Irregular Report 15

Congratulations to Dave Zabriskie and Tyler Hamilton for winning the USPro time trial and road race respectively. Both championships are are rewards for hard work in the face of additional challenges. Well done.

Here and There
The VeloNews says reports state Manuel Beltran's "B" sample from the Tour de France also tested positive for EPO.

The CyclingNews reports that the Vuelta is the first race to use the UCI's "bio-passport" and that all riders were tested prior to the beginning of this year's third Grand Tour. Testing for the "new" EPO CERA will also apparently be done.

Rant posts part one of a two part interview with Mike Straubel of the Sports Law Clinic at Valparaiso University. In this installment they discuss the stunning CAS decision that came down against Floyd Landis earlier this year:

DR: When I first read the Landis decision, I thought, “Boy, this is a really strongly worded opinion.” It really seems like [the CAS panel are] taking Landis’ legal team to task.

MS: They certainly believed all of USADA’s/WADA’s experts and none of Landis’ experts. And it sounds as if not only the legal strategy and the way in which Landis’ lawyers made their arguments, but the way in which the experts … were aggressive [in their testimony and statements for Landis] backfired, too. I think there was one section of the opinion where the panel took the experts to task for being a little too partisan and a bit too much advocates rather than experts.

Straubel is a professor whose law clinic successfully defended LaTasha Jenkins. He concludes that the award given in the Landis case is legally consistent with the presumptions built into the WADA system, and carefully avoids saying whether he considers it to be absolutely or morally correct. He's concerned that, basically, an athlete has no way of making a defense on the merits of a test that has been declared to be positive.

Look also for Part II, forthcoming.

Racejunkie discusses the usual cornucopia of topics including the "fabulous" Vuelta which started yesterday.

Healthy Living manages somehow to cite Floyd Landis in a discussion of menopausal hormone testing. Don't think that Floyd has ever been tested for his FSH levels.

The Spoof , in a noble attempt at humor, drags the Cowardly Lion into the doping mix and predictably invokes the name of Floyd Landis.

Full Post with Comments...

Irregular Report 14

An emailer points us to a New York Times report on a medical test that has not been approved by the FDA because of a 1% false-positive rate -- the FDA takes that to mean "the test doesn't work."

Dr. Berchuck of Duke said only 1 of 3,000 women has ovarian cancer. So even if a screening test had a 1 percent rate of false positives, it would mean that 30 out of 3,000 women tested might be subject to unnecessary surgery for every one real case of cancer.

Others say, what the hell, we take 'em out anyway, so what's the problem?

Blogs
Rant wonders if any of the anti-doping tests dome recently at the Olympics which thus far have yielded few positives, mean anything. He points to Larry's excellent piece here on TBV.

Racejunkie "handicaps" the incomparable Vuelta which starts this weekend.

BBKE passes word of an EPO positive for Maribel Moreno, somehow dragging Landis in.

Magnificent Bastards has what purports to be a memo from Mr. Pound, "To all you ****ers that made fun of my name." We've tried real hard not to stoop to that particular attack -- there's so much more to criticize in a substantive way. And given the other content, we have to wonder if Mr. MB is a confident heterosexual.

Full Post with Comments...

Larry's Last Call (?)

Larry sends the following musing, and wonders if this may be his last opus on L'Affaire Landis.

Bourbon and Beer:

Why The Landis Positive Test Results May Be Meaningless

(An Exercise in Hubris by Larry)

Here on TBV, we've spent time and effort trying to explain how Floyd Landis could have tested positive for testosterone doping without having doped with testosterone. We've focused on things that could have caused the positive test: it might have been the beer he drank, or the cortisone he took for his ailing hip, or small but mysterious "blips" we can see in his test results. We've also considered a few different lab mistakes that might have caused the positive test: failure to correctly identify the substances in Landis' urine, or possible contamination of these substances, or overlaps in these substances that might have resulted in the labs improperly measuring two substances at once. Yours truly has recently considered a theory that Landis' cortisone treatments might have impaired his liver function, which might have affected his metabolism of testosterone and thrown off the test results. Each of these theories is impossible to rule out, and impossible to prove.

Moreover, each of these theories assumes that something somehow went wrong with the lab tests.

Until recently, I had not considered a second possibility. (Thanks to Tom Fine for suggesting this possibility to me.) Maybe there was nothing wrong with how the lab conducted these tests. Maybe the test measurements are 100% accurate. And maybe, just maybe, these test results are meaningless. Maybe, just maybe, Landis' system, his metabolism, his biochemistry, were able to NATURALLY produce the results measured by the lab.

[MORE]


To explain this possibility, I need to do a couple of things. First, I need to discuss scientific questions that I do not fully understand. I am a lawyer, not a scientist. Hopefully, this article will stimulate debate among the scientists and scientifically inclined on this site, and my discussion will be corrected and supplemented as necessary.

I also need time to tell this story. It is a story that will look at scientific studies performed on three continents. It is a story that will consider the marvelous and maddening diversity and complexity of human biochemistry, of how the human system refuses to obey simple rules of thumb. In simpler terms: this is a story of bourbon and beer.

I've actually cut this story short. There is more to tell, if people are interested.

An Introduction and Some Background

Let's first discuss the background of the Landis case, and define some terms.

Floyd Landis' problems began after he won stage 17 (S17) of the 2006 Tour de France (TdF), As the winner of S17, Landis submitted a urine sample to TdF doping control. The urine sample was divided into two portions, an "A" sample and a "B" sample. The two samples were delivered to the French anti-doping lab (LNDD) for analysis. LNDD tested the "A" sample immediately, and froze the "B" sample to be tested later if necessary.

LNDD began its analysis by performing general screening tests on the S17 "A" sample. These tests indicated that LNDD needed to perform additional tests to determine whether FL doped with exogenous testosterone. Exogenous testosterone is testosterone that comes from a "doping" source like a cream or an injection, in contrast to the endogenous testosterone that is naturally produced by the human body. .

LNDD then performed a "T/E" ratio test to check the ratio of testosterone to epitesttosterone in Landis' S17 sample. According to LNDD, this ratio exceeded the 4:1 ratio established under the rules of the World Anti-Doping Agency (WADA) as the threshold ratio for a doping offense. LNDD then performed a second test on the S17 sample, called a "carbon isotope ratio" (or CIR) test. We'll discuss the CIR test in some detail in this article. According to LNDD, the CIR test indicated that Landis had doped with exogenous testosterone. Once FL learned that his S17 "A" sample had tested positive for doping, he exercised his right to require LNDD to test the S17 "B" sample. For the "B" sample, LNDD was required to perform only the "T/E" ratio test and the CIR test. LNDD concluded that its "B" sample testing confirmed the results of its "A" sample testing.

A positive anti-doping test result is sometimes referred to as an adverse analytical finding, or an AAF.

