1 Division of Clinical Trials and Epidemiological Sciences, National Cancer Centre, Singapore
2 Skaraborgsinstitutet, Skövde, Sweden
3 Centre for Molecular Epidemiology, National University of Singapore, Singapore
4 Medical Statistics Unit, School of Health and Related Research, University of Sheffield, Sheffield, United Kingdom
Correspondence to Fei Gao, Division of Clinical Trials and Epidemiological Sciences, National Cancer Centre, 11 Hospital Drive, Singapore 169610 (e-mail: ctegfe{at}nccs.com.sg).
Received for publication December 29, 2004. Accepted for publication May 13, 2005.
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ABSTRACT |
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leukemia, lymphoblastic, acute; seasons
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INTRODUCTION |
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The first published studies on the seasonality of leukemia appear to be from Belgium (7, 8
), which reported a NovemberFebruary peak in acute leukemia. Since then, numerous reports (we identified more than 30 in a systematic literature search) from 15 countries have specifically investigated the seasonality of ALL.
While many of these studies have identified an obvious seasonal pattern, others have not found a significant seasonal variation. For example, for England and Wales combined, a summer peak was noted in two age groups (019 and 2044 years) in studies from the early 1960s (9, 10
), while one study some 30 years later showed no such pattern (11
).
Inconsistency between results may itself be informative, perhaps reflecting various levels of between-population heterogeneity and different patterns of seasonality induced by possible causative agents. It is also possible that seasonality may be more pronounced within subtypes of leukemia or, for example, a particular locality. There was little evidence of seasonality in a national data set from Great Britain (England, Scotland, and Wales), but seasonality (summer: MayOctober) was evident in one regional data set from the West Midlands, England (12). The authors concluded that "further work on seasonality needs more sophisticated analysis, controlling for broad geographical heterogeneity" (12
, p. 678). However, to our knowledge, no formal synthesis of published reports has been attempted to date. As a consequence, the etiology of leukemia in this respect, in both children and adults, still remains essentially undetermined.
One study, reporting some 20 years ago, examined in particular the influence of latitude on presentation of ALL for US subjects aged 019 years by using monthly data from the Surveillance, Epidemiology, and End Results (SEER) Program and from an independent survey of a 57-county study area in the eastern half of Nebraska (13). The authors examined the seasonal variation in ALL by using periodic regression of monthly rates; they noted up to three peaks (April, August, and December) in registries north of 40°N and the same, but in different months (February, July, and October), for the southern counterparts. They commented that "the observed peaks in monthly ALL risk coincide with seasonal elevations in the rates of allergenic and infectious diseases, elements of which are capable of promoting lymphocytic proliferation and transformation" (13
, p. 915).
The SEER Program records, and makes available to researchers, individualized data on each case from 11 registries in the United States over a range of latitudes from 21.18°N to 41.36°N. We have the same detail for cases of ALL from part of western Sweden (latitude 58.24°N) and the whole of Singapore (latitude 1.16°N). In these two registries, the actual day is recorded and not just the month, as with SEER.
The purposes of our study were to search for a seasonal component in the presentation of ALL in the registry data from these three countries, to determine the influence of latitude (if any), and to investigate the role of subject age and gender.
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MATERIALS AND METHODS |
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Data
Singapore (latitude 1.16°N, longitude 103.51°E).
We used Singapore Cancer Registry data that included all cases of cancer occurring in citizens and permanent residents of the island (population 3.5 million) over the period 19681999. Disease classification follows the International Classification of Diseases, Ninth Revision. In addition, age, gender, ethnic group, date of birth, place of birth, and date of diagnosis are available on an individual case basis. A total of 941 ALL cases were registered for that time period. Two cases were excluded from our analysis of age (for one, only the year was recorded; for the other, the diagnosis was recorded a few days earlier than the birth).
United States (latitude 21.18°N47.36°N, longitude 72.41°W157.52°W).
