Early Mortality Rate of Morbidly Obese Patients after Tracheotomy by Ilaaf Darrat, MD, Kathleen Yaremchuk, MD The Laryngoscope, Volume 118 Issue 12, 2009, Pages 2125 - 2128 Objectives: To 1) determine the early mortality rate (within 30 days) of morbidly obese patients after tracheotomy; 2) determine the difference between the mortality rate after tracheotomy of morbidly obese patients and patients who are not morbidly obese; and 3) determine the difference between the mortality rate after tracheotomy adjusted for case mix index (CMI) of morbidly obese patients and patients who are not morbidly obese.

23 Example Decreasing Late Mortality Among Five-Year Survivors of Cancer in Childhood and Adolescence: A Population-Based Study in the Nordic Countries by Moller et al Journal of Clinical Oncology, Vol 19, Issue 13 (July), 2001: 3173-3181 PURPOSE: To assess the risk of death in patients who survive more than 5 years after diagnosis of childhood cancer and to evaluate causes of death in fatal cases. RESULTS. Overall late mortality was significantly lower in patients treated during the most recent period of time, 1980 to 1989, compared with those treated from 1960 to 1979 (hazard ratio, 0.61; 95% CI, 0.54 to 0.70), and there was no increase in rates of death due to cancer treatment.

24 Early PeriodLater Period Cause of death Mortality Rate Proportionate Mortality Mortality Rate Proportionate Mortality Heart disease 40/1000%80/1000% Cancer20/1000% % All other causes 20/1000% % All deaths80/1000100%120/1000100% Consider a population of 1000 people. Compute: A)case-specific mortality rates for each period B)PMRs for each period

25 Early PeriodLater Period Cause of death Mortality Rate Proportionate Mortality Mortality Rate Proportionate Mortality Heart disease 40/100050%80/100067% Cancer20/100025%20/100017% All other causes 20/100025%20/100017% All deaths80/1000100%120/1000~100% Consider a population of 1000 people with the following deathsConsider a population of 1000 people. Compute: A)case-specific mortality rates for each period B)PMRs for each period

26 Mortality rates and proportionate mortality rates

27 Dumbass Disease Nosepickery Disease specific mortality rate 6%1% PMR14%26% CFR64%13% Which disease is more serious?

28 Comm AComm B Mortality rate from all causes 20/1,00010/1,000 Proportionate mortality from heart disease 30% Mortality rate from heart disease 6/1,0003/1,000 Rate of death Proportion Rate of death from heart disease A) What is the risk of death in each community? B) What is the risk of death from heart disease? C) What is the burden of heart disease in each community?

29 Burden of Disease How would you measure a population’s “burden”?

30 Years of potential life lost (YPLL) Is a measure of premature mortality or early death Deaths at a younger age involves a loss of future productive years of life Eg, if you are expected to live to 65 and a disease kills you at age 20, then you have lost 45 years (65-20). So the YPLL for this disease is 45

31 YPLL Canada, 1993 – injuries killed 10,286 people – Cancer killed 25,687 people But Cancer affected more young people, and injuries killed more old people – cancer caused 302,585 YPLL – injuries caused 336,593 YPLL Which disease is more serious?

32 YPLL Obviously you need: – A specific time period – A defined population – A defined life expectancy – YPLL for a population for a disease = sum of all YPLL of individuals lost to that disease

33

34 YPLL for children YPLL before the age of 65 years for children and young adults younger than 20 years of age

35 Use of YPLL YPLL assists in – Establishing research and resources priorities – Surveillance of temporal trends in premature mortality – Evaluating the effectiveness of program intervention

36 Another Option for Disease Burden – “Quality Adjusted Life Years” – www.jr2.ox.ac.uk/bandolier/booth/glossary/QALY.htm – Used to measure both the quality and quantity of life years lived as a result of a medical intervention – QALY = (year lived) x (index) Index = 0  1 0 = death, 1 = perfect health – E.g., new heart valve saves your life, but hinders your quality of life QALYs

37 QALY Example Bob is 50 and has heart disease. He is expected to live for another 10 years. His is given a special heart stent that extends his life such that he is expected to live till 80 Because of the stent, he must give up all exertion, which really sucks It is believed that the stent represents a quality index of 0.6 How many QALYs did the stent give Bob?

38 QALY Example Without stent, Bob would have lived 10 years With stent, Bob lives 30 years (80-50) Thus, Bob gains 20 years QALYs = (years gained) x (index) = 20 x 0.6 = 12 years

39 Oh but it doesn’t end there… – “Disability Adjusted Life Expectancy” – Measure life expectancy in a population, shortened to account for quality years lost due to disability – Eg: Japan has one of the world’s highest life expectancies = 81.3 years, computed at birth – But DALE in Japan is 74.5 years! DALE

40 DALEs Like QALYs, requires agreement on how much a disability “shortens” the quality of one’s life DALE of an individual = total number of years lived without disability +number of years with disability x (index) Index = 0 -> 1 (just like in QALYs) DALE of a population = sum of DALES of each member

41 Life Expectancy – The expected time remaining to live – Usually given relative to birth – E.g., Presently, life expectancy at birth is 32.6 years in Swaziland and 81 years in Japan – Life expectancy is computed using “life tables”, which means that it will vary depending on what age it is calculated for….