Landis exercised his right under the WADA rules to challenge his AAF in an arbitration proceeding. Prior to the arbitration proceeding, the LNDD performed the CIR test on other urine samples given by Landis during the TdF, and some of these samples also tested positive for exogenous testosterone. The arbitration panel ruled that the LNDD had improperly performed the T/E test, but he panel upheld the AAF on the basis of the CIR test performed on the Landis S17 urine sample.

One further definition: in this paper, we use the term ADA to refer to the various national and international anti-doping agencies. WADA is an ADA, as is the U.S. Anti-Doping Agency (USADA) that prosecuted Landis' AAF case.

Testosterone is Testosterone

Now that we have discussed the background of the Landis case, we can dive into our analysis of why the Landis test results may add up to nothing meaningful. A good place to begin this discussion is with a question: exactly what did the LNDD find when it performed its CIR test?

If you've followed the Landis case, you've probably read that the CIR test "discovered" exogenous testosterone in Landis' urine. These statements are incorrect. The CIR test cannot "discover" exogenous testosterone, for the simple reason that no such discovery is possible. Exogenous testosterone IS testosterone, and testosterone is a natural substance - all human beings naturally produce testosterone. From a chemical standpoint, artificial and natural testosterone are identical. If you could somehow place a molecule of natural testosterone side by side with a molecule of artificial testosterone and examine them both down to the most minute atomic and subatomic level of detail, chances are that the two molecules would be identical in every way. Moreover, even if you could spot a difference between the two molecules, the difference would not indicate whether one molecule is natural and the other is artificial. In simplest terms, testosterone is testosterone, regardless of where it comes from or how it is made.

Testosterone is a good illustration of why doping testing is so difficult to do. For the most part, modern athletes don't dope with artificial substances. They dope with natural substances like EPO, and insulin, and human growth hormone (HGH) ... and testosterone. We consider these practices to be doping, not because the substances are unnatural, but because the doping substances are produced outside of the human body.

To detect doping with a natural but exogenous substance, the ADAs must find some property of the exogenous substance that differs from the natural substance. For some forms of doping (like autologous blood doping), the ADAs have not yet discovered any such property. For a while, the ADAs could not find any such property associated with exogenous testosterone. Instead, the ADAs focused on the amount of testosterone in an athlete's system, reasoning that athletes could not naturally produce endogenous testosterone above a certain level. But this assumption proved to be incorrect in a lot of cases, and the scientists continued to search for another property that is characteristic of exogenous testosterone.

In the 1990s, the scientists announced that they'd discovered such a characteristic property. The property they discovered is a characteristic feature of all biochemistry, and is one of the differences between bourbon and beer.

Bourbon, Beer, and Carbon-Based Life Forms

Human beings consist primarily of three elements: hydrogen, oxygen and carbon. These three elements have the capability of joining together into a dizzying array of complex molecules, and the processes that sustain life rely on the ability of an organism to create and manipulate these molecules. Testosterone is one of these molecules, made up of 19 carbon atoms, 28 hydrogen atoms and 2 oxygen atoms.

About 99% of the carbon on earth is carbon-12, or C12. C12 has an atomic weight of 12, with an atomic nuclei containing 6 protons and 6 neutrons. However, a small amount of the carbon on earth is C13, with 6 protons and 7 neutrons. You can think of C13 as slightly heavier than C12. C12 and C13 are pretty much interchangeable. Every molecule (like testosterone) that contains carbon might contain C12 carbon or C13 carbon, or both.

Speaking generally, the processes of life prefer C12 over C13. This preference varies, depending on the chemical process in question (as we'll see in a minute). For some chemical processes, the lighter nature of C12 means that it takes less energy to work with a C12 atom than with a C13 atom. For this reason, living things tend to have more C12 and less C13 than non-living things, because life generally prefers chemical processes that require the least amount of energy.

The preference for C12 over C13 is a general rule. Not all biochemical processes prefer C12 to the same extent. A good example of this is photosynthesis, the process used by plants to generate energy from sunlight. Most plants are so-called C3 plants that utilize a form of photosynthesis that strongly prefers C12 over C13. However, a smaller number of plants - including corn -- utilize another form of photosynthesis (either C4 or CAM) that does not strongly prefer C12. So, corn will have a bit more C13 in its molecules than will wheat (a C3 plant).

We are what we eat (and drink!). If all we ate and drank was beer (made of C3 plants), we'd have a relatively low amount of C13 compared to C12 in our molecules. If we then gave up beer in favor of bourbon (made primarily from corn), the amount of C13 in our systems would go up. Human biochemistry manufactures testosterone from what we eat. If what we eat is relatively light in C13, then our endogenous testosterone will tend to be light in C13. If what we eat has a relatively large amount of C13, then our endogenous testosterone will also have more C13.

In the 1990s, the ADA scientists considered the C12 and C13 makeup of exogenous testosterone. This testosterone is usually made from soy, and soy is a C3 plant that is light in C13 atoms. Bingo, thought the scientists! On average, exogenous testosterone should have fewer C13 atoms than endogenous testosterone. If a person is doping with exogenous testosterone, the C13 content in the person's testosterone should decrease - and this decrease could be measured with CIR testing.

A new anti-doping test was born: the CIR test for exogenous testosterone.

In order to function as an effective anti-doping test, the CIR test must be able to measure very small differences in C12 and C13 content. It is an AAF under the WADA rules if the CIR test for testosterone measures 0.3% less C13 than would be expected. Given that C13 is only about 1% of the carbon on earth, and that the test is supposed to be 95% accurate, that means that the test must be accurate to about 1 carbon atom in 650,000 (per my rough and inexpert calculations). Supposedly, the CIR tests ARE this accurate, if performed correctly. But this statistic illustrates why it's impossible to "discover" exogenous testosterone. At best, the CIR test might enable the scientists to "discover" an exceedingly small difference between populations of exogenous and endogenous testosterone molecules.

More About the CIR Test

As we've learned above, the goal of the CIR test is to measure the C13 content of the testosterone in an athlete's system. If that C13 content is too low, then according to the ADA scientists, the athlete has been doping with exogenous testosterone.

From this description, it may surprise you that the CIR test for exogenous testosterone does not actually look directly at testosterone . For whatever reasons, the test focuses on testosterone metabolites in an athlete's urine. The human body metabolizes (breaks down) testosterone into other substances, and these break-down substances are called "metabolites". Specifically, the LNDD's CIR test (like the test used in other WADA labs) measures the C13 content of 4 testosterone metabolites: androsterone (andro), etiocholanolone (etio), 5a-androstanediol (5aA) and 5b-androstanediol (5bA).