The SEER Program of the National Cancer Institute records data from 11 cancer registries over a wide geographic area in the United States, and we used the data for the time period 19731999. The SEER locations included the island of Hawaii and the following mainland areas: metropolitan Atlanta, Georgia; Connecticut; metropolitan Detroit, Michigan; Iowa; New Mexico; the San Francisco-Oakland Standard Metropolitan Statistical Area, California; Seattle, Washington; Utah; and Los Angeles and San Jose-Monterey, California. Seattle contributed data for the years 19741999, metropolitan Atlanta for 19751999, and Los Angeles and San Jose-Monterey for 19921999 only.
SEER collects patient-specific information on tumor site, histology, gender, age, ethnicity, and date (month and year only) of diagnosis from all residents diagnosed with cancer in collaborating states or localities. Data for 9,158 ALL patients were collected, but 38 cases were excluded from our seasonality analysis because their month of diagnosis was not available.
Western Sweden (latitude 58.24°N, longitude 13.50°E).
Individual dates of each arrival at the hospital for any disease were available for part of the West Götaland Region in western Sweden from 1977 to 1994 (the population of the catchment area was 270,000 in 1995), and we used these data. Disease classification follows a Swedish version of the International Classification of Diseases, Eighth Revision before 1987 and a Swedish version of the International Classification of Diseases, Ninth Revision thereafter. For our purposes, the date of admission to the hospital was considered the date of diagnosis. In addition, age and gender are available on an individual-case basis.
A total of 81 cases were diagnosed with ALL, and we reviewed their diagnoses noted at each visit. As a consequence, two cases were excluded because, on most occasions, their diagnosis was recorded as lymphosarcoma or reticulosarcoma but only once as ALL. Corrections to the date of presentation regarding ALL were made for seven cases.
Statistical analysis
Data from each calendar year were first standardized to 365 days and were then converted to an angle between 0° and 360°. We illustrate these data graphically in a rose diagram format (figure 1), where each petal is of a "standard" month or 360/12 = 30°. The segments are ordered from January to December (clockwise) starting from due north. In these diagrams, the square root of monthly totals is used to preserve equal areas for each unit of frequency, as in a conventional histogram.
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RESULTS |
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To some extent, the rose diagram format obscures the shape of the distribution over the year; therefore, we plotted data for Singapore, Hawaii, and Sweden again in a (double-year) histogram format (figure 2). Superimposed on these plots are the corresponding von Mises distributions. It is clear from this figure that the von Mises distribution reasonably describes the seasonal pattern for these cases and suggests that the strength of the peak is increasing from Singapore to Sweden. However, a more detailed examination of the values of in all of the intermediate-latitude registries (table 2) was far from suggestive of a general pattern. Furthermore, there was no clear evidence of any systematic change in the estimated date of peak diagnosis over the changing latitudes.
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The 13 estimated peak dates ranged over 10 months of the year from January 3 in western Sweden to October 23 in San Jose-Monterey, southern California (figure 3). Ten of the 11 peak dates in the United States were located on the arc between Singapore and Sweden, suggesting a weak latitude effect. Only the date for San Jose-Monterey, California, was found within the opposite arc. However, a plot of the estimated peaks, with corresponding 95 percent confidence intervals, by increasing latitude showed no clear, systematic pattern. Furthermore, all but one of the corresponding estimates of were less than 0.12 (small), implying little evidence of seasonality in most registries except for western Sweden (
= 0.458). The size of the symbol "" representing peak date of diagnosis is proportional to
, except that those peak dates with
< 0.1 are labeled "," and the length of the vertical lines, one for each location, represents the 95 percent confidence interval for the peak date. Because the confidence intervals may "wrap around" December 31 and January 1, different symbols are used to indicate the lower ("
") and upper ("
") confidence limits, which indicate the direction to go along the arc from that point to find the peak.
For the places from Singapore to San Francisco, at a latitude of <40°Nthe cutpoint used previously for comparison purposes (13)the estimated peaks ranged from April to October (table 2, figure 3). For the locations at a latitude of
40°N, from Utah to western Sweden, the estimated peaks ranged from January to February (winter) except in Seattle, where the latitude is 47.36°N and the estimated peak was July 19 (summer).