42 Life Expectancy Life expectancy in the USA, stolen from www.imminst.org

43 Life Expectancy – More ill-health and disabilities, and greater suffering? – Longer period of life in good health? – Does long life = productive life?  economics – Some have proposed using “healthy life expectancy” or HLE (meanwhile, TLE=“total life expectancy”) The expected number of years to be spent in good health Need to weight different disabilities based on severity What’s the problem with using life expectancy as a gauge of population health?

44 And The Grand Daddy of them all… – “Disability Adjusted Life Year” invented in 1996 – Measure of overall disease burden in a population – www.who.int/healthinfo/boddaly – A DALY is considered a bad thing : – The number of years of productive life lost in a population due to both death and disability DALYs

45 – DALY = YLL + YLD YLL = years of life lost in the population due to death from a specific health YLD = years of productive life lost due to disability, rather than death

46 Why is the DALY so important? Now we have a measure for the population burden of a disease that accounts for the impact, not only of death, but of morbidity

47 Current Global Burden of Disease (DALYs, 1999) 1.Acute lower respiratory infections 2.HIV/AIDS 3.Perinatal conditions 4.Diarrhea 5.Unipolar major depression 6.Ischemic heart disease 7.Cerebrovascular disease 8.Malaria 9.Traffic injuries 10.COPD 11.Congenital abnormalities 12.TB 13.Falls 14.Measles 15.Anemia Source: WHO, Evidence, Information and Policy, 2000

48 Projected Global Burden of Disease (DALYs, 2020) 1.Ischemic heart disease 2.Unipolar major depression 3.Traffic injuries 4.Cerebrovascular disease 5.COPD 6.Lower respiratory infections 7.TB 8.War 9.Diarrhea 10.HIV 11.Perinatal conditions 12.Violence 13.Congenital abnormalities 14.Self-inflicted injuries 15.Trachea, bronchus and lung cancers Source: WHO, Evidence, Information and Policy, 2000

49 Survival

50 Survival rates _____________ is the probability of remaining alive for a specific length of time 1 year and 5 year survival are often used as indicators of the severity of disease and the prognosis 5 year survival rates for myelocytic leukemia is about 0.14, indicating that about 14% of the patients with acute myelocytic leukemia survive for at least 5 years after diagnosis. Survival (S) = (A – D) / A where – A is the number of newly diagnosed patients under observation and D is the number of deaths observed in a specified period of time

51

52 Observation of each patient begins at diagnosis (time = 0), and continues until one of the following outcomes occurs: death, survival for 5 years, or follow-up ceases (the subject is "censored"). A patient is censored when follow-up ends prior to death or completion of a full period of observation. Follow-up could end for one of several reasons: (1) the patient decides to discontinue participation, (2) the patient is "lost" to follow-up, or (3) the study ends. Five of the six people under observation (N = 6) survive at least 2 years. Thus, the 2-year survival is 5/6=0.83=83%

53 Specifying Length of Survival 1, 2, 5 years are standard, but it can be anything For example, prostate cancer has a much higher one year overall survival rate than pancreatic cancer, and thus has a better prognosis.

54 Relative Survival Rate RSR Ratio of survival rate of disease in question, divided by the survival rate of the general population Eg RSR of cancer at 2 years = (% of cancer patients who are alive @ 2 years) / (% of general population who are alive @ 2 yrs) Why is this important? Eg, The overall 5-year relative survival rate for 1999-2005 from 17 SEER geographic areas was 89.1%. Five-year relative survival rates by race were: 90.3% for white women; 77.9% for black women.

55 Cause-Specific Survival Rate Cause-specific survival (CSS) is a term that denotes the chances of death due to a particular condition (or cause) at a particular point of time. It takes care to exclude death due to unrelated causes in patients suffering from the cancer in question. The 5-year cause-specific survival for stage IIA Hodgkin lymphoma is 85% when treated with ABVD followed by involved field radiation. This means that 15% of these patients are estimated to die directly due to the Hodgkin disease by 5 years. The remaining 85% are either alive or have died due to other unrelated causes.

56 Problems with mortality data Information on mortality is obtained from death certificates Deaths are coded according to the underlying cause – Which is defined as the disease or injury which initiated the train of morbid events leading directly or directly to death or circumstances of accident or violence which produced the fatal injury – The underlying cause therefore excludes information pertaining to the immediate cause of death, contributory causes and those that intervene between the underlying and immediate causes of death Some causes of death have better validity than others

57

58 Cause of death from a death certificate

59 ICD classification on death certificates Deaths are coded by ICD classification Drop in diabetes related deaths in 1949 were caused by changes in classification codes Prior to 1949 the policy was to include diabetes as cause of death anywhere on the certificate lead to diabetes being mentioned on the death certificate After 1949 only death certificates on which the underlying cause of death was listed as diabetes were coded as a death from diabetes

60 Changes in death rates from diabetes caused by changes in classification

61 Changes in the definition of disease In 1993, a new definition of AIDS was introduced These changes resulted in a rapid rise in the number of reported cases

62 AIDS cases in the US from 1984-2000

63 Causes of death in the early 20th century Table 4-6. Some Causes of Death That Were Reported on Death Certificates in the Early 1900s "Died suddenly without the aid of a physician" "A mother died in infancy" "Deceased had never been fatally sick" "Died suddenly, nothing serious" "Went to bed feeling well, but woke up dead"


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