As we've discussed, we are what we eat, so the C13 content of these four metabolites will depend to some extent on the person's diet whose metabolites we want to measure. Because different people eat differently, the scientists had to design the CIR test in a way that would correct for different diets. For this reason, the CIR tests typically look at two other metabolites: 11-Ketoetiocholonolone (11Keto) and 5b-Pregnanediol (5bP). According to the scientists, the C13 content of these metabolites depend solely on a person's diet and are not affected by exogenous testosterone. These types of metabolites are sometimes called endogenous references, because they are supposed to reflect a person's endogenous delta values without regard to whether the person has taken exogenous substances. So, if the C13 difference between a person's andro or etio and 11Keto is large enough, or if the C13 difference between a person's 5aA or 5bA and 5bP is large enough, then the C13 difference cannot be explained by diet, and can only be caused by something else ... like exogenous testosterone. Or so the theory goes.

The C13 content of a substance is typically stated as a "delta" value. It is usually negative, in the range of -20 to -30 or so. The more negative the delta value, the less C13 has been measured in the substance. The calculations noted above (andro minus 11Keto, etio minus 11Keto, 5aA minus 5bP and 5bA - 5bP) are sometimes called delta-delta values. The WADA rules provide for an AAF if the delta-delta value for any of these metabolites is more negative than -3. (LNDD added a margin of error of 0.8 to this calculation, so by the LNDD, a delta-delta had to be more negative than -3.8 in order to find an AAF.) LNDD was willing to declare an AAF if the delta-delta value for only one metabolite was more negative than the rules allow; other WADA labs will not declare an AAF unless more than one delta-delta value is too negative. For example, UCLA reportedly requires three delta-delta values to exceed the negative limit before it will declare an AAF.

The CIR Test Finds Dopers - Sometimes

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Enough about the theory behind the CIR test. Let's ask the question: is the CIR test capable of catching dopers? To find out, let's look at a recent study performed by Saugy from the Swiss WADA lab and a host of others, reported in volume 71 of Steroids pp. 364-70, available for the moment at (Saugy 2006 Study)

In this study, 7 test subjects were given oral testosterone, and the scientists measured the T/E ratios and delta levels for andro and etio. In a number of cases, the measurements came out exactly the way you'd expect, given our discussion of the CIR test. For example, here are the results for one of the subjects:

Figure 1: Subject 2

The top chart shows the T/E ratio for subject S2. As you can see, when the subject was given oral testosterone, the subject's T/E ratio spiked to a high level, from a little less than 1:0 to over 90:0 (note that this is over 8 times as high as the level LNDD said they measured for Landis - this is presumably a very high level of testosterone). The bottom chart shows the delta values for the endogenous reference (a relatively straight line at the top) plus the delta values for andro and etio (the two lines dropping sharply at the time the oral testosterone was administered). This is exactly the kind of result we'd expect to see if the CIR test is a good test.

Unfortunately for the testers, not all the subjects reacted as we might have predicted. For example, look at the results for subject S1:

Figure 2: Subject 1 (yeah, they are in reverse order).

The bottom chart for subject S1 looks pretty much like the bottom chart for subject S2. But compare the top charts for these two subjects! While S2's T/E levels went through the roof, S1's T/E levels scarcely moved at all. It seems like S1 got no benefit whatsoever from his dose of testosterone. The authors of this study noted this result, and hypothesized that S1 might be a person who quickly metabolizes testosterone. In other words, as soon as the testosterone hit his system, S1 metabolized it into other substances, including the andro and etio shown in S1's bottom chart.

But if this is the explanation for S1's results, then how do we explain the following results for S3?

Figure 3: Subject 3

S3's results look like the results we'd expect from someone who skipped the study altogether! S3's T/E ratio barely moved after taking the oral testosterone, and perhaps more surprisingly, S3's delta values for andro and etio were nearly flat as well. What is the story here? Again, the authors of this study tried to explain S3's results as being the product of fast testosterone metabolism. But if S1 rapidly metabolized his testosterone dose into andro and etio, what happened to S3's dose of testosterone, which appears to have disappeared altogether? Did S3 further metabolize the andro and etio into even more basic substances? The study authors do not say.

The lesson to be learned here is an important one: human biochemistry is complicated and diverse. We cannot expect that two people will react to a doping product in the same way. Some people (like subject S2) will react as we might predict, and some (like S1 and S3) will not.

Is it possible that Landis may have an unusual biochemistry, and might also be capable of naturally producing unusual CIR results? Well, to consider this possibility, we have to proceed a bit further through the analysis. After all, we've just looked at a couple of cases where doping subjects produced unusual CIR results. But maybe this is something we'd only expect to see when people are doping. We have not considered whether a person NOT using doping substances might also produce unusual results. To consider this possibility, we have to look at a few more of the scientific studies.

Studies on Non-Doping Populations

Let's take a look at a second study, this one produced by a group including Don Catlin, the ex-head of the UCLA anti-doping lab. This study is reported in volume 47 of Clinical Chemistry (2001) on pages 292-300 (Catlin 2001 Study).

In most ways, the Catlin 2001 Study is typical of published studies on CIR testing for exogenous testosterone. (Don't worry if you have trouble following this description.) The study first looks at a control group of non-doping subjects, and measures a mean average delta-delta reading and standard deviation for the control group. The study then adds three standard deviations to the mean average delta-delta, to come up with a delta-delta threshold that should be beyond what a normal non-doping subject could test at merely by chance. Then the study attempts to find urine samples from people who have taken (or are suspected of having taken) exogenous testosterone, to see if their delta-delta readings are beyond the threshold reading. If so, the scientists conclude that their method is a valid test for exogenous testosterone, and they propose that the drug testing authorities adopt their threshold as the standard for determining whether a doping violation has occurred.

As part of his study, Catlin looked at the delta-delta measurements for 5aA - 5bP and 5bA - 5bP for a population of 74 male UCLA medical students who were NOT taking exogenous testosterone. Here are the results:

	Mean Difference	Standard Deviation	Threshold Test
5aA – 5bP	-2.09	0.68	-3.99
5bA – 5bP	-1.43	0.63	-3.47

Table 1: Catlin Data

In compiling their results for the negative control group, Catlin noticed something unusual: the delta-delta for 5aA was significantly more negative than the delta-delta for 5bA. This difference was significant enough to warrant discussion in the study. Catlin and his group put forth two possible reasons why 5aA might naturally have a more negative delta reading than 5bA:

* 5bA is thought to be metabolized only by the liver (hepatic metabolism). 5aA may be metabolized both by the liver and outside of the liver (peripheral metabolism)
* 5bA may be produced by metabolism of substances other than testosterone - for example, DHEAS.

But neither of these explanations tells why the delta reading for 5aA would be more negative than the delta reading for 5bA. Why would it matter, for example, that 5bA is metabolized only by the liver, while 5aA can be metabolized peripherally? Clearly, there must be differences between these two kinds of metabolism! Consider our earlier discussion of photosynthesis, where we described how some biochemical processes prefer C12 more strongly than others. If the differences in 5aA and 5bA delta readings can be explained by different pathways of metabolism, then it must be the case that the control group's peripheral metabolism preferred C12 more strongly than did the group's hepatic metabolism.

