A method to model season of birth as a surrogate environmental risk factor for disease

When Do Tumours Develop? Neoplastic Processes Across Different Timescales: Age, Season and Round the Circadian Clock

While it is recognised that most, if not all, multicellular organisms harbour neoplastic processes within their bodies, the timing of when these undesirable cell proliferations are most likely to occur and progress throughout the organism's lifetime remains only partially documented. Due to the different mechanisms implicated in tumourigenesis, it is highly unlikely that this probability remains constant at all times and stages of life. In this article, we summarise what is known about this variation, considering the roles of age, season and circadian rhythm. While most studies requiring that level of detail be done on humans, we also review available evidence in other animal species. For each of these timescales, we identify mechanisms or biological functions shaping the variation. When possible, we show that evolutionary processes likely played a role, either directly to regulate the cancer risk or indirectly through trade-offs. We find that neoplastic risk varies with age in a more complex way than predicted by early epidemiological models: rather than resulting from mutations alone, tumour development is dictated by tissue- and age-specific processes. Similarly, the seasonal cycle can be associated with risk variation in some species with life-history events such as sexual competition or mating being timed according to the season. Lastly, we show that the circadian cycle influences tumourigenesis in physiological, pathological and therapeutic contexts. We also highlight two biological functions at the core of these variations across our three timescales: immunity and metabolism. Finally, we show that our understanding of the entanglement between tumourigenic processes and biological cycles is constrained by the limited number of species for which we have extensive data. Improving our knowledge of the periods of vulnerability to the onset and/or progression of (malignant) tumours is a key issue that deserves further investigation, as it is key to successful cancer prevention strategies.

Association between month of birth and melanoma risk: fact or fiction?

Background

Evidence on the effect of ultraviolet radiation (UVR) exposure in infancy on melanoma risk in later life is scarce. Three recent studies suggest that people born in spring carry a higher melanoma risk. Our study aimed at verifying whether such a seasonal pattern of melanoma risk actually exists.

Methods

Data from the population-based Cancer Registry Bavaria (CRB) on the birth months of 28 374 incident melanoma cases between 2002 and 2012 were analysed and compared with data from the Bavarian State Office for Statistics and Data Processing on the birth month distribution in the Bavarian population. Crude and adjusted analyses using negative binomial regression models were performed in the total study group and supplemented by several subgroup analyses.

Results

In the crude analysis, the birth months March-May were over-represented among melanoma cases. Negative binomial regression models adjusted only for sex and birth year revealed a seasonal association between melanoma risk and birth month with 13-21% higher relative incidence rates for March, April and May compared with the reference December. However, after additionally adjusting for the birth month distribution of the Bavarian population, these risk estimates decreased markedly and no association with the birth month was observed any more. Similar results emerged in all subgroup analyses.

Conclusions

Our large registry-based study provides no evidence that people born in spring carry a higher risk for developing melanoma in later life and thus lends no support to the hypothesis of higher UVR susceptibility during the first months of life.

Seasonal Variation in Skin Cancer Diagnosis

Purpose

Seasonality of skin cancer is well known, and it is influenced by a number of variables, such as exposure and personal characteristics, but also health service factors. We investigated the variations in the diagnosis melanoma skin cancer (MSC) and non-melanoma skin cancer (NMSC) during the year.

Methods

We analyzed incident cases recorded in the Umbria Regional Cancer registry from 1994 to 2010 (1745 cases of MSC, 50% females, and 15,992 NMSC, 41% females). The Walter–Elwood test was used to assess seasonal effects. Relative risks were analyzed using negative binomial regression and splines.

Results

Seasonality of MSC and NMSC was similar. Incidence peaks were observed in weeks 8, 24, and 43 (February, July, and October) and troughs in weeks 16, 32, 52, and 1 (August and December). Both NMSC and MSC cancers showed most elevated risks in autumn. A seasonal effect was present for trunk (p < 0.001) and absent for face cancers (p = 0.3).

