Tuesday, January 2, 2007

Confidence limits on NNTs - a guide to comparing NNTs

Previously in this series I discussed the definition of the NNT (i.e. when comparing therapy to placebo, it's 1/absolute risk reduction of therapy) and how to interpret it (it's the expected number of people that you would have to treat to prevent one unfavorable outcome). It's evil twin, the NNH, is similarly calculated and interpreted in association with an adverse event.

In my first entry on the subject, a commenter asked whether the NNT is a number or a statistic with an error. The answer is that it's a statistic with an error. Problem is, most people do not report the error (or confidence interval) along with the NNT. The error or confidence interval helps us answer questions such as "Drug A has NNT of 21 and Drug B has NNT of 22. Is there really a difference?"

To begin with, I'll assume that all needed data is available in this form:
  • Risk of unfavorable outcome for placebo group
  • Risk of unfavorable outcome for treatment group
  • Sample size
To calculate the NNT itself, just do 1/(risk in placebo-risk in treatment). The sample size is not needed. However, to calculate the error, the sample size is necessary.

Then, we calculate the error for (risk in placebo-risk in treatment) (i.e. 1/NNT). The expression is a little more complicated, but not hard to put into a spreadsheet or calculator:

std error = sqrt(risk placebo * (1 - risk placebo) / (# in placebo group) + risk treatment * (1 - risk treatment) / (# in treatment group)),

where sqrt means take the square root of the whole thing. A simple explanation goes as follows:

risk group A * (1 - risk group A) / (# in group A)

is the variance of the estimate in group A. Add the variances in the placebo and treatment groups to get the variance of the treatment, and then take the square root to get the error. So two principles: variances (often) add, and the error is the square root of the variance.

To get a 95% confidence interval of the risk reduction, you take the difference and add/subtract 2 times the error1.

Example. In the last entry I compared niacin and simvastatin. The article has some of the information we need:

DrugRisk placeboRisk treatmentSample size
Simvastatin21.5%13.5%2221 (sim)
2223 (placebo)

I had to do some sleuthing to get the sample size numbers. For niacin a Google search for the Coronary Heart Disease project landed this draft of a report, from which I found a total sample size and divided by 6 (there were six groups). For the simvastatin number I used the Wikipedia entry on Scandinavian Simvastatin Survival Study to get the sample size. But anyway, we're able to do a confidence interval calculation. We start with niacin:
  • risk reduction = (36.5% - 31.5%) = 5% (so NNT = 1/5% = 20)
  • error = sqrt(0.365 * 0.635/1390 + 0.315*0.685/1390) = 0.018 = 1.8%
  • 95% confidence interval of risk reduction is 5%-2*1.8% to 5%+2*1.8% = 2.4% to 8.6%
The 95% confidence interval for risk reduction for simvastatin is 5.8% to 10.2%. (I got a risk reduction of 8% and standard error of 1.1%).

End example.

The simplest way to get a 95% confidence interval for the NNT is to just do 1/confidence limits. You will also have to invert the order of the limits. Granted, this isn't necessarily the best way, and I'll probably show how to do another way one day, but it's easy and are actual (approximate) 95% confidence limits. So the NNT limits for niacin are (1/8.6% to 1/2.4%) = (11.63 to 41.7). The NNT limits for simvastatin are (9.8 to 17.2).

From this quick and dirty calculation, it's not absolutely clear that niacin has higher efficacy than simvastatin. Part of the reason for this is the wide error in the risk reduction estimate for niacin, which comes from the fact that 31.5% of subjects in the niacin group of the study had a cardiovascular event.

A few other issues are worth point out here, and they cloud the issue even more. I took these numbers from two different studies: the 4S study and the Coronary Heart Disease project. If you look at these two studies, they have different inclusion criteria (e.g. the CHD project had an inclusion criterion of men only). Eventually, in trying to get the information we need, we come across such barriers. Preferably, the numbers I used above would have come from the same study, and given the differences between objectives and populations in the studies, the comparison between the simvastatin and niacin NNTs are not as straightforward as back-of-the-envelope calculations as given above can lead you to believe. It's important to keep the limitations of both the data and the statistics in mind.

1Technical details: this is an approximate interval, and those who have been through stats classes may prefer to use z0.025=1.965. I don't think it matters too much except in cases that accuracy is very important such as academic reports and regulatory submissions. Also, this confidence interval has fallen out of favor with statisticians, but is easy and useful for the kinds of back-of-the-envelope things I'm doing here. [back]

Monday, January 1, 2007

Not quite a repost - Number Needed to Treat (NNT)

Rather than repost this entry on the NNT, I thought I would discuss the issue a little further. For background, here are some references:
For the individual, the NNT doesn't really matter. After all, when you take a drug, it doesn't matter what happens to other people on the drug. It only matters what happens to you. However, for public policy makers and insurance companies, the NNT has become very important. The reasoning goes as follows:

Say you, as an insurance company, wanted to compare two therapies to prevent serious cardiovascular events (e.g. cardiovascular death, myocardial infarction): niacin and simvastatin. The cost of a cardiac event is high both economically (in terms of health care cost and days missed) and in pain and suffering. Then we can answer the following question: what is the cost of preventing one event using niacin and simvastatin?

You can organize the work as follows:
Therapy Source Duration (years) Cost/Day NNT Total Cost/1 prevention
Niacin Coronary Drug Project 6.2 $0.21 20 $9,511.11
Simvastatin 4S 5.4 $0.93 13 $23,845.71

The only calculated column is the last one (you can easily set this kind of table up in any spreadsheet). The calculation is total=duration*365.25*cost/day*NNT. In addition, I used a favorable cost for simvastatin (although it will get more favorable when more generics hit the market) and an unfavorable cost for niacin. Source of data is Tables 1 and 2 from Therapeutics Letter, May 1998 as shown here. Note that cerivastatin has been withdrawn since then, and a generic form of simvastatin has hit the market.

You can interpret the last column as follows: to prevent one cardiovascular event, you expect to pay $9,511.11 for niacin therapy or $23,845.71 for simvastatin therapy.

Simvastatin actually doesn't compare too unfavorably with niacin therapy. Other measures such as safety profile (including NNH - Number Needed to Harm - for the more serious adverse events) are needed in the decision making process, but under this measure we should not rule out simvastatin as a valid and effective therapy. The main issue is unit cost, something that will change as generics come on the market or something that can be negotiated down (especially in the case of transporting drugs to developing countries).

Speaking of safety profile, that is something that hasn't been figured into the table above. The costs associated with flushing, gastrointestinal problems, skin problems, and acute gout, -- all associated with niacin -- along with the NNH for these issues, need to be addressed. On the simvastatin side, creatine kinase elevation with muscle weakness and rhabdomyolysis need to be addressed, along with the other adverse events that have been found to be associated to statin therapy in the last couple of years. These expected costs are to be added to the costs in the table above.

There are a few caveats to the NNT a couple of which I mention below:
  • First, the NNT is a number derived from an estimate, i.e. 1/absolute risk reduction. Though most estimates are reported with a standard error, NNTs are not (and this is a flaw). Likewise, the costs above have a range deriving from several sources: range of cost, range of NNT, range of durations studied.
  • The NNT is based on population-based statistics. For an individual making an individual decision about healthcare, it carries less weight than it would for an insurance company deciding which therapies to cover or a healthcare NGO deciding which therapies to pay for transport into developing countries. Side effect risk factors, metabolism profile, and other individual factors carry more weight (and those carry less, but higher than zero, weight with policy makers).
So next on my plate in the NNT series is how to compute a standard error from measures that you see in the literature.