Follow-up after breast cancer: Variations, best practices, and opportunities for improvement according to health care professionals

The effectiveness of personalised surveillance and aftercare in breast cancer follow-up: a systematic review

PURPOSE

Breast cancer follow-up (surveillance and aftercare) varies from one-size-fits-all to more personalised approaches. A systematic review was performed to get insight in existing evidence on (cost-)effectiveness of personalised follow-up.

METHODS

PubMed, Scopus and Cochrane were searched between 01-01-2010 and 10-10-2022 (review registered in PROSPERO:CRD42022375770). The inclusion population comprised nonmetastatic breast cancer patients ≥ 18 years, after completing curative treatment. All intervention-control studies studying personalised surveillance and/or aftercare designed for use during the entire follow-up period were included. All review processes including risk of bias assessment were performed by two reviewers. Characteristics of included studies were described.

RESULTS

Overall, 3708 publications were identified, 64 full-text publications were read and 16 were included for data extraction. One study evaluated personalised surveillance. Various personalised aftercare interventions and outcomes were studied. Most common elements included in personalised aftercare plans were treatment summaries (75%), follow-up guidelines (56%), lists of available supportive care resources (38%) and PROs (25%). Control conditions mostly comprised usual care. Four out of seven (57%) studies reported improvements in quality of life following personalisation. Six studies (38%) found no personalisation effect, for multiple outcomes assessed (e.g. distress, satisfaction). One (6.3%) study was judged as low, four (25%) as high risk of bias and 11 (68.8%) as with concerns.

CONCLUSION

The included studies varied in interventions, measurement instruments and outcomes, making it impossible to draw conclusions on the effectiveness of personalised follow-up. There is a need for a definition of both personalised surveillance and aftercare, whereafter outcomes can be measured according to uniform standards.

Personalized surveillance and aftercare for non-metastasized breast cancer: the NABOR study protocol of a multiple interrupted time series design

BACKGROUND

Follow-up of curatively treated primary breast cancer patients consists of surveillance and aftercare and is currently mostly the same for all patients. A more personalized approach, based on patients' individual risk of recurrence and personal needs and preferences, may reduce patient burden and reduce (healthcare) costs. The NABOR study will examine the (cost-)effectiveness of personalized surveillance (PSP) and personalized aftercare plans (PAP) on patient-reported cancer worry, self-rated and overall quality of life and (cost-)effectiveness.

METHODS

A prospective multicenter multiple interrupted time series (MITs) design is being used. In this design, 10 participating hospitals will be observed for a period of eighteen months, while they -stepwise- will transit from care as usual to PSPs and PAPs. The PSP contains decisions on the surveillance trajectory based on individual risks and needs, assessed with the 'Breast Cancer Surveillance Decision Aid' including the INFLUENCE prediction tool. The PAP contains decisions on the aftercare trajectory based on individual needs and preferences and available care resources, which decision-making is supported by a patient decision aid. Patients are non-metastasized female primary breast cancer patients (N = 1040) who are curatively treated and start follow-up care. Patient reported outcomes will be measured at five points in time during two years of follow-up care (starting about one year after treatment and every six months thereafter). In addition, data on diagnostics and hospital visits from patients' Electronical Health Records (EHR) will be gathered. Primary outcomes are patient-reported cancer worry (Cancer Worry Scale) and overall quality of life (as assessed with EQ-VAS score). Secondary outcomes include health care costs and resource use, health-related quality of life (as measured with EQ5D-5L/SF-12/EORTC-QLQ-C30), risk perception, shared decision-making, patient satisfaction, societal participation, and cost-effectiveness. Next, the uptake and appreciation of personalized plans and patients' experiences of their decision-making process will be evaluated.

DISCUSSION

This study will contribute to insight in the (cost-)effectiveness of personalized follow-up care and contributes to development of uniform evidence-based guidelines, stimulating sustainable implementation of personalized surveillance and aftercare plans.

TRIAL REGISTRATION

Study sponsor: ZonMw. Retrospectively registered at ClinicalTrials.gov (2023), ID: NCT05975437.

The decision aid is the easy part: workflow challenges of shared decision making in cancer care

Delivering high-quality, patient-centered cancer care remains a challenge. Both the National Academy of Medicine and the American Society of Clinical Oncology recommend shared decision making to improve patient-centered care, but widespread adoption of shared decision making into clinical care has been limited. Shared decision making is a process in which a patient and the patient's health-care professional weigh the risks and benefits of different options and come to a joint decision on the best course of action for that patient on the basis of their values, preferences, and goals for care. Patients who engage in shared decision making report higher quality of care, whereas patients who are less involved in these decisions have statistically significantly higher decisional regret and are less satisfied. