 The 2004 Healthcare Conference April 2004 Scarman House, The University of Warwick Session B1 / D3 Richard Morris, Hamish Galloway, Sue Elliott Critical Illness Trends Research Group

Trends in Critical Illness Risk Costs Further Lessons from Population Data An update from the Critical Illness Trends Research Group n What impact might screening for bowel cancer have ? Richard Morris n The interaction between trends in CABG, angioplasty, angina and heart attacks n The importance of trends in non-CI deaths Hamish Galloway n Pulling it all together - a framework for assessing the outlook on CI risk costs Sue Elliott

Critical Illness Trends Research Group n Our Aims : n To examine underlying trends in the factors influencing UK Insured Critical Illness claim rates, and from these, to assess : nThe historic trend in incidence and death rates for the major CI’s nAny pointers for future trends in Standalone CI, Mortality and hence Accelerated CI. n Formed in March 2001

Group Members and our Current Focus Heart AttackMS, TPD, Cancer & Strokenon-CI mort y & overall proj’n n Actuaries Azim Dinani Scott ReidSue Elliott Richard Morris Joanne WellsHamish Galloway Neil Robjohns (Chair)Scott Reid n Medical Experts Professor Rubens Richard Croxson Consultant Oncologist Consultant Cardiologist n Links : nActuaries Panel on Medical Advances nCMIB CI experience investigation nABI CI definitions group

The Impact of Screen for Bowel Cancer - Richard Morris The Actuarial Profession making financial sense of the future

Screening for Colo-rectal Cancer (Prostate - quick update) Background on the disease Plans for screening Trends to date Modelling screening

Prostate Cancer Screening Update PSA Test: –Not specific enough - false positives –Not sensitive enough - false negatives –Not standardised No evidence that screening reduces mortality Cancer Research UK briefing to MPs (Sep 03): “Population screening of men displaying no symptoms is not recommended.”

Colorectal cancer

Statistics 3 rd most common cancer in men 2 nd most common cancer in women Over 35,500 new cases per annum Male incidence (ages 40-59) increasing at 1% p.a. Female incidence trend is level 90% of cases occur over age 50

Risk Factors Unclear but could include: High-fat diet Lack of dietary fibre Sedentary lifestyle Obesity Alcohol Family history Age History of bowel disease (inflammation, Crohn’s disease, …) Lack of melatonin (night-shift workers)

Histology Normal cells Abnormal gland cells in the lining of the bowel wall Adenomatous Polyp –(20-25% prevalence at age 50) Cancer localised within the bowel wall (Duke’s Stage A) Cancer which penetrates the bowel (Duke’s Stage B) Cancer spread to lymph nodes (Duke’s Stage C) Cancer with distant metastases (Duke’s Stage D / Stage 4)

Histology Normal cells Abnormal cells Adenomatous Polyp –(20-25% prevalence at age 50) Cancer localised within the bowel wall (Duke’s Stage A) Cancer which penetrates the bowel (Duke’s Stage B) Cancer spread to lymph nodes (Duke’s Stage C) Cancer with distant metastases (Duke’s Stage D / Stage 4) DETECTION?

Screening Methods Faecal Occult Blood Test (FOBT) Double Contrast Barium Enema Flexible sigmoidoscopy Colonoscopy CT Colonography DNA in stools

Plans for screening UK clinical trials: population screening over age 50 using FOBT: –15% reduction in mortality. Two pilots (Coventry and Fife) set up in spring 2000 for a 2-year period. –50-69 year olds invited for FOBT screen. Evaluated by National Screening Committee and DofH Second round of screening in pilot sites. Separate UK trial of flexible sigmoidoscopy screening.

Screening Pilot Conclusions “Our recommendation to the Department of Health is that FOBT screening should be part of new national strategies targeting colorectal cancer.” “Findings … suggest that population-based FOBT screening is feasible.” “adverse effects of screening … were low” “The UK Pilot has demonstrated that mortality reductions demonstrated in randomised studies of FOBT screening can be repeated in the models of screening used in the UK pilot.”

