A web-based personalized decision support tool for patients diagnosed with ductal carcinoma in situ: development, content evaluation, and usability testing

Disease-specific survival outcomes for patients after locoregional treatment for ductal carcinoma in situ: observational cohort study

BACKGROUND

Breast-conserving surgery alone, breast-conserving surgery with adjuvant radiation treatment, and mastectomy are guideline-concordant treatments for ductal carcinoma in situ. The aim of this study was to compare survival outcomes between these treatment options.

METHODS

A stratified random sample of patients diagnosed with pure ductal carcinoma in situ between 2008 and 2014 was selected from 1330 sites in the USA. Data on diagnosis, treatment, and follow-up were abstracted by local cancer registrars. Population-averaged marginal estimates of disease-specific survival and overall survival for breast-conserving surgery alone, breast-conserving surgery with radiation treatment, and mastectomy were obtained by combining sampling and overlap weights.

RESULTS

A total of 18 442 women were included, with a median follow-up of 67.8 (interquartile range 46.1-93.5) months. A total of 35 women died from breast cancer, at a median age of 62 (interquartile range 50-74) years. Population-averaged 8-year rates of disease-specific survival were 99.6% or higher for all treatment groups, with no significant differences between groups (breast-conserving surgery alone versus breast-conserving surgery with radiation treatment, HR 1.19 (95% c.i. 0.29 to 4.85); and mastectomy versus breast-conserving surgery with radiation treatment, HR 1.74 (95% c.i. 0.53 to 5.72). There was no difference in overall survival between the patients who underwent a mastectomy and the patients who underwent breast-conserving surgery with radiation treatment (HR 1.09 (95% c.i. 0.83 to 1.43)). Patients who underwent breast-conserving surgery alone had lower overall survival compared with the patients who underwent breast-conserving surgery with radiation treatment (HR 1.29 (95% c.i. 1.00 to 1.67)). This survival difference vanished for all but one subgroup, namely patients less than 65 years (HR 1.86 (95% c.i. 1.15 to 3.00)).

CONCLUSION

There was no statistically significant difference in disease-specific survival between women operated with breast-conserving surgery alone, breast-conserving surgery with radiation treatment, or mastectomy for ductal carcinoma in situ. Given the low absolute risk of disease-specific mortality, these results provide confidence in offering individualized locoregional treatment without fear of compromising survival.

Navigating the perils and pitfalls throughout the consent process in hematopoietic cell transplantation

Hematopoietic cell transplantation (HCT) is a complex treatment used in malignancies and some non-malignant diseases. The informed consent process for HCT can also be complex due to patient- and process-related barriers. The informed consent process needs to be a dynamic and ongoing process, not simply a checklist. As a result of the realities of HCT, we highlight some potential pitfalls to the informed consent process including uncertainty, sociocultural and communication barriers, and decisional regret. The purpose of this comprehensive review is to highlight unique situations which can result in failure of the informed consent process. We also offer potential solutions to these pitfalls, primarily making the informed consent more patient focused through dynamic and continuous processes to mitigate decisional regret.

Prediction Models and Decision Aids for Women with Ductal Carcinoma In Situ: A Systematic Literature Review

Simple Summary

Ductal carcinoma in situ (DCIS) is a potential precursor to invasive breast cancer (IBC). Although in many women DCIS will never become breast cancer, almost all women diagnosed with DCIS undergo surgery with/without radiotherapy. Several studies are ongoing to de-escalate treatment for DCIS. Multiple decision support tools have been developed to aid women with DCIS in selecting the best treatment option for their specific goals. The aim of this study was to identify these decision support tools and evaluate their quality and clinical utility. Thirty-three studies were reviewed, in which four decision aids and six prediction models were described. While some of these models might be promising, most lacked important qualities such as tools to help women discuss their options or good quality validation studies. Therefore, the need for good quality, well validated decision support tools remains unmet.

Abstract

Even though Ductal Carcinoma in Situ (DCIS) can potentially be an invasive breast cancer (IBC) precursor, most DCIS lesions never will progress to IBC if left untreated. Because we cannot predict yet which DCIS lesions will and which will not progress, almost all women with DCIS are treated by breast-conserving surgery +/− radiotherapy, or even mastectomy. As a consequence, many women with non-progressive DCIS carry the burden of intensive treatment without any benefit. Multiple decision support tools have been developed to optimize DCIS management, aiming to find the balance between over- and undertreatment. In this systematic review, we evaluated the quality and added value of such tools. A systematic literature search was performed in Medline(ovid), Embase(ovid), Scopus and TRIP. Following the PRISMA guidelines, publications were selected. The CHARMS (prediction models) or IPDAS (decision aids) checklist were used to evaluate the tools’ methodological quality. Thirty-three publications describing four decision aids and six prediction models were included. The decision aids met at least 50% of the IPDAS criteria. However, most lacked tools to facilitate discussion of the information with healthcare providers. Five prediction models quantify the risk of an ipsilateral breast event after a primary DCIS, one estimates the risk of contralateral breast cancer, and none included active surveillance. Good quality and external validations were lacking for all prediction models. There remains an unmet clinical need for well-validated, good-quality DCIS risk prediction models and decision aids in which active surveillance is included as a management option for low-risk DCIS.