In the broad age categories of 019 and 20 years, there appeared to be no trend across the latitudes for children or adults (table 3, figure 4). Although the values of
tended to increase once the subjects, within each registry, were divided into these two age groups, suggesting a difference between the younger and older cases in the corresponding peak dates of diagnosis, no systematic pattern emerged of one age group experiencing a peak earlier in the year than another.
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There were no systematic patterns within or between genders across the registries (table 4, figure 5). Furthermore, no association between peak date of diagnosis and longitude was observed.
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DISCUSSION |
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For this study, we were able to obtain individualized data from western Sweden, the Singapore Cancer Registry, and the SEER database of 11 registries in the United States for a total of 10,599 cases over the years 19681999.
Singapore (latitude 1.16°N) is very close to the equator; therefore, if there was indeed an influence of season on the date of peak diagnosis of ALL, it should be weak in this country because there are no marked seasonal weather patterns. In contrast, western Sweden (latitude 58.24°N) has seasons that differ markedly from winter, with few daylight hours and temperatures below 0°C, to summer, with almost continual daylight and temperatures ranging from 25°C to 30°C. Thus, one might expect to identify a seasonal pattern for ALL if one exists, and western Sweden was indeed the only location of the 13 studied in which a statistically significant peak (January 3) was identified. However, the sample size was small (79 cases in total), so there is a danger of a spurious finding especially because there are regions covered by the US registries where the climate (but not day length) is similar to that of western Sweden, but no peaks were established there. For the US registries as a whole, and despite a wide range of latitudes extending from Hawaii to Seattle (a difference of 26.18°), there is little evidence to suggest a climatic effect.
Apart from the Swedish data just noted, in which the peak was confined to young males, there was little other evidence to suggest that, within specific age groups, strong peaks are present or that there is any systematic trend across ages regarding diagnosis, even when age was categorized into groups ranging from 02 years to the elderly. There was also little evidence of any gender effect in any location or any suggestion of a consistent effect across locations.
Our failure to find any such influences may have resulted from not studying registries in more regions of the world, weaknesses in the analytical approach, and (nonrecorded) etiologic factors playing a major role and obscuring any latitude, longitude, gender, and age effects. Thus, we are aware that we were not able to perform an "individual-case," systematic overview of the ALL studies (we identified more than 30) that have been conducted. Also of concern is the loss of statistical sensitivity because the SEER data provide only the month and not the day of diagnosis. Were the precise days available, then angular regression models (18) could be used to investigate the associations rather than the somewhat descriptive approach that we had to use. Further work is also required to confirm (or otherwise) the utility of the von Mises distribution as an adequate description of seasonality; once more, only precise dates would allow a thorough investigation.
For some diseases, seasonal variation in known or unknown precipitating factors will depend on climate and a range of population characteristics (19), and these in turn will induce seasonal patterns in the disease itself. However, apart from gender and age, unavoidably all of the possible precipitating factors are expressed merely through the latitude (and longitudes) of the individual registry locations. These clusters will clearly obscure the influence of, for example, case-specific socioeconomic status and some environmental factors (20
, 21
) that have been linked to the risk of developing ALL.
Our findings are consistent with a report concluding that there was no seasonality in the United States across all ages (22) but not with a later reanalysis of these same data (13
). This reanalysis identified up to three peaks in each of the nine locations studied for subjects aged 019 years. Our view is that this result more likely reflects the statistical methodology applied to data that are essentially random (but grouped into 12 bins), so that a trigonometric model with many parameters will mirror the vagaries of such a toothy distribution and not reflect the smoothed (and more likely) pattern of a uniform distribution over the year. We could not substantiate the claimed summer peak in the diagnosis of ALL in children (23
).
In contrast, for western Sweden, the significant peak in winter (early January) is close to the peak of onset reported for Capetown, South Africa (winter: JuneAugust) (24) and the peak of symptoms occurring in Shiraz, Iran (winter: October) (5
). However, this information differs from the summer peaks reported for onset in England and Wales (9
, 10
) and diagnosis in England (6
). These contrasting results for ALL may be due to the different statistical approaches that have been used, the different age groups chosen for analysis and reporting, or the different date of "onset" of ALL considered, although the delay between clinical symptoms in children and diagnosis is not likely to be great (4
).