The Catlin 2001 study also briefly mentions another fact: the control group's average delta readings for 5bP (the endogenous reference) had a considerably less negative delta than either the 5aA or the 5bA. Three different metabolites, three significantly different delta readings, all of which were produced naturally and without doping.

This is a highly important piece of information to keep in mind: human beings can NATURALLY produce substances having different delta values. In other words, it's not the case that only doping can explain differences in the delta readings for various substances found in the human body.

What kind of differences can we expect to see in delta-delta readings for different sets of non-dopers? To answer this question, I've looked at two other studies comparable to the Catlin 2001 study: a study by Ayotte and others (Ayotte 2001 Study) contained in the exhibit package for the arbitration at GDC 0024, and a study by Saugy and others (Saugy 2004 Study) reported in the volume 28 of the Journal of Analytical Toxicology (September 2004). The Ayotte 2001 Study looked at delta-delta values for 78 people described only as "mixed athletes" from different nationalities. The control group for the Saugy 2004 Study was a group described only as "40 male caucasian subjects." Unfortunately, neither study measured the standard deviation for the delta-delta measurement, but only the standard deviation for the separate delta components. The results are shown below, along with the results of the Catlin 2001 Study.

Study	Delta - Delta	Mean Difference	Standard Deviation
Catlin 2001	5aA – 5bP	-2.09	0.68
Saugy 2004	5aA – 5bP	-0.3	1.00
Catlin 2001	5bA – 5bP	-1.43	0.92
Saugy 2004	5bA – 5bP	-0.9	1.15
Saugy 2004	Andro – 5bP	0.1	1.23
Ayotte 2001	Andro – 5bP	1.5	1.6
Saugy 2004	Etio – 5bP	-1.1	0.83
Ayotte 2001	Etio – 5bP	1.6	1.3

Table 2: Summary of Studies

The standard deviations for some of these measurements are uncomfortably high - note in particular the Ayotte 2001 standard deviation of 1.6 for Andro. This means that the Ayotte study could expect to see swings in the Andro delta measurement of close to 5 points that could be caused solely by chance. That's a pretty large swing in delta values! But to my view, even more significant is the difference in the mean average delta-delta values that can be seen in these studies. Pay particular attention to the mean differences measured for 5aA - 5bP (range of about 1.8), 5bA - 5bP (range of about 1.4), Andro -5bP (range of about 1.6) and Etio - 5bP (range of about 2.7).


The measurements in these studies are all over the board! And remember, these are measurements on populations that are presumed to be clean - these differences cannot be explained by doping.

Can the differences be explained by nationality? In the 1997 study by Shackleton and others (Shackleton Study) reported in Steroids volume 62 pp. 379-87 (available in the Landis team document package at GDC 1098 [huge!]), Shackleton compared delta values for twenty individuals of twelve different nationalities, and here's what he found:

Figure 4: Shackleton Data

In this chart, the open circles are delta values for 5bP, the closed diamonds are delta values for 5aA, and the closed rectangles are delta values for 5bA. Again, notice the lack of any discernable pattern in these results! The Indian and three of the Chinese subjects had 5aA more negative than 5bA, as in the Catlin study, but the French, Australian and Turkish subjects had the opposite result. Most nationalities showed 5bP values less negative than 5aA or 5bA, but this is not the case for the English or the French subjects. Moreover, a close look at the chart may cause us to doubt that the variations shown here are truly characteristic of the nationalities in question. For example, the measurements for the French subject do not match the measurements we get from the LNDD (where 5aA has a consistently more negative delta value than the 5bA). Also, where we have multiple measurements for the same nationality, these measurements do not match up. Note, for example, that for the 5 Chinese subjects noted above, three have 5bA delta values more negative than the 5aA values, one goes in the opposite direction, and one appears to be inconclusive.

Once again, the measurements seem to be all over the place, and we have reason to doubt that these measured differences are characteristic of various nationalities.

So, what can we conclude from all this? To be certain, the data displayed above reinforces what we learned from the Catlin study, that human biochemistry is naturally capable of producing substances having different delta values. But where the Catlin study suggested that we'd see rules and patterns in these delta value differences (for example, that 5aA would have a more negative delta value than 5bA), the other studies reveal seemingly random differences in the delta values for various individuals. It appears that human biochemistry is capable of producing a wide range of substances with a wide range of delta values, without any discernable rhyme or reason.

I have purposely held back a study from this analysis. It's a bit of a mind-blower. Let's look at it now.

Delta - Delta: It's Big In Japan

To my knowledge, the most comprehensive study ever performed on the delta-delta readings for a purportedly non-doping population (the Nagano Study) is mentioned almost as an afterthought in a study authored by Ueki and Okano in volume 13 of the journal Rapid Communications in Mass Spectrometry (pages 2237-43, 1999). This study looked at the 5aA, 5bA and 5bP delta readings for over 400 athletes participating in the Nagano Winter Olympic Games in 1998. This study is significant, not only because it is the largest and most diverse study of its type (to my knowledge), but also because it focused on a specific population of international (and presumably elite) athletes. The Nagano Study purports to measure non-doping suspects only.

The Nagano Study will take a bit of explanation, because its findings are reported differently than those in other studies. Set forth below are the details of the Nagano Study that are pertinent to our analysis:

	Mean	Standard Deviation	Range
5aA	-17.5	3.5	-15.6 to -24.1
5bA	-20.0	2.75	-15.2 to -26.2
5bP	-21.0	1.65	-17.2 to -23.8
5aA/5bP	0.86	0.163	0.47 to 1.12
5bA/5bP	0.96	0.098	0.73 to 1.12

Table 3: Nagano Study Data

The first thing to note here is that these results don't look like the results we've seen in some of the other studies. For one thing, the measured delta value for 5bP is the most negative of the three values measured, and contrary to what Catlin saw in his 2001 study, the 5aA is a lot LESS negative than the 5bA. My first reaction to the Nagano Study was "this can't be right!" But the Nagano Study is highly regarded - it is widely cited, including by WADA in its listed references to its technical document for CIR testing. Plus, the study appeared in a peer-reviewed journal. I don't have the "hubris" to suggest that we can ignore this study.

And look what this study has to say about CIR testing! For example, note that the standard deviation for measurements of 5aA in the Nagano Group (a group presumed not to be doping) is 3.5. This is a HUGE standard deviation - it means that we could expect to routinely see delta values for 5aA that are 3.5 more negative than the mean, and that we would have to see a delta value more than 10.5 below the mean before we could conclude that the value was not "natural" (i.e., that it was not a chance occurrence). If we can expect delta values to naturally range up to 10 points from the mean, then that would pretty much blow all CIR testing out of the water. To my knowledge, no lab has ever measured a delta value 10 points more negative than the mean.

