Mæhle et al. BMC Cancer 2010, 10:115 http://www.biomedcentral.com/1471-2407/10/115 Table 1 Number of breast cancer patients and patient characteristics in Trondheim and in Bergen Age (years) Birth length (cm) Birth weight (g) Ponderal index (kg/m3) Positive lymph node status Tumour diam. (cm) Number of breast cancer deaths Number of deaths from other causes Numbers lost to follow-up Follow-up time (months) No 165 165 164 164 138 110 29 5 0 165 Bergen Mean (SD) 52.1(11.4) 50.3 (1.62) 3486 (466) 27.3(2.69) 39% 2.3 (1.3) Range 27-83 46-54 2310-4900 17.1-34.3 0.5-8.0 No 166 166 165 165 154 133 58 14 0 166 Trondheim Mean (SD) 49.0 (10.3) 50.4 (1.91) 3436 (493) 26.8 (2.2) 47% 3.2 (1.9) Table 2 Hazard ratios (with 95% confidence intervals) of dying from breast cancer according to birth length, birth weight and ponderal index, with adjustment for place of birth and year of diagnosis Birth length Birth weight Ponderal index 1st quintile 2-4th quintiles 5th quintile N = 331 N = 329 1.0 (reference) 1.0 (reference) 1.08 (0.61,1.88) 1.08 (0.62,1.88) 1.83 (1.03,3.25) 1.16 (0.59,2.29) p-value linear trend p = 0.03 p = 0.59 Table 3 Hazard ratios (with 95% confidence intervals) of dying from breast cancer according to birth length and ponderal index Birth length 2-4th quintiles (48-52 cm) 5th quintile (> 52 cm) Ponderal index 1st quintile 2-4th quintiles 5th quintile 1st quintile (< 48 cm) 1.0 (reference) 1.0 (reference) 1.0 (reference) A N = 329 1.07 (0.61, 1.86) 1.84 (1.03, 3.28) 0.93 (0.54, 1.61) 0.80 (0.39, 1.65) B N = 293 1.15 (0.64, 2.08) 1.88 (1.03, 3.45) 0.82 (0.47, 1.43) 0.65 (0. 30, 1.38) 1.0 (reference) 1.0 (reference) 1.0 (reference) N = 329 1.0 (reference) 1.01 (0.59,1.74) 0.81 (0.39,1.67) p = 0.11 C N = 246 1.21 (0.61, 2.39) 2.17 (1.06, 4.45) 0.95 (0.50, 1.83) 0.91 (0.38, 2.20) Estimates adjusted for place of birth and year of diagnosis (A), with additional adjustment for lymph node status (B) and tumour diameter (C). analysis C, 246 patients were included. The results show that survival among patients within the highest quintile of birth length remained consistently poorer than for patients in lower categories of birth length, also after taking lymph node status and tumour diameter into account (Table 3). Detailed correlation analyses showed Page 3 of 4 Range 30-73 46-54 2320-4800 18.6-32.2 0-8.0 142 4-487 125 5-354 no correlations between birth length and tumour dia- meter (-0.056), and between birth length and lymph node status (-0.017). Discussion and Conclusions We have studied whether birth size is associated with the prognosis of breast cancer patients, and found that women with high birth length had poorer outcome than women with shorter length at birth. Specifically, women who were 52 cm or longer at birth had nearly twice the risk of dying from breast cancer compared to women who were shorter than 48 cm at birth. This association was not reduced after taking ponderal index, lymph node status, tumour diameter and place of birth into account. We found no association with survival related to birth weight or ponderal index. In prognostic studies, predictors are usually assessed at the time of diagnosis, and patients are subsequently followed up in relation to outcome, which is typically time to death (survival) from the specified disease under study. In this study, however, measurements of birth size were made decades before the diagnosis (on average 50 years earlier). In the literature, there is no evidence that indicators of birth size have any influence on the prognosis of breast cancer once the diagnosis is estab- lished, and previously, no study has assessed survival of breast cancer related to birth size. However, given the magnitude of the association that we observed for birth length, sources of bias that may explain the finding should be carefully considered. It is conceivable that better prognosis in one subgroup of patients could be due to better treatment quality. Birth length is positively correlated with adult height, and hence with socioeconomic status [10,11]. If quality of care and treatment followed a socio-demographic gradient, women with high birth length would be expected to receive better treatment. In that scenario the higher risk of dying from breast cancer related to