Re: "Reproductive factors and breast cancer"

The impact of patient characteristics and lifestyle factors on the risk of an ipsilateral event after a primary DCIS: A systematic review

Objective

The majority of ‘low-risk’ (grade I/II) Ductal Carcinoma In Situ (DCIS) may not progress to invasive breast cancer during a women’s lifetime. Therefore, the safety of active surveillance versus standard surgical treatment for DCIS is prospectively being evaluated in clinical trials. If proven safe and selectively implemented in clinical practice, a significant group of women with low-risk DCIS may forego surgery and radiotherapy in the future. Identification of modifiable and non-modifiable risk factors associated with prognosis after a primary DCIS would also enhance our care of women with low-risk DCIS.

Methods

To identify modifiable and non-modifiable risk factors for subsequent breast events after DCIS, we performed a systematic literature search in PUBMED, EMBASE and Scopus.

Results

Six out of the 3870 articles retrieved were included for final data extraction. These six studies included a total of 4950 patients with primary DCIS and 640 recorded subsequent breast events. There was moderate evidence for an association of a family history of breast cancer, premenopausal status, high BMI, and high breast density with a subsequent breast cancer or further DCIS.

Conclusion

There is a limited number of recent studies published on the impact of modifiable and non-modifiable risk factors on subsequent events after DCIS. The available evidence is insufficient to identify potential targets for risk reduction strategies, reflecting the relatively small numbers and the lack of long-term follow-up in DCIS, a low-event condition.

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Need for risk management strategies for untreated DCIS patients.

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Limited evidence for association between lifestyle factors and prognosis after DCIS.

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Positive family history, premenopausal status, high breast density associated with prognosis.

Joint effects on cancer risk of age at childbirth, time since birth and attained age: circumventing the problem of collinearity

In previous studies of female cancer risk, we introduced a new method for circumventing the problem of collinearity in age-adjusted analysis of the joint effects of age at birth and time since birth. The basic idea was to estimate the pure age effect considering nulliparous women, assuming that the age effect is common to all women. However, risk estimates for attained age obtained in this manner may suffer from bias, in particular in small data sets, which may in turn influence risk estimates for reproductive factors among parous women. Certain factors possibly affecting cancer risk among nulliparous women only, for instance biological infertility, might also introduce bias. The purpose of this paper is to investigate the accuracy of risk estimates obtained by the joint approach, and to reveal the extent of bias in traditional separate age-adjusted analyses of age at birth or time since birth among parous women. Results are based on analyses of simulated data sets reflecting reproductive and demographic characteristics of a cohort of 1.1 million Norwegian women. Incidence rate ratios are calculated in Poisson regression analyses of person-years at risk. Our simulations show that the joint analysis in general yields unbiased risk estimates, but the number of cases must be rather high to achieve reliable results. Risk estimates from separate analyses can be seriously biased, although the amount of bias depends on the strength and direction of associations with cancer risk. With a total of 5500 cancer cases, the estimators for age at last birth and time since last birth were 13-78 per cent and 5-66 per cent more efficient in the joint than in the separate analysis, respectively. Significance levels were close to the nominal 5 per cent in the joint analysis, but about twice as high in the separate analysis. Adding an effect of biological infertility on cancer risk among nulliparous women, without taking it into account in the analyses, did not seriously affect risk estimates in the joint model.