Conclusion

The observed pattern of diagnoses presumably depends on health service factors (e.g., organization of melanoma days, reduced access to care in August and during Christmas holidays) and personal factors (e.g., unclothing in the summer and delays in seeking care). High incidence rates in autumn could also in part depend on a late cancer progression effect of UV exposure. More efforts should be placed in order to guarantee uniform access to care through the year.

Perinatal risk factors for acute myeloid leukemia

Infectious etiologies have been hypothesized for acute leukemias because of their high incidence in early childhood, but have seldom been examined for acute myeloid leukemia (AML). We conducted the first large cohort study to examine perinatal factors including season of birth, a proxy for perinatal infectious exposures, and risk of AML in childhood through young adulthood. A national cohort of 3,569,333 persons without Down syndrome who were born in Sweden in 1973-2008 were followed up for AML incidence through 2010 (maximum age 38 years). There were 315 AML cases in 69.7 million person-years of follow-up. We found a sinusoidal pattern in AML risk by season of birth (P < 0.001), with peak risk among persons born in winter. Relative to persons born in summer (June-August), incidence rate ratios for AML were 1.72 (95 % CI 1.25-2.38; P = 0.001) for winter (December-February), 1.37 (95 % CI 0.99-1.90; P = 0.06) for spring (March-May), and 1.27 (95 % CI 0.90-1.80; P = 0.17) for fall (September-November). Other risk factors for AML included high fetal growth, high gestational age at birth, and low maternal education level. These findings did not vary by sex or age at diagnosis. Sex, birth order, parental age, and parental country of birth were not associated with AML. In this large cohort study, birth in winter was associated with increased risk of AML in childhood through young adulthood, possibly related to immunologic effects of early infectious exposures compared with summer birth. These findings warrant further investigation of the role of seasonally varying perinatal exposures in the etiology of AML.

Perinatal and familial risk factors for brain tumors in childhood through young adulthood

Perinatal factors, including high birth weight, have been associated with childhood brain tumors in case-control studies. However, the specific contributions of gestational age and fetal growth remain unknown, and these issues have never been examined in large cohort studies with follow-up into adulthood. We conducted a national cohort study of 3,571,574 persons born in Sweden in 1973-2008, followed up for brain tumor incidence through 2010 (maximum age 38 years) to examine perinatal and familial risk factors. There were 2,809 brain tumors in 69.7 million person-years of follow-up. After adjusting for potential confounders, significant risk factors for brain tumors included high fetal growth [incidence rate ratio (IRR) per additional 1 SD, 1.04; 95% confidence interval (CI), 1.01-1.08, P = 0.02], first-degree family history of a brain tumor (IRR, 2.43; 95% CI, 1.86-3.18, P < 0.001), parental country of birth (IRR for both parents born in Sweden vs. other countries, 1.21; 95% CI, 1.09-1.35, P < 0.001), and high maternal education level (Ptrend = 0.01). These risk factors did not vary by age at diagnosis. The association with high fetal growth appeared to involve pilocytic astrocytomas, but not other astrocytomas, medulloblastomas, or ependymomas. Gestational age at birth, birth order, multiple birth, and parental age were not associated with brain tumors. In this large cohort study, high fetal growth was associated with an increased risk of brain tumors (particularly pilocytic astrocytomas) independently of gestational age, not only in childhood but also into young adulthood, suggesting that growth factor pathways may play an important long-term role in the etiology of certain brain tumor subtypes.

Perinatal and familial risk factors for acute lymphoblastic leukemia in a Swedish national cohort

BACKGROUND

Perinatal factors including high birth weight have been found to be associated with acute lymphoblastic leukemia (ALL) in case-control studies. However, to the best of our knowledge, these findings have seldom been examined in large population-based cohort studies, and the specific contributions of gestational age and fetal growth remain unknown.

METHODS

The authors conducted a national cohort study of 3,569,333 individuals without Down syndrome who were born in Sweden between 1973 and 2008 and followed for the incidence of ALL through 2010 (maximum age, 38 years) to examine perinatal and familial risk factors.

