Which HIV+ individuals should be screened for colorectal cancer?

Which HIV+ individuals should be screened for colorectal cancer?
R. Scott Braithwaite, MD, MSc, FACP

Introduction Individuals with HIV living longer
Increasingly likely to die of non-HIV illnesses However, life expectancies still shorter than for general population Especially for low CD4 and/or salvage regimens No systematic method to predict whether guidelines developed on general population should apply to individuals with HIV New mechanisms such as “pay for performance” and physician “report cards” are providing powerful incentives for caregivers to comply with clinical guidelines regardless of their context. Paradoxically, there is now increasing awareness that guidelines should be tailored to a patient’s particular clinical setting, such as their comorbidity burden and age, in order to maximize their benefit. If a patient’s comorbidity burden is higher, that patient will have a greater competing risk of death from sources unrelated to the guideline and therefore is LESS likely to sustain BENEFIT, while simultaneously MORE likely to sustain HARM from a side effect or procedural complication. However, no systematic method exists to tailor guidelines to comorbidity burdens, making it increasingly likely that they will be applied in an indiscriminate manner.

Introduction Payoff Time = Minimum time until incremental benefits > incremental harms Applies to any guideline where harms are short-term and benefits are long-term Colorectal cancer screening (CRC) Will vary by guideline and by patient population Payoff time can be compared to life expectancy If death likely before payoff time, guideline not advised If death unlikely before payoff time, guideline advised Our approach involves the concept of a “payoff time”, which we define as the minimum time until the benefits from a guideline exceed its harms. This concept would apply to any guideline where harms occur in the short-term and benefits occur in the long-term, and will vary by guideline and patient population. Guidelines involving procedures with substantial complication risks are likely to have long payoff times. We used this concept of a payoff time to develop a systematic method for evaluating guidelines, based on the heuristic that if an individual’s death is likely to occur before the payoff time, the guideline is likely not advised for that individual, whereas if death is unlikely to occur before the payoff time, then the guideline may be advised for that individual.

Objective To predict which HIV patients would benefit from colorectal cancer screening. Our objective was to explore the feasibility of tailoring guidelines to comorbidity burdens. As a test case, we decided to examine the case of cancer screening for 50 year-old HIV+ men. Because of the success of current antiretroviral therapies, HIV is now a chronic disease rather than an acute illness if individuals take their antiretroviral therapy regularly, and its prevalence as a comorbidity is likely to increase steadily in the future.

Illustrative Cases 1. 60 year-old HIV+ male on salvage ARV, CD4 count 46 Comorbidities: COPD (severe), hepatitis C, heavy alcohol 2. 60 year-old HIV+ female on 1st line ARV, CD4 count 392 Comorbidities: diabetes

Payoff time applicable? No Stop
Yes Estimate payoff time Payoff time needs adjustment? No Yes Adjust payoff time Use HIV simulation to estimate life expectancy Estimate life expectancy Payoff time > LE? Yes No Compare payoff time to life expectancy Screening likely harmful Screening may be beneficial

Is payoff time applicable?
Payoff time inapplicable if all are true: Impact of pt characteristic on guideline’s harms and/or benefits is substantial Impact of pt characteristic on guideline’s harms and/or benefits is unknown Impact on harms likely overestimated and/or impact on benefits likely underestimated Otherwise, payoff time applicable

Characteristics that make CRC payoff time inapplicable Inflammatory bowel disease Personal history of colon cancer or adenomatous polyps History of pelvic radiation Hodgkins Lymphoma Acromegaly Impact on benefits is unknown, substantial, and likely to result in underestimation

Case 1: 60 year-old HIV+ male on salvage ARV, CD4 count 46 Comorbidities of Case 1: COPD (severe), hepatitis C, heavy alcohol Is payoff time applicable for CRC screening for case 1? YES

Payoff time needs adjustment?
Payoff time applicable? No Stop Yes Estimate payoff time Payoff time needs adjustment? No Yes Adjust payoff time Use HIV simulation to estimate life expectancy Estimate life expectancy Payoff time > LE? Yes No Compare payoff time to life expectancy Screening likely harmful Screening may be beneficial

