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Letters To The Editor |
Memorial Sloan-Kettering Cancer Center, New York, New York, USA
Correspondence: Correspondence: Peter B. Bach, M.D., Memorial Sloan-Kettering Cancer Center, 1275 York Ave., New York, New York 10065, USA.
Received February 11, 2008; accepted for publication February 12, 2008.
Disclosure: This article discusses the off-label use of computed tomography devices (manufactured by General Electric and others) for screening. No potential conflicts of interest were reported by the author.
I am writing about the article called "CT screening for lung cancer: Update 2007," which appeared in the January 2008 issue of The Oncologist [1]. The article contains numerous problematic and unsubstantiated assertions, in many cases inappropriately coupled to references that are either unrelated to, or contradictory to the point made by the authors.
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2. The authors present the term "curability rate," although it has no concrete meaning in epidemiology. Their reference is to Martini and colleagues, where the concept of "curability rate" does not appear [3].
3. The authors present, in Figure 1, estimates of "cure rates," a concept that is not found in conventional epidemiology. They cite as their source for the cure rate estimates the "American Cancer Society Facts and Figures: 2006." Yet, no cure rates appear in that report.
4. The authors claim that there is a distinction between "baseline" and "subsequent" rounds of screening. They cite Morrison [4]. In that article, no such distinction appears. In fact, Morrison focuses on a hypothetical scenario in which only a single round of screening (i.e., only the baseline round) has been performed.
5. The authors assert that "length bias" only affects the first round of screening, again referencing Morrison [4]. Morrison's article explicitly contradicts the authors on this point, noting that length bias cannot be sequestered to certain patients in a single-arm noncomparative design (such as Early Lung Cancer Action Project [ELCAP]). The Morrison article more generally critiques the type of design pursued by ELCAP, while implicitly endorsing randomized trials such as the National Lung Screening Trial (NLST). He states that "the observed case-fatality (the ELCAP endpoint) is not an appropriate measure of the beneficial effect of screening. Outcome evaluation of a screening programme is best carried out by comparison of mortality rates in the screened population with those in another otherwise comparable unscreened population (i.e., the NLST design)."
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2. They state that the "median follow-up time [in the NLST] will be 4 years in 2009." The NLST website lists enrollment dates ranging from 2002 to 2004. Thus, follow-up by 2009 will range from 5 years (i.e., 2004–2009) to 7 years (i.e., 2002–2009), and the median will lie somewhere between 5 and 7 years.
3. The authors claim that the cumulative mortality rate declined in years 5 and 6 of a study examining computed tomography screening [7]. The study referenced contains no such finding. In that study, the cumulative number of events over time (i.e., deaths from lung cancer), not the cumulative mortality rate, was examined.
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2. The authors report that, in I-ELCAP, "those who were in stage I who had no treatment all died from lung cancer," referencing their own work [9]. As noted by Yee and Lynch, the cause of death of these eight subjects was not specified in the paper that the authors reference [10].
On a potentially related point, the authors state that Figure 11 displays a comparison of individuals who did and did not receive treatment for their lung cancer. The graph leaves open some questions. For instance, if these data are meant to reflect the outcomes of the 8 untreated subjects the authors have frequently referenced in their publications, then why are there 13, not 8, events in the untreated group? Also, why is there no censoring in the untreated group (as evidenced by the fact that there are equal size steps and no tick marks in the Kaplan-Meier curve), while over the same period of follow-up, there is abundant censoring among the group of treated subjects? It would be helpful to readers if the authors would address these questions, and more generally describe the sources of data used to construct the two curves in this figure.
The evaluation of cancer screening approaches is complex, and involves many subtle epidemiologic concepts that can seem counterintuitive.
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