Cyclic patterns of incidence rate for skin malignant melanoma: association with heliogeophysical activity*

Background: Our previous studies revealed cyclicity in the incidence rate of skin malignant melanoma (SMM; ICD9, Dx:172) in the Czech Republic (period T=7.50~7.63 years), UK (T=11.00 years) and Bulgaria (T=12.20 years). Incidences compared with the sunspot index Rz (lag-period dT=+2, +4, +6, +10 or +12 years) have indicated that maximal rates are most likely to appear on descending slopes of the 11-year solar cycle, i.e., out of phase. We summarized and explored more deeply these cyclic variations and discussed their possible associations with heliogeophysical activity (HGA) components exhibiting similar cyclicity. Methods: Annual incidences of SMM from 5 countries (Czech Republic, UK, Bulgaria, USA and Canada) over various time spans during the years 1964~1992 were analyzed and their correlations with cyclic Rz (sunspot number) and aa (planetary geomagnetic activity) indices were summarized. Periodogram regression analysis with trigonometric approximation and phase-correlation analysis were applied. Results: Previous findings on SMM for the Czech Republic, UK and Bulgaria have been validated, and cyclic patterns have been revealed for USA (T=8.63 years, P<0.05) and Canada (Ontario, T=9.91 years, P<0.10). Also, various ‘hypercycles’ were established (T=45.5, 42.0, 48.25, 34.5 and 26.5 years, respectively) describing long-term cyclic incidence patterns. The association of SMM for USA and Canada with Rz (dT=+6 and +7 years, respectively) and aa (dT=−10 and +9 years, respectively) was described. Possible interactions of cyclic non-photic influences (UV irradiation, Schumann resonance signal, low-frequency geomagnetic fluctuations) with brain waves absorbance, neuronal calcium dynamics, neuro-endocrine axis modulation, melatonin/serotonin disbalance and skin neuro-immunity impairment as likely causal pathways in melanoma appearance, were also discussed. Conclusion: The above findings on cyclicity and temporal association of SMM with cyclic environmental factors could not only allow for better forecasting models but also lead to a better understanding of melanoma aetiology