RESULTS

There were 1960 ALL cases with 69.7 million person-years of follow-up. After adjusting for potential confounders, risk factors for ALL included high fetal growth (incidence rate ratio [IRR] per additional 1 standard deviation, 1.07; 95% confidence interval [95% CI], 1.02-1.11 [P =.002]; and IRR for large vs appropriate for gestational age, 1.22; 95% CI, 1.06-1.40 [P =.005]), first-degree family history of ALL (IRR, 7.41; 95% CI, 4.60-11.95 [P<.001]), male sex (IRR, 1.20; 95% CI, 1.10-1.31 [P<.001]), and parental country of birth (IRR for both parents born in Sweden vs other countries, 1.13; 95% CI, 1.00-1.27 [P =.045]). These risk factors did not appear to vary by patient age at the time of diagnosis of ALL. Gestational age at birth, season of birth, birth order, multiple birth, parental age, and parental education level were not found to be associated with ALL.

CONCLUSIONS

In this large cohort study, high fetal growth was found to be associated with an increased risk of ALL in childhood through young adulthood, independent of gestational age at birth, suggesting that growth factor pathways may play an important long-term role in the etiology of ALL.

Seasonal incidence of hospital admissions for Stanford type A aortic dissection

The objective of this study was to test the hypothesis that there is seasonal variation in the incidence of Stanford type A aortic dissection (SA-AoD) among patients admitted to our cardiovascular surgical service. A sinusoidal logistic regression model was used to analyze event data for 6081 calendar days. A cyclic peak risk for SA-AoD was observed for calendar day 304 (p=0.019). The odds ratios for the 3- and 6-month window surrounding this peak were 1.6 (p=0.054) and 1.7 (p=0.0040), respectively. Our results suggest than a seasonal variation exists in the incidence of SA-AoD.

Season of birth and other perinatal risk factors for melanoma

BACKGROUND

Ultraviolet radiation (UVR) exposure is the main risk factor for cutaneous malignant melanoma (CMM), but its specific effect in infancy is unknown. We examined whether season of birth, a proxy for solar UVR exposure in the first few months of life, is associated with CMM in childhood through young adulthood.

METHODS

National cohort study of 3,571,574 persons born in Sweden in 1973-2008, followed up for CMM incidence through 2009 (maximum age 37 years) to examine season of birth and other perinatal factors.

RESULTS

There were 1595 CMM cases in 63.9 million person-years of follow-up. We found a sinusoidal pattern in CMM risk by season of birth (P=0.006), with peak risk corresponding to birthdates in spring (March-May). Adjusted odds ratios for CMM by season of birth were 1.21 [95% confidence interval (CI), 1.05-1.39; P=0.008] for spring, 1.07 (95% CI, 0.92-1.24; P=0.40) for summer and 1.12 (95% CI, 0.96-1.29; P=0.14) for winter, relative to fall. Spring birth was associated with superficial spreading subtype of CMM (P=0.02), whereas there was no seasonal association with nodular subtype (P=0.26). Other CMM risk factors included family history of CMM in a sibling (>6-fold) or parent (>3-fold), female gender, high fetal growth and high paternal education level.

CONCLUSIONS

In this large cohort study, persons born in spring had increased risk of CMM in childhood through young adulthood, suggesting that the first few months of life may be a critical period of UVR susceptibility. Sun avoidance in early infancy may play an important role in the prevention of CMM in high-risk populations.

