Important note: Information in this article was accurate in January 2009. The state of the art may have changed since the publication date.
Number needed to treat to harm (NNTH) analysis of impact of underlying cardiovascular factors on risk of abacavir-related heart attack
HIV Treat Bull - 2009 Jan-Feb;10(1/2): 10
Simon Collins, HIV i-Base
JD Kowalska from the D:A:D study presented a model looking at the ‘number needed to treat to harm’ (NNTH) in order to help interpret the clinical importance of the 90% increased relative risk (RR=1.90), previously reported between abacavir use and the risk of heart attack.[1, 2]
This estimate changed depending on an individuals underling cardiovascular risk. The underlying risk was calculated based on 5-year Framingham score[3] and the relative rate was assumed to remain constant across the range of underlying risk of MI.
NNTH was calculated as:
_____________________1___________________
(underlying risk of MI × 1.90) – underlying risk of MI
The lowest NNTH values were observed in the high risk group, while the most dynamic changes in NNTH is in the low risk group, showing an exponential relationship between NNTH and underlying risk of MI. The NNTH dropped steeply from 185 with an underlying risk of MI of 0.6% to only 5 when underlying MI risk is 20%.
The importance of additional risk factors was illustrated by starting with a low risk patient (0.1% risk of MI); in this case, 1111 patients would need to be treated before seeing an abacavir-related MI. When two unfavourable risk components are present the NNTH drops to around 100 for most pairs, except smoking and low HDL, for which NNTH drops to 69. When all risk factors are unfavourable, in patients with 15% underlying CVD risk, only 7 people would need to be treated with abacavir to see a treatment associated MI. (See Table 1).
| Table 1: Change in factors contributing to underlying risk | ||
| Underlying risk of MI in 5 years | 5-year risk of MI (%) |
NNTH |
| Low risk profile (40 year old man with none of risk factors listed below) | 0.1 | 1111 |
| Impact of additional single risks: | ||
| If total cholesterol 240 mg/dL (6.2 mmol/L) | 0.2 | 555 |
| If diabetes | 0.2 | 555 |
| If ECG-LVH | 0.2 | 555 |
| If sBP 160 mmHg | 0.3 | 370 |
| If HDL 35 mg/dL (0.9 mmol/L) | 0.3 | 370 |
| If smoking | 0.4 | 277 |
| Impact of multiple risks: | ||
| If HDL and total cholesterol unfavourable | 0.8 | 138 |
| If smoking and diabetes | 1.1 | 101 |
| If smoking and total cholesterol unfavourable | 1.0 | 111 |
| If smoking and sBP 160 mmHg | 1.3 | 85 |
| If smoking and HDL unfavourable | 1.6 | 69 |
| If smoking and lipids unfavourable | 3.1 | 35 |
| If all unfavourable combined (excluding ECG-LVH) | 10.1 | 11 |
| If all unfavourable combined (including ECG-LVH) | 15.0 | 7 |
Comment
This model supports the conclusions from both D:A:D and SMART studies to caution against using abacavir in patients with high underlying cardiovascular risk.
It also demonstrates the potential clinical impact from reducing other risk factors where alternative treatment options are not available.
References
2009-02-10
IB2009-01-10
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