Look at the values reported in this study for 5aA/5bP and 5bA/5bP. Unfortunately for us, these are not delta minus delta values, like we've looked at before. These are delta divided by delta values (or delta/delta values). Luckily, a number of the studies (including Catlin 2001) have recommended a delta/delta threshold for doping of 1.1:1.0, so we can consider a 1.1 delta/delta value to be roughly the same as a -3 to -4 delta - delta value. But per the Nagano study, we could not set a delta/delta threshold anywhere near as low as 1.1. The appropriate threshold supported by the Nagano Study (mean plus three times the standard deviation) would be 1.37:1.0.

What was Landis' HIGHEST measured delta/delta value? By my calculations, 1.22:1.0. That's barely more than TWO standard deviations above the mean as measured in the Nagano Study.

If the Nagano Study was the WADA guideline, then there would be no AAF against Landis - or probably against anyone else - for doping with exogenous testosterone.

Conclusion: What Do We Make of Nagano?

What do we make of the Nagano Study? Is it possible that the Nagano Study is right, and that the other studies (from Catlin, Saugy, Ayotte and the rest) are all wrong?

To understand what to make of the Nagano Study, we can see what other studies had to say about Nagano. For example, the 2001 Catlin Study politely suggested the possibility that "our analytical method differs from that of Ueki and Okano." But the Catlin study failed to point to any actual difference in analytical methods, and I would argue that mere differences in analytical methods could not possibly explain the differences in results between these two studies. No, there would have to be something WRONG with the analytical method used in the Nagano Study before one could conclude that it would be safe to rely on the results reached in the 2001 Catlin Study.

The 2004 Saugy Study also examined the Nagano Study, and noted that "there are striking differences" between the findings of the Nagano Study and the 2004 Saugy Study. Like Catlin, Saugy nowhere stated that the Nagano Study was wrong. Like Catlin, Saugy suggested that the differences in results might stem from differences in the analytical methods used. But Saugy also noted a second possibility: he pointed out that the athletes at the 1998 Winter Olympics came from different locations with different diets, and Saugy suggested that this "diet heterogeneity" might explain the difference in results.

Saugy's comment here is worth considering. If the Nagano Study is different from all other studies because of "diet heterogeneity", then we'd want to pay special attention to the Nagano Study in considering the CIR testing at an event like the Tour de France. The Tour de France, like the Winter Olympics, attracts elite athletes from around the world. The Tour de France participants will also present the testers with "diet heterogeneity". If "diet heterogeneity" explains the results reached in the Nagano Study, then we'd expect to see similar results in a study performed on riders in the Tour de France ... and we'd have particular reason to doubt the results of any CIR test coming out of the Tour de France.

My own guess is that "diet heterogeneity" is not a full explanation for why the Nagano Study reached different results from the other studies. Since the Nagano Study looked at a large and diverse population of subjects, my guess is that what we're seeing is the product of "human heterogeneity". People are different. They have different biochemistries. These biochemistries are capable of producing testosterone metabolites with differing delta readings, for reasons we do not presently understand. The more diverse the population we study, the wider the variations should be in these delta values.

Moreover, while it's true tha t the Nagano Study does not agree with the other studies we've examined, it's also the case that these other studies do not agree with each other. Each study we've looked at has reached different conclusions about the delta-delta mean we should expect from a random sample of non-dopers.

The conclusion I reach from all this is not an expert opinion, but I think it is the only logical conclusion. I conclude that the CIR test for exogenous testosterone is based on a false sense of human homogeneity. People come in a wider variety of types than the CIR testers are willing to admit. We don't have uniform delta-delta readings, we possess systems that are naturally capable of producing different delta scores for different substances, and we probably have different biochemical reactions to the same events.

Different stokes for different folks. One size does not fit all.

In short, this non-expert believes that Floyd Landis could have naturally produced the results measured by the LNDD, without need of exogenous testosterone.

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Irregular Report 13

News
The CyclingNews notes that the "John Doe vs USADA" lawsuit has been dismissed.

CTV.ca posts a piece about doping at the Olympics in which it's noted that far fewer "positives" have been found than expected at this year's games.

Blogs
Pommi shows what could potentially happen if you don't wear your helmet when you ride. He also gives us some very detailed "pictures" of himself. Keep the faith!

Racejunkie notes more defections from the beloved Vuelta, "doping" horses at the Olympics, and "Boom Boom" Boonen is back.

Rant writes about the low number of doping positives to come from this year's Olympics in Beijing and wonders if some athletes may be finding other less detectable ways of "cheating".

And:F looks at Berry, and starts to have questions about Landis.

Cheat or Beat points the finger, mostly at the Games. Bonnie Fishman would like a hero too.

Cycling 4 Charity ran into Landis at an event at Hearst Castle

(photo: Cycling 4 Charity)

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Irregular Report 12

News
The CyclingNews flashes a "truce" between the ASO and UCI:

The long-running political battle between the UCI and the Grand Tour organisers appears to be moving closer to an end following the announcement on Monday of a new "UCI World Calendar" system.

Under the proposed terms, participation in the 2009 and 2010 Tours de France will be governed by the agreement signed by the teams and ASO on 18 June. From 2011 onwards, the classifications of the UCI World Calendar would confer the right to participate, with either seventeen teams of 9 riders or eighteen teams of eight taking part

Reaction to the announcement can be found here.

Blogs
Bill Dykes writes about the upcoming Audi Best Buddies Challenge cycling charity ride in which Floyd Landis is apparently taking part.

Pommi unfortunately joins the "injured reserve list". Get well soon!!!

Racejunkie reminds us all of why we should still love cycling, despite all of the recent crap. Thanks for the kind blurb RJ, and yes, just to be able hear Phil Liggett and Paul Sherwin is enough of a reason to still watch cycling!

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Saugy's Page 26

In response to our post about Ashendon's "highly, highly unlikely" comment, we offered a figure from a presentation from Saugy of the Swiss WADA lab that challenged Ashendon's stated assumptions.

Figure 1: Saugy's page 26.

In response, there have been some questions where we obtained the numbers, and the answer was first by eyeball (proven good enough for Brenna), and now, by counting.

Figure 2: Count the dots, 1, 2, 3...

From this, we get 32/156= 20%, which sort of validates eyeballing as a methology (± 20%), at least in this case dealing with discrete samples.

Then, there is the suggestion that we should not look at the overall, but the specific case offered by Landis, of starting around 15.5 and ending up around 16.1.

Figure 3: How many that started around 15.5 ended up around 16.1?

From this, we'll suggest that 6/35 = 17%, which isn't quite 20%, but is certainly well above zero. One rejoinder to this is that we've drawn the boxes too wide, and that we should look only at individual columns and rows. We believe that would be an exercise in futility given the low number of data points and is overconfident in the margins of error in the source data.

