The Epidemiology of Diseases in Emerging Markets &

Challenges to Estimating Patient Populations:

Focus on China

Michael McGuill & Nikhil MehtaMichael McGuill & Nikhil Mehta

Challenges to Estimating Patient Populations: Focus on China

January 31, 2007

Dr. Michael McGuill, Principal Director, EpidemiologyNikhil Mehta, Cardiovascular Therapeutic Analyst

Decision Resources, Inc.

Discussion Topics1. The Effects of Population Trends on Risk Factors and

Disease

2. Forecasting Patient Populations at the National and Regional Level

3. Estimating Diagnosed and Drug-Treated Patient Populations

Total Population

China

Total Population

Beijing

Total Population

Guangdong

Total Population

Shanghai

Total Population

Yunnan

Prevalent Population

(Shanghai)

Rural prevalent

Population

Urban prevalent

Population

Forecast: Population-Based vs. “Top-Down”

Model subpopulations

● Age, gender, disease severity

Triangulate with known drug sales to identify areas of remaining opportunity

● Potential market size

● Growth in diagnosis or treatment rate?

● Improvements in compliance rate?

Forecast: Population-Based vs. “Top-Down”Forecast following market disruptions

● Changes in health care system e.g. growth in community physician care, retail pharmacies

Create transparent and rigorous long-term forecasts

Incomplete sales history and lack of comparable analogues in China makes extrapolation and trending difficult

Chinese Urban Population ProjectionUrbanization increases the risk of chronic diseases tied to an urban lifestyle.

0

10

20

30

40

50

60

1970 1975 1980 1985 1990 1995 2000 2005 2010 2015

Perc

enta

ge U

rban

United Nations Projection

“Epidemiological Transition”: 4 Phases

Pestilence and famine: malnutrition, infectious diseases

Receding pandemics: more chronic disease, hypertension

Degenerative and man-made diseases: deaths from chronic diseases exceed those from infectious disease

Delayed degenerative diseases: CVD and cancer are leading causes of morbidity and mortality

Trends in Cause of Death, U.K.

Forecasting Patient Populations

Estimating Cases in China: the Urban/Rural Challenge

Prevalent Cases of Disease X, 1000s2006 2016

China 35,990 51,100

Urban 27,340 76% 43,720 86%

Rural 8,650 24% 7,380 14%

Beijing 2,320 3,240

Urban 2,000 86% 2,900 90%

Rural 320 14% 340 10%

Finding Estimates of Disease in China

To estimate the current and forecasted size of disease populations:

● Review secondary literature: don’t forget studies in Chinese.

● Analyze large Chinese population-based databases

● Conduct primary research with epidemiology experts.

● Examine studies of other Asian and/or developing nations.

Transparent methods

Urban-rural ratesRegion-specific data

Criteria for Judging Data

Recent

Definitions comply with international standards

Representative

Population Forecasts: National LevelUse UN urban/rural data (available in 5 year increments – fit curve for intervening years)

Model historical population based on data published by Chinese government agencies, but this has limits

Rough estimate for shorter (5 to10-year) forecast: assume 1% growth in urban population

Apply national prevalence rates

Population Forecasts: Regional Level

Need region-specific population data and urban/rural proportions

● If lacking historical urbanization trends, determine where a region fits on the national curve and apply the curve after that point

● Alternatively, you may find historical urbanization trends for a region that allow you to model future region-specific urbanization trends