Past Trends

Past Trends: Breast Cancer

Past Trends: Prostate Cancer

H ULRP UHRP LC A DHRP DC A DC B DC C DC D Cured From Cancer Dead From Cancer LC B LC C LC D DLRP Cancer Screening Model

Screening Studies National Screening Committee UK –Pilot study data “Cost-effectiveness of screening for colorectal cancer in the general population” - Frazier et al (Journal of the American Medical Association – October 2000) –: “One of the most robust modelling studies reported to date.” National Screening Committee report Both focus on mortality reduction.

Model Assumptions Medical data Transition rates: Low-risk polyp to high-risk polyp High-risk polyp to cancer (stage A) Transition between cancer stages Population data Cancer incidence rate Incidence rate by Duke’s stage Unknown Risk of developing low-risk polyp

Cancer Incidence: Modelled Incidence

Cancer Incidence: No polyp detection

Cancer Incidence: Duke’s Stage

Cancer Incidence: Up to 10% Polyp detection

Cancer Incidence: Indexed

Screening: Conclusions for Insurers We’re all doomed! Don’t panic!

Interaction in Trends between Heart Attack, CABG and Angioplasty - Hamish Galloway The Actuarial Profession making financial sense of the future

Should Trends in Heart Conditions be Modelled Together? nDrivers of trends nRisk factors nMedical intervention nReview of trends in incidence nheart attack, coronary artery bypass, angioplasty 2+ nCorrelation nby age nby calendar year

Risk Factors for Coronary Heart Disease Source: Britton and McPherson (2000). National Heart Forum

Medical Intervention nDrug treatments nSurgical intervention (e.g. CABS and Angioplasty) nLimited by resource ncould also be driven by resource

Trends in Population Incidence Rates Heart Attack (First and Subsequent) Age 35-64

Trends in Population Incidence Rates Coronary Artery Bypass Graft Age 35-64

Trends in Population Incidence Rates Angioplasty 2+Vessels Age 35-64

Percentage Change p.a. in Incidence Rates Non-smoker model HA, CABG and Angioplasty 2+ Males

Percentage Change p.a. in Incidence Rates Non-smoker model HA, CABG and Angioplasty 2+ Females

Summary Trends Heart Related Conditions nHeart attack incidence is no longer reducing at historical rates nPotentially explained by the use of troponin to assist in the diagnosis of heart attacks nFull impact of troponin not yet in data nOperations nCABG nstabilising/reducing less 60 nincreasing over 60 nAngioplasty operations increasing at all ages nCombined effect nFlat incidence at younger ages nIncreases in incidence at older ages nBefore troponin and other medical advances

Heart procedure rates versus 1 st ever heart attack rates 35 up to age data combined. Age

Heart procedure rates versus 1 st ever heart attack rates. From age data combined. Age

Years Heart procedure rates versus all heart attacks rates By HES year 1989 to Ages combined Years

Effectiveness of CABS and Angioplasty nRandomised controlled trials of revascularisation against medical treatment show: nfor CABS na reduction in mortality nno reduction in the subsequent risk of non fatal vascular events nFor angioplasty nimproved symptoms in patients with angina nno improvements in survival nno prevention of subsequent myocardial infarction

Heart procedure rates versus angina rates by HES year 1989 to Ages combined Years

Ratio of heart procedures to first ever heart attack by calendar year for England and Wales, Ages combined

Ratio of heart procedures to angina rates by calendar year for England and Wales, Ages combined

International data on the ratio of heart procedures to all heart attacks

Summary on Correlation nTrends in diet and smoking will impact all of HA, CABS, and angioplasty as well as angina but… nthe impact does not appear to be the same due to medical intervention nCorrelation by calendar year of CABS and angioplasty is stronger with angina than heart attack nIncreases in the number of CABS and angioplasty are not acting to reduce the rate of heart attack nGreatest potential for increase in operations is at ages over 65 nInternational comparisons show considerable scope for the rate of angioplasty operations to increase. nHeart attack, needs to be modelled separately from CABS and angioplasty.