At what point is something "highly, highly unlikely?" TBV professionally does highly-available computer systems, working between four and five nines as target reliabilities -- 99.99% and 99.999%. A motto here is "With a one gigahertz processor, one in a million is a thousand times a second." Whole percentages are not, to us, "unlikely", but virtual certainties. It's a matter of perspective.

Given that one of the reasons guys become GC contenders is because they recover well, one could argue the odds of a highly placed rider being in that group are higher too. Just at raw numbers, we've got 32 riders above the line, which is more than one per team. Who on each team is it mostly likely to be?

But...

Another argument has been made that, essentially, the 25, er, 20% who went up were doping. While that is an improvement over the sentiment "they are all doping", it is unprovable. The purpose of Saugy's presentation was to identify things that needed to be considered in implementation of a "passport" program, and he didn't suggest these were anything beyond data to be considered -- he made no accusations.

Finally, there has been no counter-argument to the observation that the first week of a tour is a "rest" week for riders who did intensive training the week before. In a rest week after hard training, it is a reasonable natural reaction to have these values go up. We suggested and maintain that Ashendon's assumption that the first week of the tour is a "hard week of cycling" is physiologically incorrect, and therefore invalidates his conclusion. It does not disprove his conclusion -- there are still reasons to look further, which we acknowledge and accept.

We remain convinced that

• The comment "highly, highly unlikely" is hyperbole, because we have shown a substantial likelihood of natural occurance, and shown one of Ashendon's premises to be invalid;
• Ashendon is correct to draw no conclusions from the available data, a point missed by the strident.
• Ashendon is correct to suggest more study would have been needed.
• Additional blood tests done on Landis during the Tour also provided no conclusions.
• If the UCI didn't do even more blood testing, that is not Landis' responsibility.
  
• No agency or party has officially or openly suggested Landis did any specific oxygen vector doping because doing so would be inappropriate and legally unsupportable.

This will not stop people from making insinuations, but this discussion is now available for those who wish to look further.

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Irregular Report 11

News
The Boulder Report posts a "truthiness" quiz and Floyd Landis is NOT one of the answers.

Blogs
Suitcaseofcourage finally got around to reading "Positively False" and felt there was good points made by the book which if true reveal that someone has some "splainin" to do. Thanks for the kind blurb.

Media
Someone named Jeff Nordin has "published" an instantly downloadable "ebook" of Floyd Landis' quotes. They will amaze you and inspire you according to the "author" whose blurb reads like a late night infomercial. Nordin also provides, as a "bonus" if you buy, the best online resources for Floyd Landis information, we're guessing we might make that list. One "review" is less than favorable.

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Highly, highly unlikely?

The "highly, highly unlikely" remark from Ashendon, in Mark Zeigler's story of July 2007, provides the exclamation mark to the "of course he doped" reaction to our recent post about the hematology values. As Tenerifed snipped:

“Going from 15.5 to 16.1 (in hemoglobin) is not that unusual when not competing,” Ashenden said by phone from Australia. “But it is very unusual to see an increase after a hard week of cycling. You'd expect it to be the reverse. You'd expect that to fall in a clean athlete. An increase like this in the midst of the Tour de France would be highly, highly unlikely.

“There's nothing where I could point to one value and say, 'This guy definitely doped.' But it raises red flags for me. I would definitely recommend to anti-doping authorities that an athlete presenting these values should be target-tested for blood doping.”

[boldface from Tenerifed]

We'll point out some things that weren't bolded in his reading of the story.

• "Not unusual when not competing"
• "Unusual to see an increase after a hard week of cycling"
• "Nothing where I could point to one value and say, 'This guy definitely doped.'

We'll get to the key assumption Ashendon makes in the above in a moment. For the moment, let's observe his conclusion isn't shared by all the experts either. In particular, it disagrees with a presentation by Saugy, who observed that 25% of riders would see the kind of change seen in the two Landis samples from the 2006 Tour, being a ride in Hb after 8 days of racing

Figure 1: Saugy Presentation, page 26.
About 25% of riders (the ones over the diagonal) have rising Hb values.

So, "highly, highly unlikely?"

To review what we understand of the basic theory, when not fatigued, a stressed body (work and altitude) will stimulate natural EPO delivery. This results in more reticulocytes, which a week or so later become hemoglobin carrying mature red cells. If the stress is short, the reti count may spike high, and be decreasing while the red count comes up. If the stress is long but not too intense, the reti count may stay relatively high, while the red count also rises. Should the stress be long with high intensity, fatigue may preclude production of more reticulocytes, leading to low reti counts and low red cell levels.

Hard Week?

How does this relate to the idea of a "hard week"? This is the assumption built into Ashendon's reasoning, that the first week of the Tour Landis rode was a "hard week" that would be a time of fatigue leading to a collapse of Hct and reticulocytes.

This seems to us an argument based on conjecture, and not supported by specific data. We don't know what Landis workload was before the tour, but it did leave him with a low Hct/Hb and high reticulocyte count. We also understand that strategically, a GC contender would be trying to take it easy the first week, so as not to be spent when the roads turn uphill. This seems like the natural strategy of any GC contender, probably more important for a clean rider than a dirty one. It's also probably more consciously adopted by a known contendor (Landis) rather than an opportunist (Vande Velde) or a domestique (Millar). That is, Vande Velde, while somewhat protected, probably felt more need to work to stay highly placed than Landis the first week, and Millar was supposed to be doing work.

Is there data to support this theory? That's why we included the stage summary and performance data in the original post. Up until that rest day, Landis had been averaging 3500 kj of work on the full-length stages, putting out 260w when pedaling, and 210w average over the length of the rides start to stop. That is not an intense amount of power. For comparison, Landis was doing 250w while bonked on Stage 16.

Now, let's look at Vande Velde's power data from the 2006 tour, from cyclingPeaks.com:

Stage	time	kj	tss	IF	watts
stage 2	5:45	3970	280	.699	192
stage 3	5:08	3500	256	.707	189
stage 4	5:06	3416	227	.668	186
stage 5	5:31	3510	235	.653	177
stage 6	4:19	3259	245	.753	209
stage 7 itt	1:04	1498	112	1.026	390
stage 8	4:26	3873	304	.828	243
stage 9	3:55	2484	143	.604	175
average (less s7)	4:44	3430	236	0.700	195
stdev (less 7)	0:40	487	61	0.07	23.6

Table 1: Vande Velde data from 2006 tour.

IF = intensity, 1.0 being at aerobic threshold.
Values > 1 start going anaerobic.

TSS = IF * hours * 100;

Is this hard? The pitiful, fat and 50+ TBV did a century in May that took 5:30, 3233 kj @ 163 watts, TSS 328, IF .772, and felt pretty good the next week, doing three hard, shorter rides.