Does payoff time need adjustment?
Characteristic Impact on benefits (RR) Impact on harms (RR) Smoking17*† 1.8 Unknown‡ Obesity 18,19* 1.5 Heavy alcohol 20§ 1.3 Diabetes 21*§ Aspirin (regular use) 22 § 0.8 NSAID (regular use) 22 § 0.7 Hormone replacement therapy23§ 0.6 Unknown‡║ Coumadin 14§ Unknown¶ 4.0 American Anesthesiology Society Class 1 (“normal healthy patient”) 14§ American Anesthesiology Society Class 3 (“severe systemic disease”) 14§ 4.3 1st degree relative with CRC, age unknown24† 2.3 1st degree relative with CRC, age<4524† 3.9 >1 1st degree relative with CRC24†

Case 1: 60 year-old HIV+ male on salvage ARV, CD4 count 46 Does CRC screening payoff time need adjustment for Case 1? YES Relative risk for harms multiplied by 4.3 because Case 1 is ASA Class 1 Relative risk for benefits multiplied by 1.3 Personalized benefit to harm ratio = relative risk for benefit/relative risk for harm = 1.3 / = 0.3

Adjust payoff time Benefit-to-harm ratio Age 40 Age 50 Age 60 Age 70 M
0.1 >10 9.7 7.5 8.6 0.2 7.3 8.7 6.2 6.7 0.5 7.4 6.0 6.5 5.5 5.8 1 9.0 10.0 6.8 5.4 5.7 5.2 5.3 2 7.0 7.6 5.6 5.9 5.1 4 6.3 5.0 10

Adjust payoff time Case 1: 60 year-old HIV+ male on salvage ARV, CD4 count 46 For Case #1, adjusted payoff time is approx 7.3 years This is the minimum time until the benefits from CRC screening exceed the harms Should not advise screening if Case #1’s life expectancy is < 7.3 years Advise screening if Case #1’s life expectancy is ≥ 7.3 years

Use HIV simulation to estimate life expectancy

Estimate life expectancy
CD4 Age Round 1 Round 2 Round 3 <50 all 5.25 5.38 5.12 50-200 7.5 7.04 6.96 41-50 12.17 11.79 11.46 51-60 11.5 10.79 10.08 61-70 insuff data 8.75 8.62 >=70 7.08 7.25 15.79 15.5 15.42 15.12 13.75 12.67 11.54 10.96 8.58 8.54 >=500 18.17 17.96 17.75 17.67 16.29 14.96 14.04 12.87 9.54 9.29

Estimate Life Expectancy
Case 1: 60 year-old HIV+ male on salvage ARV, CD4 count 46 For Case #1, life expectancy is 5.1 years

Compare payoff time to life expectancy
Case 1: 60 year-old HIV+ male on salvage ARV, CD4 count 46 Payoff time for Case 1 is 7.3 years Life Expectancy for Case 1 is 5.1 years Because life expectancy is less than payoff time (minimum time until benefits exceed harms), Case 1 is unlikely to benefit from colorectal cancer screening

Screening likely harmful

Illustrative Cases 1. 60 year-old HIV+ male on salvage ARV, CD4 count 46 Comorbidities: COPD (severe), hepatitis C 2. 60 year-old HIV+ female on 1st line ARV, CD4 count 392 Comorbidities: diabetes

Payoff time inapplicable if all are true: Impact of pt characteristic on guideline’s harms and/or benefits is substantial Impact of pt characteristic on guideline’s harms and/or benefits is unknown Impact on harms likely overestimated and/or impact on benefits likely underestimated Otherwise, payoff time applicable

Characteristics that make CRC payoff time inapplicable Inflammatory bowel disease Personal history of colon cancer or adenomatous polyps History of pelvic radiation Hodgkins Lymphoma Acromegaly Impact on benefits is unknown, substantial, and likely to result in underestimation

Case 2: 60 year-old HIV+ female on 1st line ARV, CD4 count 392 Comorbidities of Case 2: Diabetes Is payoff time applicable for CRC screening for Case 2? YES

Payoff time needs adjustment?