Apply incidence/prevalence to rural populations

Estimating Urban/Rural Population, ShanghaiModeled China Urbanization Curve

0

20

40

60

80

100

120

1980 2000 2020 2040 2060 2080 2100

Time, years

Urb

aniz

atio

n, %

83.3 %, 2004

87.2%, 2016

85.3%, 2006

Estimating Urban/Rural Population, Shanghai

Total (1000s) Urban Ruralage 2004 200450- 606 505 101

55- 395 329 66

60- 268 223 45

65- 230 192 38

70- 201 167 34

75- 119 99 20

80- 53 44 9

85+ 19 16 3

Total 1,891 1,575 316

100.0% 83.3% 16.7%

Estimating Urban/Rural Population, Shanghai

Total (1000s) Urban Ruralage 2004 2004

50- 606 505 101

55- 395 329 66

60- 268 223 45

65- 230 192 38

70- 201 167 34

75- 119 99 20

80- 53 44 9

85+ 19 16 3

Total 1,891 1,575 316

100.0% 83.3% 16.7%

Estimating Rural/Urban Cases, Shanghai

Urban Shanghaiage pop 1000s rate/ 100,000 cases

50- 517 13.668 7,066

55- 337 27.081 9,120

60- 228 48.272 11,027

65- 196 62.892 12,348

70- 171 76.925 13,188

75- 101 86.173 8,738

80- 45 86.751 3,903

85+ 17 61.829 1,025

Total 1,613 66,416

50% 40% 30% 20% 10% % 10% 20% 30% 40% 50%

0-9

10-19

20-29

30-39

40-49

50-59

60-69

70-79

80+

Population Percentage

Urban Rural

Population Pyramid, China, 2000

Data SourcesSource Description

United Nations Population Division

National age- and gender-specific population estimates and forecasts (to 2050) and rural and urban population estimates

China National Bureau of Statistics

Population projections, economic information, regional rural and urban population splits

Chinese Population, Economic, Health and Nutrition Survey

Incidence/prevalence/diagnosed/ treated data from sample of 9 provinces and 13,000 adults; six surveys taken between 1989-2004; includes self-report and lab measures

Data SourcesSource Description How to Access

InterAsia Study Nationally representative sample, 35-74, 2000-2001, described markers of lipid levels, overweight and obese, hypertension, diabetes, etc.

Research articles

National Nutrition and Health Survey (NNHS)

Sample of 31 provinces by Chinese Ministry of Public Health; conducted in 2002

Research articles

Cancer Data SourcesSource Description How to Access

Incidence data collected by cancer registries worldwide; six Chinese registries are represented

http://www.iarc.fr/index.html

Incidence data and mortality collected by twelve Chinese registries

http://cancernet.cicams.ac.cn/

China Search EngineSource Description How to Access

EastView Medical Database

Chinese language equivalent of MedLine, database of Chinese papers, translation required

http://www.cnki.net/index.htm

Available through subscription

Estimating Diagnosis and Treatment Rates

Population with Disease X

% Diagnosed

% Drug-treated

% Western Drugs

Systematic literature review

Population-based databases

Surveys with high-prescribing physicians

% Branded Western Drugs

Secondary Literature: Deriving Top-line Estimates

Apply quality criteria to survey data available in literature“Ballpark” estimates for diagnosis/treatment

0%

50%

100%

#1 #2 #3 #4Population surveys (n >10,000)

Hypertension % diagnosed % treated of diagnosed

Variations in Wealth and Reimbursement Status

Uneven distribution of wealth and insurance coverage creates regional disparities that influence likelihood of diagnosis and ability to pay for therapyVariations in drug reimbursement status complicate assumption-making process

Urban Rural% with no insurance coverage

45% 30%

Median Per Capita Income $1,266 $330

Reimbursement in Beijing

Reimbursement in Shanghai

PPAR-γ agonists 50% 90%

Regional Data from Population Databases

● CHNS database contains diagnosis and partial drug-treatment status for representative sample in 9 provinces

• Diabetes, Hypertension, Myocardial Infarction, Obesity.

● Chronic cardio-metabolic diseases: income is a greater determinant of diagnosis than of treatment

● Upper 20% of earners with diabetes are 3 times more likely to be diagnosed than lowest 20%.

● Urban patients nearly 2.5 times more likely to be diagnosed with diabetes than rural patients.

● Diabetes diagnosis rate in Shanghai 25% higher than in Beijing and 100% higher than in Gansu province

Primary Research Physician surveys fill research gaps and add granularity to market forecasts:

● Provincial- or city-level diagnosis and treatment rate estimates

● Attitudes of patients and prescribers to disease management

● Determinants of disease awareness and prescribing behavior

● Use of TCM vs. Western medicine

● Use of MNC branded Western medicine vs. unbranded Chinese-made generics

● Provincial- or city-level prescription or patient share estimates

Primary ResearchBe aware of:

● Regional differences in language

● Need for face-to-face interviews

● Cultural differences in tone and language used to pose questions

Conclusions

Estimating and forecasting patient populations in China present unique challenges given the size and complexities of the demographics and distributions of risk factors and disease.

Regional estimates of patient populations, segmented into urban and rural proportions, provide a more accurate understanding of the burden of disease and treatment opportunities.

ConclusionsPopulation datasets, supplemented by medical literature and sociodemographic data, allow accurate estimation of diagnosis/treatment rates.

Physician interviews are source of important quantitative and qualitative data, especially in absence of patient-level data.