It is certainly true that no stages in the Tour are "easy", and the workload and pace of the initial stages would kill most of the readership. And it is true that they are nervous for the riders, with lots of mental effort. This does not say that they are particularly physically demanding for the should-be-protected GC contending team leaders and domestiques not in the break. Vande Velde got out one day, on stage 8, and worked much harder.

By comparison, on stage 3, Mr. "Happy to be in front" Jens Voigt rode off into the distance:

"After a fast start and few early attacks, it was Jensy Voigt (CSC) who made a strong move at km 15 near Strassen, and he was quickly joined by Arrieta (AG2R), Pineau (Bouygues), Laurent (AG2R) and Etxebarria (Euskaltel). This was the right combination and the quintet cruised away as the peloton was in no mood to try and bring them back on the hot, hard and hilly stage. By Bridel, 5 km later, the break already had 1'30 and Voigt was virtual malliot jaune as the big German rouleur was in 47th, 0'36 behind leader Thor Hushovd. "

Voigt's day was 5:12, 5300 kj, at 283 average watts. That is a hard day of racing.

On the same early stages, Landis and Vande Velde did far more comparable efforts.

Stage	FL kj	VV kj	FL watts*	VV watts*
stage 2	3934	3970	195	192
stage 3	3969	3500	222	189
stage 4	3760	3416	209	186
stage 5	3749	3510	196	177
stage 6	3349	3259	223	209
stage 8	3481	3873	227	243
stage 9	2624	2484	203	175
average (less s7)	3552	3430	210	195
stdev (less s7)	467	487	13.35	23.6

Table 2: Landis and Vande Velde, 2006 Tour

* note average watts are computed by different methods and may not be truly comparable.

We see Landis did a whopping 120 kj more work a day (about one can of Coke) than Vande Velde, averaging 15 more watts over the first week -- which makes sense, because he did the same work in less time.

On stage 10, Voigt went on the break and blew up -- but Voigt's day was 5513 kj @ 281w, compared to Landis' 4377 @ 246w.

We think it reasonable to suggest the first week was not a "hard week" of cycling for Landis. Thus, Ashendon's predicate to his expectation of drop may not be true -- which means his conclusion may not be true either,

Saugy's data suggests that unless you think 25% is a slim prospect, "very, very unlikely" is hyperbole. A juicy quote for Zeigler to use, and ammunition for accusers, but it is a conclusion not supported by direct evidence.

Swings of reasonable size

The offscore methodology that Ashendon developed places limits well above and below any of those seen Landis, Vande Velde, or Millar. To date, we don't have data on a known-doping rider to see where there offscore lies, but there have been suggestions that the "odd values" that were discussed with Hamilton were pushing the high number very hard.

When people say Landis' values are "very high" or "very low", these relative terms become questionable, because they are well within the range that is considered "normal" by the off-score methodology.
For some idea of "natural variations", there is an anecdotal story at "Can't holder tongue" describing a non-doper's experience with odd reported blood values.


Given the paucity of information in the two Landis data points that are available, Ashendon is right to say (a) there is no smoking gun, (b) there is reasonable cause to look further.


Further investigation

We note that Landis had blood taken on four occasions during the tour, and nothing came of it. (Why the UCI only reported two sets of hematological data is an interesting question.) We might suspect that he was targeted for additional scrutiny, and that nothing came of it. That doesn't prove anything, as we know the available tests don't reliably detect everything. But the chain of reasoning is becoming very conjectural.

Unfortunately, the UCI running controls at the time did not seem to follow up thorougly and get enough data that one could possibly see the spikey pattern that Saugy discusses that would be indicative of manipulation -- or if the UCI did with the other tests, found nothing. It is not Landis' responsibility that no other samples were taken.

Conclusion

As far as we know, no one in an official position has ever seriously suggested Landis did anything other than Testosterone doping.

As far as we know, no one in an official position has ever made the argument that the micro-dosing of testosterone would have particularly enabled the performance of Stage 17. At best, there is conjecture that microdoses are believed by some racers (Papp) to enhance recovery, but there are no studies to support that -- USADA certainly never entered anything into the record.

We do know there is rumor and conjecture that Landis blood-doped, and a common twist is that the "blood he doped with" was spiked with testosterone from some training cycle. The latter makes little sense, for two reasons. First, blood-doping spins out the plasma that carries testosterone; and second, it doesn't account for the reported exogenous testosterone in some of the other B samples, if one thinks they are reliable.

As with so much else about the case against Landis, the available data seems inconclusive, and one is left with the weight of presumption as the probable determining factor. Looking at the two data points and making an accusation seems, objectively, to be as (in)valid as looking at Stage 17 and saying "I know that is doping."

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Blood values: Landis, Garmin, and that 48.5

[UPDATE: oops! Everyplace you see "48.5", note that the actual value is 48.2. Sometimes we should look more carefully at the primary documents.]

One of the arguments offered by those who think "Landis doped" comes from blood values that were presented late in the process. These never really came up in the litigation, because they aren't relevant to the issue of testosterone doping which was the charge.

They are arguably relevant if one is suggesting that Stage 17 was enabled in some way by Oxygen vector doping, through either some EPO-like substance or blood doping.

The argument being made is based on a single datapoint in the collection of Landis hematology data, the reported hematocrit value on 11-jul-2006. This was after an easy stage following the first rest day of that tour.

Here's the data in raw form:

Figure 1: GDC 1372, located in the GDC Binder on PDF page 1801.
UCI collected hematology values for Landis.
(click for bigger)

Conveniently, a discussion that tries to hang Landis on this crops out the irrelevant stuff, and presents just the germane numbers, focusing on the 48.5 hct value:

Figure 2: Edited version of Figure 1, more legible.

The question that is asked is, "does a rising hematocrit 11 days into the tour indicate doping?" And the assumed answer is, "of course it does, fool!" Well, fools we may be, but that's not necessarily a supported conclusion.

As we know, the UCI limit is 50, and while 48.5 is high, it isn't pushing the 50 level hard, so there's mandatory cause for a "no start" by the UCI.

But this isn't the only answer. We well know that hematocrit is very sensitive to hydration, and we don't have any data to indicate Landis' condition on that day. The reported value is also sensitive to the particular machine being used, and its calibration.

Phonak, which was the first team to start trying internal controls of any time, checked rider's HCT on its own, and would not see the UCI values. The internal limit was 48, to be sure of clearing the UCI limit of 50. How then did Phonak let a 48.5 slip? Probably because their value wasn't 48.5, or because they knew something about Landis' hydration state that would explain an upward fluctuation.

If one goes back to Velonews TV interviews during the period, you can hear that Landis has the rattle of a cold. Did a cold cause underhydration with fluid loss, or did some treatment he got do so? We don't know, nor do we have Phonak's internal control values, which seem not to have been recorded.

So, what can we say about the raw 48.5 hematocrit? Unclear. Since the argument that it means something is about contextual understanding, let's look at some more context. We'll start with the other values reported in the UCI document, the Hb and Reti (reticulocytes) values.

