Our study shows that young Asian breast cancer patients treated with BCT have higher rates of local recurrence and breast cancer death than other patients. While previous investigations have examined the effect of age in a dichotomous fashion using arbitrary definitions of youth, our results showed no apparent threshold effect of age on breast cancer control or survival.
Outcomes of patients with breast cancer are influenced by the complex interactions between tumor biology, host biology and treatment received. Many aspects of tumor biology that influence treatment responses and outcomes have been clearly established, including (1) the stage of disease at presentation, (2) tumor grade, (3) the presence of hormone receptors, and (4) HER2 overexpression. Although many of these factors are associated with a patient’s age and account for a significant portion of the variability in outcomes, age still remains a significant, independent prognostic factor [23].
The actual mechanism through which age influences outcomes is unknown. Recent studies have shown that breast cancer in young patients is replete with processes related to immature mammary epithelial cells (luminal progenitors, mammary stem, c-kit, and Receptor activator of nuclear factor kappa-Β ligand RANKL), growth factor signaling and mitogen activated protein kinase (MAPK), and phosphoinositide 3-kinase (PI3K)-related pathways [24,25,26,27,28]. Other studies that contradict the abovementioned reasoning postulate that age is no longer a significant prognostic factor, after correcting for clinicopathological and histopathological features such as grade, nodal status, ER status, and breast cancer subtypes [28, 29]. However, this argument only brings us back to the question of why younger women are more prone to aggressive subtypes of breast cancer in the first place and how the factors associated with younger patients, such as increased breast density and lower parity, contribute to these findings.
Although the same general trend for the age-outcome relationship is observed, it is clear that this interaction is complex and may well involve different mechanisms for each of the well-recognized breast cancer subtypes. The relationships of disease control and cancer death to age in luminal cancers are L-shaped, emphasizing the preponderance of risks in the youngest patients. This inflection point at 40–45 years of age may be indicative of a switch in factors driving disease initiation and progression. It has been similarly observed that luminal B cancers are particularly associated with poor outcomes in young breast cancer patients [30, 31]. However, the relationship between age and breast cancer events in HER2 enriched and triple-negative subtypes are more manifestly linear.
Our findings build on earlier studies carried out in dissimilar populations, indicating that women diagnosed with breast cancer at a younger age are more likely to have a poorer outcome. In patients younger than 40 years old, adjuvant radiotherapy following breast-conserving surgery reduced this risk by more than half [29, 30].
One study of 1703 patients from a single center showed that the relationship between recurrence hazard and age was continuous. Fitting with a log-linear function showed a 4% decrease in recurrence and a 2% decrease in cancer-specific death for every one-year increase in age, thus echoing our study findings [6].
A larger study carried out in Korea by Han et al. [7] showed that in patients younger than 35 years of age, there was an increasing risk of death with decreasing age; however, age did not affect patients between 35 and 50 years old. This finding is similar to our results for patients in the same age range. However, Han et al. [7] only included patients up to 50 years of age, whereas our study examined a wider age range. Our study examined records of patients older than 80 and showed that patients diagnosed at ages older than 50 faced increasing competing risks of death from non-breast cancer mortality; the evidence was a larger difference between breast cancer-specific survival and overall mortality in the older age group.
A relative survival analysis in our study population yielded results different from those reported in previous studies. Younger patients were found to have increased excess mortality compared with the older age groups, although this finding was not statistically significant in our study. The lack of statistical significance was possibly due to the smaller number of patients in the younger age group compared with that in the older age group, as well as the small number of events in the older age group.
Chia et al. [34] studied Singaporean breast cancer data and performed a population-based survival analysis. This study showed that younger patients have higher relative survival rates and lower excess risks of death compared with older patients. As demonstrated, this conclusion is opposite to that reached by our group. One possible explanation could be that the study by Chia et al. was conducted over an earlier period (1968–1992) that observed less effective systemic therapy for older patients. Older patients were often undertreated due to poorer health, reduced acceptance of treatment, or the denial of standard treatment arising from concerns of poorer tolerance to toxicity. In contrast, the increased use of systemic treatment, more effective chemotherapy, and better supportive care among older patients during our study period (1989–2012) enables older patients to enjoy the benefits of more effective treatment and improved outcomes. This finding reflects the relatively more indolent nature of their disease. A smaller, single-institution study by Foo et al. [35] showed that patients younger than 40 years did not have poorer overall survival, despite having tumors and a poorer prognostic profile. This result may be attributed to the more aggressive treatment the patients received. It is therefore likely that the differences in outcomes between age groups can be diminished with better treatment and better cancer subtyping.
These studies raise the issue of how we should define the relationship between age and the management of patients with breast cancer. Younger patients may need more aggressive treatment, while older patients may need less aggressive treatment. The current literature reveals conflicting results with regard to locoregional control in patients who have received BCT. Some studies have observed an increased risk of local recurrence with BCT, while others have not [32,33,34,35,36]. Nonetheless, there is no evidence that survival rates are inferior for younger patients who have received BCT relative to those for patients undergoing mastectomy [33]. Therefore, young age is not a contraindication to BCT.
Understanding the effect of age on breast cancer may allow us to better select patients for more appropriate therapy. Regan et al. studied SOFT and TEXT trials and found that the clinicopathologic characteristics that had the greatest contribution to the composite measure of recurrence risk relative to the complementary reference categories were young age (less than 35 years), four or more positive lymph nodes, and Grade 2–3 tumors. There was a gradual reduction in the hazard ratio from 2.2 to 1.2 for women 35 or younger to older than 50. It is now recommended that young women younger than 35 with hormone receptor positive breast cancer receive tamoxifen or exemestane plus ovarian suppression [37, 38].
At the other end of the spectrum, studies have shown that the survival of patients > 70 years old with estrogen-receptor (ER) positive tumors was not improved by the addition of adjuvant radiotherapy on top of lumpectomy and hormonal therapy; such an approach may therefore represent overtreatment in women of this age group [39, 40].
Mao et al. [41] showed that for women diagnosed at age 60 or younger, only the luminal A and basal molecular subtypes showed an overall survival benefit from radiotherapy. For women diagnosed at age 60 and older, there was no significant overall survival benefit of radiotherapy across all molecular subtypes.
Our study examined breast cancer outcomes with BCT in the Asian population. As the median age of diagnosis of breast cancer in Asians is 10 years younger than that in the Caucasian population, it is important for us to understand the effects of age on breast cancer. However, a drawback of our study was that the median follow-up period was only 4 years. A longer follow-up study in this population is being planned and would give us more information on the long-term outcome of BCT.
By intentionally limiting our study patients to only those with BCT, we may have inadvertently underestimated the effect of age, as long-term observational studies have shown improved overall outcomes with BCT compared with mastectomy. van Maaren et al. [42] carried out a population-based study on the Netherlands Cancer Registry and found that the 10-year overall survival for patients who received BCT was 21% higher than that for those who received mastectomy. The results were similar across all T and N stages. In particular, patients with T1N0 breast cancers had a 24% higher metastasis-free survival after BCT compared with that for patients undergoing mastectomy. In addition to our shorter follow-up, this observation may further explain the relatively high BCSS for patients in our study cohort, among whom more than half had Stage I cancer.
Our study population has a relatively small number of patients with HER2 or basal subtypes breast cancers. As such, the relationship between age and clinical outcomes cannot be determined accurately. To a large extent, our results have been affected by the large proportion of patients with luminal cancers. In the model construction, there might have been non-linear relationships that we missed, as we used significance testing (which is sensitive to sample size) to select models.
There were sufficient events to perform multivariate analysis for the relationship between age, overall survival and breast cancer-free interval. For other endpoints, these variables could not be adjusted for as the number of events was too small, particularly as size and number of positive nodes were modeled as continuous variables.