Trends in non-CI Mortality - Hamish Galloway The Actuarial Profession making financial sense of the future

Importance of Non CI Mortality nAccelerated CI Incidence Rate Formula ni x + (1-k x )q x or i x + q’ x where q’ x represents non-CI related mortality nNon CI Mortality as a %age of CIBT93 nBiggest Single Component of Male ACI to Age 50 n2 nd Biggest Single Component of Female ACI throughout

Comparison of Trends in All and in Non CI Deaths

Interim Conclusions nNon CI Mortality improvement is worse than all cause improvement almost everywhere nFor key insurance ages Non CI Mortality is deteriorating nTrend in the 90’s worse than the 80’s nParticularly for females nEvidence of Ageing of Mortality Improvement

Cause of Death by Gender and Age Group

Further Conclusions - deterioration in non CI deaths at young ages due to nAccident nDrug/Alcohol nChronic Liver nInfection n“Everything Else” Offset at young ages by improvements in nVehicular Accidents

Cause of Death by Gender and Age Group

Further Conclusions - deterioration in non CI deaths at middle ages due to nRespiratory nChronic Liver nAccident (F) nCardio non CI (F < 54) Offset at middle ages by improvements in nCardio non CI (ages 55+)

Cause of Death by Gender and Age Group

Further Conclusions - deterioration in non CI deaths at old ages due to nRespiratory (F) Offset at old ages by improvements in nCardio non CI (M, F<75)

Further Work and Application to Insured Lives nNeed to understand cardio non-CI nCMI cause of Death survey discontinued 1994 nLink to deprivation codes nDistortion due to ICD coding

Pulling it all together – a framework for assessing the outlook on CI risk costs - Sue Elliott The Actuarial Profession making financial sense of the future

Pulling it all together – a framework for assessing the outlook on CI risk costs nPopulations trends nSimplistic extrapolations (based on population data) nPotential scenarios for future

Conditions considered nCardiovascular nSplit by heart attack, angioplasty, CABG, stroke, etc nData available (HES) nCancer nModelled as one condition nData available (Cancer registration statistics) nNon CI deaths nModelled as one condition nData available (OPCS cause of death statistics) nThe rest nNo change projected at this time

Health warnings nSmoker/non-smoker nObesity nHealth/wealth nBase data at 1993 may be incorrect ne.g. “fudge” for angioplasty nLarge trends in small conditions can distort big picture nAngioplasty again

Cardiovascular trends - males

Cardiovascular trends - females

Cancer trends

Non CI death trends

Simplistic extrapolations – issues to consider nWhat period of past data to use as a base trend? nProject 5 year age bands or impose an age-related pattern? nWhat level of subdivision of CI’s (eg all cancer or by key cancer site?)

Simplistic extrapolation 1 (for illustration only) nTrends from only nSome smoothing applied nTrends run to zero with half life 10 years nHeart attack, CABG, angioplasty 2+ modelled together nCIBT 93 (with angioplasty 2+) applies at 1993 nTrends in are actual population trends n2001 et al projected off trended average of

Simplistic extrapolation 1 (for illustration only)

Simplistic extrapolation 2 (for illustration only) nTrends from only nSome smoothing applied nTrends run to zero with half life 10 years nAll cardio vascular modelled separately nCIBT 93 (with angioplasty 2+) applies at 1993 nTrends in are actual population trends n2001 et al projected off trended average of

Simplistic extrapolation 2 (for illustration only)

Potential scenarios for the future nA range of outcomes are possible nNeed to consider: nMedical advances nPrevention nDiagnosis nTreatment nHealth awareness nSocial change nEconomic change

Potential scenarios for the future nNo change – current and “known” future trends run their course and are not replaced nAdverse lifestyles continue – obesity, smoking, drug/alcohol abuse, etc n“Prevention” campaigns – have best effect that can be reasonably considered nImproved detection: ncancer screening (eg breast, prostate, bowel) – create a spike? nimpact of troponins? noverall – improved detection could increase or decrease CI claim incidence nImproved treatment – prevent a CI condition from becoming a CI claim