Let's take a peak at what Michael Ashendon said recently to The Boulder Report:

Perhaps because of the UCI's old fixation on hematocrit, many of us similarly key on that value as an indication of clean racing. But according to Ashenden, it's one of the least important. Hematocrit, or the percentage of total blood volume that is red blood cells, fluctuates by large amounts in even normal human beings. It's susceptible to issues ranging from the subject's hydration to proper sample transport (improper refrigeration causes RBCs to swell, disproportionately increasing their volume).

He also notes the wildly varying values between testers, consistent with Phonak seeing different values than the UCI:

One of the first things that Ashenden noted in examining results was the variability between official UCI figures and ACE figures, even for values taken just days apart. The UCI numbers were vastly more uniform. "Almost like a different person," said Ashenden of some of the ACE results.

What does Ashendon look at instead of Hct?

"The first thing I look at in interpreting results is reticulocyte count and OFF-score, then hemoglobin," explained Ashenden. "I also look at anything about a sample that is strange and might explain off values due to transport and testing issues - mean cell volume and hematocrit chiefly."

The off-score is computed with the formula: (HB*10) - (60 * SQRT(reti))

Extracting values by eyeball from the graphs that are published in the article, we get the following values for Vande Velde and Millar. To see if our data and off-score calculation method is correct, we pulled out the reported off-scores with the ones we calculated, and they are all pretty close, so we think we have decent data and computations. Due to the vagueness of the graphs, the dates are approximate.

Vande Velde				computed	reported
Date	event	HB	Reti	Offscore	0ffscore
10/27/07	off season	16.75	0.60	121.02	120
01/23/08	alt training	16.00	1.00	100.00	100
01/25/08	alt training	16.50	0.80	111.33	111
02/15/08	camp	15.25	0.60	106.02	107
02/24/08	camp	15.00	0.90	93.08	92
04/01/08	early season	15.50	1.20	89.27	90
04/18/08	early season	15.00	0.90	93.08	95
04/24/08	early season	14.25	0.80	88.83	90
05/01/08	camp	16.00	0.90	103.08	102
05/28/08	giro	15.00	0.70	99.80	100
07/16/08	tdf	14.75	0.50	105.07	105
avg		15.45	0.81	100.96	101
stdev		0.77	0.20	9.84	9

Table 1: Vande Velde's data from Slipstream.

Millar				computed	reported
Date	event	HB	Reti	Offscore	offscore
10/27/07	off season	14.50	1.80	64.50	63
11/29/07	off season	14.75	0.70	97.30	95
01/07/08	alt training	15.00	0.70	99.80	98
01/24/08	alt training	14.50	0.60	98.52	100
02/07/08	alt training	15.00	0.60	103.52	105
02/24/08	camp	14.25	0.80	88.83	90
03/25/08	early season	14.75	0.70	97.30	98
04/07/08	early season	14.50	1.20	79.27	78
04/15/08	early season	14.25	0.80	88.83	90
05/03/08	camp	14.50	0.70	94.80	95
05/28/08	giro	15.00	0.80	96.33	95
07/16/08	tdf	15.25	0.40	114.55	115
avg		14.69	0.82	93.63	94
stdev		0.32	0.36	12.55	13

Table 2: Millar's data from Slipstream.

Now, let's take Landis' data from the UCI and do the same analysis that Slipstream offered as proof that their two aces are clean:

Date	event	HB	Reti	Offscore
03/03/05	Paris-nice	15.60	0.98	96.60
06/07/05	tdf	14.80	1.07	85.94
07/18/05	tdf	15.30	0.45	112.75
07/23/05	tdf	14.50	0.74	93.39
08/25/05	vuelta	13.90	0.46	98.31
03/05/06	Paris-nice	15.80	0.99	98.30
06/29/06	tdf	15.50	1.30	86.59
07/11/06	tdf	16.10	0.92	103.45
avg		15.19	0.86	96.92
stdev		0.73	0.30	8.76

Table 3: Landis' data from the UCI

As we see, there is nothing in the Landis data that is out of the range of normal; if anything, it is more normal than Millar's.

We note also the absence of other hematology data from the UCI, even though Landis has blood taken on other occasions during the tour. In particular, there are no blood values offered for after the one in question, and we're working from two data points and trying to find enlightenment.

Well, what was going on in the tour from one data point to the other? Not very much. It was pretty much a week off, as we see from the stage descriptions and the data reports that Allen Lim made at the time, and which are also in the exhibits.

stages	what	place	kj	moving w	pedal w	pedal wkg
Prologue - July 1: Strasbourg ITT, 7 km	tt	9	no data
Stage 1 - July 2: Strasbourg - Strasbourg, 183 km	sprint	46	3075	205	250	3.56
Stage 2 - July 3: Obernai - Esch-sur-Alzette (Luxembourg), 223 km	sprint	30	3934	195	256	3.67
Stage 3 - July 4: Esch-sur-Alzette - Valkenburg (Netherlands), 216 km	break	44	3969	222	276	3.96
Stage 4 - July 5: Huy (Belgium) - Saint-Quentin, 215 km	sprint	22	3760	209	256	3.67
Stage 5 - July 6: Beauvais - Caen, 219 km	sprint	34	3749	196	242	3.48
Stage 6 - July 7: Lisieux - Vitré, 184 km	sprint	59	3349	223	275	3.96
Stage 7 - July 8: Saint-Grégoire - Rennes ITT, 52 km	itt	2	no data
Stage 8 - July 9: Saint-Méen-le-Grand - Lorient, 177 km	break	37	3481	227	274	3.94
Rest Day - July 10: Bordeaux
Stage 9 - July 11: Bordeaux - Dax, 170 km	sprint	20	2624	203	234	3.42
Stage 10 - July 12: Cambo-les-Bains - Pau, 193 km	mtn stage	50	4377	246	309	4.45
Stage 11 - July 13: Tarbes - Val d'Aran/Pla-de-Beret (Spain), 208 km	mtn stage	3	5870	267	314	4.52
Stage 12 - July 14: Luchon - Carcassonne, 211 km	mtn stage	20	4199	244	285	4.16
average 1-9		30.3	3492	210	257	3.7
stdev 1-9		17.47	464	12.53	15.9	0.22

Things indeed got much harder right following - 5870 kj vs. 3500 average in all preceding. It's not unreasonable to think Landis was recovering from hard training before the tour during the first week, which might also account for some HCT rise independant of hydration issues.

From this, we offer the following thoughts.

1. Raw HCT values are problematic, as testified by Ashendon.
2. Landis' values for Hb and reticulocytes are pedestrian, or at least comparable to those of "clean" riders provided by Slipstream.
3. If one wants to draw any conclusions against Landis from the hematological data available, then one ought to wonder about Millar's first off-season value.
   

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