Characteristic Impact on benefits (RR) Impact on harms (RR) Smoking17*† 1.8 Unknown‡ Obesity 18,19* 1.5 Heavy alcohol 20§ 1.3 Diabetes 21*§ Aspirin (regular use) 22 § 0.8 NSAID (regular use) 22 § 0.7 Hormone replacement therapy23§ 0.6 Unknown‡║ Coumadin 14§ Unknown¶ 4.0 American Anesthesiology Society Class 1 (“normal healthy patient”) 14§ American Anesthesiology Society Class 3 (“severe systemic disease”) 14§ 4.3 1st degree relative with CRC, age unknown24† 2.3 1st degree relative with CRC, age<4524† 3.9 >1 1st degree relative with CRC24†

Case 2: 60 year-old HIV+ female on 1st line ARV, CD4 count 392 Does CRC screening payoff time need adjustment for Case 2? YES Relative risk for harms not impacted Relative risk for benefits multiplied by 1.3 because of diabetes Personalized benefit to harm ratio = relative risk for benefit/relative risk for harm = 1.3 / = 1.3

Adjust payoff time Benefit-to-harm ratio Age 40 Age 50 Age 60 Age 70 M
0.1 >10 9.7 7.5 8.6 0.2 7.3 8.7 6.2 6.7 0.5 7.4 6.0 6.5 5.5 5.8 1 9.0 10.0 6.8 5.4 5.7 5.2 5.3 2 7.0 7.6 5.6 5.9 5.1 4 6.3 5.0 10

Adjust payoff time For Case #2, adjusted payoff time is 5.7 years
Case 2: 60 year-old HIV+ female on 1st line ARV, CD4 count 392 For Case #2, adjusted payoff time is 5.7 years This is the minimum time until the benefits from CRC screening exceed the harms Should not advise screening if Case #1’s life expectancy is < 5.7 years Advise screening if Case #1’s life expectancy is ≥ 5.7 years

Use HIV simulation to estimate life expectancy

Estimate life expectancy
CD4 Age Round 1 Round 2 Round 3 <50 all 5.25 5.38 5.12 50-200 7.5 7.04 6.96 41-50 12.17 11.79 11.46 51-60 11.5 10.79 10.08 61-70 insuff data 8.75 8.62 >=70 7.08 7.25 15.79 15.5 15.42 15.12 13.75 12.67 11.54 10.96 8.58 8.54 >=500 18.17 17.96 17.75 17.67 16.29 14.96 14.04 12.87 9.54 9.29

Estimate Life Expectancy
Case 2: 60 year-old HIV+ female on 1st line ARV, CD4 count 392 For Case #2, life expectancy is 15.1 years

Compare payoff time to life expectancy
Case 2: 60 year-old HIV+ female on 1st line ARV, CD4 count 392 Payoff time for Case 2 is 5.7 years Life Expectancy for Case 2 is 15.1 years Because life expectancy is less than payoff time (minimum time until benefits exceed harms), Case 2 is likely to benefit from colorectal cancer screening

Screening may be beneficial

Limitations Analyses do not consider rate of developing new ARVs
Simulation can be modified to address this Framework will not be applicable to every HIV+ patient Requires EMR/informatics capability to integrate easily into care

Conclusion Payoff time is quantitative objective framework for predicting who will benefit Applicable to HIV+ Applicable to patients with other comorbidities CRC screening may not always be appropriate for HIV+ individuals Low CD4 Salvage ARV May simultaneously improve quality of care and reduce resource expenditures May impact quality measures and P4P rules In conclusion, tailoring guidelines to comorbidities is feasible. This goal is likely to be on the short list of innovations that simultaneously saves money and improves health. Cancer screening guidelines may not be appropriate for HIV+ men if adherence is very poor, or if prognostic indices are poor. Finally, our results suggest that task forces and expert panels should avoid “one size fits all” prescriptions whenever possible in this era of increasing comorbidity prevalence.

VA Benchmarks: “payoff time” applies?
Cancer screening Colorectal Prostate Breast Diabetes Tight glucose control Tight BP control

Which HIV+ individuals should be screened for colorectal cancer?

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