Season of birth and risk of Hodgkin and non-Hodgkin lymphoma

Infectious etiologies have been hypothesized for Hodgkin and non-Hodgkin lymphoma (HL and NHL) in early life, but findings to date for specific lymphomas and periods of susceptibility are conflicting. We conducted the first national cohort study to examine whether season of birth, a proxy for infectious exposures in the first few months of life, is associated with HL or NHL in childhood through young adulthood. A total of 3,571,574 persons born in Sweden in 1973-2008 were followed up through 2009 to examine the association between season of birth and incidence of HL (943 cases) or NHL (936 cases). We found a sinusoidal pattern in NHL risk by season of birth (p = 0.04), with peak risk occurring among birthdates in April. Relative to persons born in fall (September-November), odds ratios for NHL by season of birth were 1.25 [95% confidence interval (CI), 1.04-1.50; p = 0.02] for spring (March-May), 1.22 (95% CI, 1.01-1.48; p = 0.04) for summer (June-August) and 1.11 (95% CI, 0.91-1.35; p = 0.29) for winter (December-February). These findings did not vary by sex, age at diagnosis or major subtypes. In contrast, there was no seasonal association between birthdate and risk of HL (p = 0.78). In this large cohort study, birth in spring or summer was associated with increased risk of NHL (but not HL) in childhood through young adulthood, possibly related to immunologic effects of delayed infectious exposures compared with fall or winter birth. These findings suggest that immunologic responses in early infancy may play an important role in the development of NHL.

Sinusoidal cox regression-a rare cancer example

Evidence of an association between survival time and date of birth would suggest an etiologic role for a seasonally variable environmental exposure occurring within a narrow perinatal time period. Risk factors that may exhibit seasonal epidemicity include diet, infectious agents, allergens, and antihistamine use. Typically data has been analyzed by simply categorizing births into months or seasons of the year and performing multiple pairwise comparisons. This paper presents a statistically robust alternative, based upon a trigonometric Cox regression model, to analyze the cyclic nature of birth dates related to patient survival. Disease birth-date results are presented using a sinusoidal plot with peak date(s) of relative risk and a single P value that indicates whether an overall statistically significant seasonal association is present. Advantages of this derivative-free method include ease of use, increased power to detect statistically significant associations, and the ability to avoid arbitrary, subjective demarcation of seasons.

Season of birth and risk for adult onset glioma

Adult onset glioma is a rare cancer which occurs more frequently in Caucasians than African Americans, and in men than women. The etiology of this disease is largely unknown. Exposure to ionizing radiation is the only well established environmental risk factor, and this factor explains only a small percentage of cases. Several recent studies have reported an association between season of birth and glioma risk. This paper reviews the plausibility of evidence focusing on the seasonal interrelation of farming, allergies, viruses, vitamin D, diet, birth weight, and handedness. To date, a convincing explanation for the occurrence of adult gliomas decades after a seasonal exposure at birth remains elusive.

The impact of maternal birth month on reproductive performance: controlling for socio-demographic confounders

Based on a 1900 census sample of 34,166 post-reproductive females (> or =45 years), the birth month effect was put to the test, for both lifetime fertility as well as child survival, controlling for maternal birth cohort (1826-1835, 1836-1845, 1846-1855), Duncan's SEI, urbanity, nativity, literacy and marital duration. Testing for potential cohort effects did not indicate a temporal trend in fertility by maternal birth month (seasonal Mann-Kendall test, p=0.578), while a minute increase in offspring survival was detected (p<0.001, Sen's estimator of slope=0.02, 95% CI=0.02 to 0.03). Further analyses of the maternal birth month effect on child survival were therefore seized. For lifetime fertility, ANOVA results indicated that maternal birth month was a major predictor for total offspring count (F11, 33606=1809.0, p<0.001), accounting for 37.2% of the total variability. In addition to main effects, a statistically significant interaction effect was observed (F538, 33606=2.2, p<0.001), with a corresponding effect size of eta2=0.40. Planned contrasts revealed that birth-month-specific differences in fertility achieved statistical significance (F11, 31798=1712.9, p<0.001), while post-hoc multiple comparisons for literacy and nativity displayed an inverse relationship with fertility, which meets demographic expectations. Controlling for all factors of interest, models of cohort-specific offspring counts (independent ANOVAs for 1826-1835: F157, 3467=26.3, p<0.001; 1836-1845: F182, 10299=75.5, p<0.001; 1846-1855: F199, 19859=137.9, p<0.001) indicated that women born in the first half of the year (particularly, January, February, April and May) achieved above-average parity, while those born in the latter half (namely, July, October, November and December) displayed markedly lower fertility averages. These monthly disparities are in line with previous observations and appear to be linked to seasonal optimal ripening of the oocyte or seasonal preovulatory over-ripeness ovopathy (Jongbloet, 1992).