The seasonality observed in western Sweden (if it could be firmly established) may, in any event, be related more to precipitating than to etiologic factors. For example, eventual cases might first present as a result of lowered immunity to infections; these may be common in winter or summer, depending on their type and their ALL being detected as a result. The overall health care system in Sweden is ranked highly (25) and provides relatively open access to care. Consequently, the peak of moderate magnitude in January may reflect post-Christmas and New Year festivities delaying self-referral and not the presence of an etiologic determinant.
Despite investigation of seasonal patterns in the presentation of ALL, as indicated by the date of diagnosis, over a range of latitudes from 1.16°N to 58.24°N, there is no clear message with respect to their interpretation. Nevertheless, patterns may have emerged if the "date of first symptom" had been recorded and studied, because, for example, a significant seasonal variation for Hodgkin's disease has been reported in this date but not in the date of diagnosis (26). Thus, this and other studies (27
, 28
) suggest that date of first symptom versus date of diagnosis more closely reflects the event that precipitates the clinical onset of disease. However, the induction period of ALL is sufficiently short, so a similar seasonal pattern should be observed for date of first symptom and date of diagnosis (27
). Although the interval is indeed short for the majority of pediatric ALLs, it has been claimed that ALL can be clinically silent for months or even years in some cases (4
). Such late cases are likely to dilute seasonal patterns.
A similar lack of consistent findings has been reported for other forms of leukemia with respect to a peak in the date of diagnosis. For example, a significant summer peak was reported for ALL but not for acute myeloid leukemia in the United States (23), while a significant autumn peak (November) for ALL but (bimodal) peaks for acute myeloid leukemia in winter and spring were noted in Shiraz, Iran (5
). In contrast, no clear evidence of seasonality for ALL, acute myeloid leukemia, and chronic myeloid leukemia was reported from England and Wales (11
), but none of these studies have been analyzed on a case-by-case basis.
Given the small numbers of cases from western Sweden, no firm evidence from the United States, and the expected absence in Singapore, any suggestions for peak seasonality of diagnosis could all be ascribed to chance variations. Likewise, the corresponding degree of seasonality reported in other studies may be enhanced (or obscured) by local referral characteristicseven leading to a false indication of an underlying climatic component.
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APPENDIX |
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Here, represents the angle, over a range of 0360° (or 02
radians), that can be equivalent to the date of diagnosis within a year. For example, if this date is February 28, 2004, then
= 360 x (31 + 28)/366 = 58.03° or 1.0123 radians; if it is February 28, 2005, then
= 360 x (31 + 28)/365 = 58.19° or 1.0151 radians. After converting each date to an angular day for the N subjects concerned, the peak µ is estimated as follows: First, calculate
and note whether each is less than or greater than 0. Next, calculate µ0 = arctan (S/C), which gives a value in degrees (or radians) of between 90° and 90°. Finally, the estimated peak angle µ is equal to 1) µ0 itself, if S > 0 and C > 0; 2) µ0 + 180°, if C < 0 irrespective of the value of S; or 3) µ0 + 360°, if S < 0 and C > 0. Once µ is calculated in degrees, it can be converted to a date in a standard year of 365 days.
The second parameter of the von Mises distribution is termed the concentration parameter and relates to the inverse of the variance of the distribution. The algebraic expression for the estimate of
from the data is complex. However, a very good approximation is given by the following:
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R is the estimated magnitude of the peak at the date identified and takes values of 01. The larger the value of R, the stronger the peak identified at µ.
It can be shown that when is large, suggesting a strong peak, the shape of the von Mises distribution is close to that of a Normal distribution, with the mean at µ and a standard deviation equal to
In contrast, for small
, the von Mises distribution tends to the uniform distribution and is spread evenly over the whole 360°. This situation is clearly indicative of no peak in date of diagnosis being present.
A formal test of the null hypothesis, = 0, is made by referring the value of M = 2NR2 to the chi-squared distribution with 2 degrees of freedom.
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ACKNOWLEDGMENTS |
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Conflict of interest: none declared.
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References |
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