Dr. Armon, a leader in ALS research, poses questions probing the
validity of my study that first supported the significant cluster of ALS
in young Gulf War veterans. [1] Given the rarity of real ALS clusters and
thus their research importance, such dialogue is useful.
The method I used to test for an increase in ALS above the expected
rate was the standardized morbidity ratio (SMR). [6] Far from an
“elaborate,” “unvalidated” methodology, the SMR is a time-honored
epidemiologic method, used in over 2,000 papers listed in MEDLINE since
the early 1970s. What may have appeared as novel in my on-line appendix
[7] was but the detailed mathematical documentation of how I performed the
usual steps of an SMR calculation with the Gulf War data.
In an earlier draft of my paper, I included SMRs comparing observed to
expected ALS incidence calculated from both published studies of age-
specific incidence and nationwide mortality data. Contrary to Dr. Armon’s
prediction, SMRs from the two approaches agreed closely. The journal’s
peer reviewers argued, however, that the published incidence studies
contained too much sampling variation in younger age groups to justify
regression-derived estimates of mean age-specific incidence rates (see
Figure A1-D [7]), and so I deleted the SMRs calculated from the published
incidence studies. Dr. Armon’s suggestion to compare only to the one
published incidence study with the highest ALS rates at young ages, [3]
while ignoring others with lower rates, [7] fails to consider the extreme
sampling variation in those studies. One cannot “cherry-pick” just the
study with the highest rates.
Dr. Armon’s attribution of low incidence rates to less complete case
ascertainment in older studies is not supported by the data. In the 13
incidence studies I cited, [7] there is no correlation between year of
publication and ALS rates in men <50 years old (p = 0.34). For
example, compare recent U.S. studies [3] and [8].
To make population mortality rates better approximate incidence
rates, I adjusted age-specific mortality rates by average duration from
diagnosis to death, a firmly established interval. [9,10] This reduced
the SMRs. How long Gulf veterans with ALS will survive on ventilatory
support is irrelevant to this adjustment.
Rate estimates in young age groups from published incidence studies
are imprecise due to small numbers, but nationwide mortality data, which
contain large numbers at young ages, provide highly precise estimates. [7]
Most importantly, the significant ALS cluster identified by my study
was confirmed by Horner et al. using fundamentally different methodology.
[5]
References
6. Breslow NE, Day NE. Statistical methods in cancer research. Vol 2.
the design and analysis of cohort studies. Lyon, France: International
Agency for Research on Cancer. 1987: 65-72, 91-103.
7. Haley RW. Statistical appendix: estimation of expected incidence
of ALS. Neurology. 2003;61:750-6. Available on-line at:
http://www.neurology.org/content/vol61/issue6/images/data/750/DC1/Haley_supplemental_data.doc.
8. Annegers JF, Appel S, Lee JR, Perkins P. Incidence and prevalence
of amyotrophic lateral sclerosis in Harris County, Texas, 1985-1988. Arch
Neurol 1991; 48:589-593.
9. Magnus T, Beck M, Giess R, Puls I, Naumann M, Toyka KV. Disease
progression in amyotrophic lateral sclerosis: predictors of survival.
Muscle Nerve 2002; 25:709-714.
10. Chio A, Mora G, Leone M et al. Early symptom progression rate is
related to ALS outcome: a prospective population-based study. Neurology
2002; 59:99-103.