SUN vs BEVþIFN in first-line mRCC therapy: no evidence for a statistically significant difference in progression-free survival

Sir, 
 
It is with great interest that I read the article by Thompson Coon et al, as I agree with the authors that there is a need for performing indirect treatment comparisons in order to offer guidance on therapy decisions to oncologists. 
 
As this is an important topic, I would like to outline some methodological issues that are related to the Thompson Coon et al analysis.


Sir,
It is with great interest that I read the article by Thompson Coon et al, as I agree with the authors that there is a need for performing indirect treatment comparisons in order to offer guidance on therapy decisions to oncologists.
As this is an important topic, I would like to outline some methodological issues that are related to the Thompson Coon et al analysis.

P-VALUE CALCULATION APPROACH
Using a one-sided t-test to calculate a P-value, as performed by Thompson Coon et al (2009), has to be regarded as a questionable approach, as two-sided t-tests are the common approach in clinical research and should be expected in such an analysis by the clinical readers of BJC. Even if this unusual approach is explicitly described, the findings in the abstract are misleading, as they seem to show statistical proof on a significant difference comparing sunitinib (SUN) with bevacizumab (BEV) þ interferon alpha-2a (IFN) in firstline metastatic renal cell carcinoma. To elaborate, Thompson Coon et al (2009) simply calculated the P-value as the proportion of Bayesian Markov Chain Monte-Carlo (MCNC) trials in which the hazard ratio (HR) for any comparison exceeded the indirect comparison HR of '1'. In contrast, the authors should have reported the number of instances in which the lower confidence limit of HR for each iteration exceeded 1 or simply tested the hypothesis that Log(HR) ¼ 0, using the standard z-statistic. If a valid statistical method is used (e.g., that from Snedecor and Cochran, 1989), this would have led to a P-value that indicates a non-significant difference between SUN and BEV þ IFN. This non-significant difference between both therapy options using a two-sided t-test is obvious, as the indirect comparison HR of SUN vs BEV þ IFN exceeded '1' in the upper 95% confidence interval limit.

MCMC SAMPLING
The authors performed an indirect comparison using Bayesian MCMC sampling, with IFN as a common comparator, adopting a fixed-effect model. Point estimates and 95% confidence intervals were calculated from 100 000 simulated draws from the posterior distribution after a burn-in of 10 000 iterations.
This up-sampling of point estimates has most likely led to more narrow confidence intervals that may be responsible for possible significant differences between treatments. Taking into account the fact that the SUN pivotal trial included 750 patients (Motzer et al, 2007) and the pooled BEV trials included 1381 patients (Escudier et al, 2007;Rini et al, 2008), the chosen number of simulation samples overpowers that of base trials. In general, it is recommended to either select the number of iterations on the total number of patients or the expected number of patients in the country of interest; hence, around 2000 simulation samples would have been an appropriate choice.

INDIRECT COMPARISON APPROACH
Although the authors name the Bucher et al methodology (Bucher et al, 1997) as 'a fairly simple analytical approach', the Canadian Agency for Drugs and Technologies in Health (CADTH) (Wells et al, 2009a) and others (Tudur et al, 2002;Song et al, 2003) have identified this method as the most suitable approach for performing indirect treatment comparisons. The Bucher et al methodology is to be regarded as the gold-standard method for indirect treatment comparisons, as it is transparent and excludes the risk of producing misleading results that may be produced by up-sampling the power of base trials.

BASE DATA USED
An adequate indirect comparison approach should consider pivotal trials performed under similar conditions as comparable, and assume highest data quality (independent radiology review of PFS, blinded as opposed to the open-label study).
If the author pooled a pivotal trial (Escudier et al, 2007) and an investigator-initiated trial (Rini et al, 2008) for BEV þ IFN, the same approach should have been applied for SUN using the pivotal trial (Motzer et al, 2007) and first-line outcomes from the expanded access study (Gore et al, 2007). pivotal trials (SUN vs IFN 0.538; 95% CI: 0.439 -0.658 (Motzer et al, 2007), BEV þ IFN vs IFN 0.571 (0.450 -0.723) (Escudier et al, 2009)), there is no statistically significant evidence for a difference in efficacy with respect to PFS between SUN and BEV þ IFN-a. The indirect comparison HR was 0.942 (95% CI 0.69 -1.29; two-sided t-test P ¼ 0.71).
CADTH offers an open-access tool (Wells et al, 2009b) that enables researchers worldwide to re-perform and validate our findings.
As indirect treatment comparisons are increasingly used in medical decision making, I considered it important to draw attention to methodological issues for the benefit of those both performing and using the results of these comparisons.