The results from the 6-armed RCT trial KARISMA 2 show that 2.5 mg of tamoxifen has the potential to be as effective in reducing incidence and recurrence of breast cancer as the established 20 mg dose. 

Mammographic density change is a proxy for tamoxifen therapy response. We tested if lower doses of tamoxifen were non-inferior to reduce mammographic density and associated with fewer symptoms.

In all 1440 women, aged 40 to 74 years, participating in the Swedish mammography screening program were included in the six-months double-blind six-arm randomized placebo-controlled KARISMA phase II trial and randomized to either placebo, 1, 2.5, 5, 10 and 20 mg of tamoxifen.

The participants had non-inferior mammographic density reduction following 2.5, 5, and 10 mg tamoxifen compared with the median 10.1% decrease observed in the 20 mg group. The reduction was confined to premenopausal women. Severe vasomotor symptoms (hot flashes, cold and night sweats) were reduced by approximately 50% in the 2.5, 5, and 10 mg groups compared with the 20 mg group.

In conclusion,  premenopausal women showed non-inferior magnitude of breast density decrease at 2.5 mg of tamoxifen and experienced fewer side effects compared to the standard dose of 20 mg.

Future studies should test if 2.5 mg of tamoxifen reduces the risk of primary breast cancer.

Eriksson, et al J Clin Oncol. 2021 Mar 18:JCO2002598. doi: 10.1200/JCO.20.02598.

The thesis included a paper describing a unique tool, STRATUS, for measuring mammographic density regardless of type of image and vendor. This tool and additional mammographic features was used for generating a risk prediction tool and described below, published 20-09-08 (please see below). The thesis also described the Karisma trial where lower doses of tamoxifen were tested. In short, 1,440 women were randomised to placebo, 1, 2.5, 5, 10 and 20 mg and it turned out that 2.5 mg could be equally affective as 20 mg of tamoxifen but come with a 50% reduction in side effects (paper accepted for publication J Clin Oncology). Lastly, modelling the impact of a tamoxifen induced density decrease showed that the mammographic sensitivity would increase enabling even earlier detection of breast cancers and thereby a reduction in interval cancers by 24%.

A clinical model for identifying the short-term risk of breast cancer. Eriksson et al. Breast Cancer Reesearch, 2017. DOI: 10.1186/s13058-017-0820-y

Use of Low-Dose Tamoxifen to Increase Mammographic Screening Sensitivity in Premenopausal Women. Eriksson et al. Cancer. 2021. DOI: 10.3390/cancers13020302

Use of Low-Dose Tamoxifen to Increase Mammographic Screening Sensitivity in Premenopausal Women. Eriksson et al. Cancer. DOI: 10.3390/cancers13020302

Shadi Azam has published three papers (see links below) and have one paper in manuscript. Shadi has over the last years worked hard trying to understand the factors behind two mammographic “features” and how these features influence the risk of breast cancer. The features are mammographic density change and breast microcalcifications. None of them are currently particularly well covered in the scientific literature. 

Surprisingly few of the established risk factors for breast cancer influences mammographic density change and the change does not seem to influence subsequent risk of breast cancer. Most factors influencing the risk of breast cancers do not seem to influence the risk of microcalcifications in the same direction. On the other hand, microcalcifications seem to be as a strong risk factor for breast cancer as mammographic density in postmenopausal women. 

Determinants of Mammographic Density Change. Azam et al. 2019. JNCI Cancer Spectr. DOI: 10.1093/jncics/pkz004

Mammographic Density Change and Risk of Breast Cancer. Azam et al. Journal of the National Cancer Institute. DOI: 10.1093/jnci/djz149

Predictors of mammographic microcalcifications. Azam et al. Int J Cancer. 2021. DOI: 10.1002/ijc.33302

Using the prospective screening Karma cohort, an image-based breast cancer 2-year risk model was developed using mammographic features (density, masses, microcalcifications) identified using artificial intelligence. The model could be extended by including a polygenic risk score with 313 single nucleotide polymorphisms. The area under the receiver operating characteristic curve (AUC) for the image-based model was 0.73 (95% confidence interval [CI]: 0.71, 0.74) and for the genetic extended model was 0.77 (95% CI: 0.75, 0.79). There was a relative 9-fold difference in risk between women at high risk (8% of the population) and those at general risk. High-risk women were more likely to be diagnosed with stage II cancers and with tumours 20 mm or larger and were less likely to have stage I and estrogen receptor-positive tumours.

Identification of Women at High Risk of Breast Cancer Who Need Supplemental Screening. Eriksson et al. Radiology, 2020. DOI: 10.1148/radiol.2020201620

The association between annual mammographic density change and breast cancer risk was evaluated using the Karma Cohort (N = 43 810). Density was measured using the STRATUS method and relative mammographic density change was categorized as decreased (>10% decrease per year), stable (no change), or increased (>10% increase per year). Cox proportional hazards regression was used to estimate the association.

In all, 563 women were diagnosed with breast cancer but no significant association between mammographic density change and breast cancer was seen. Adding baseline mammographic density did not influence the results.

Mammographic Density Change and Risk of Breast Cancer. Azam et al. Journal of the National Cancer Institute. DOI: 10.1093/jnci/djz149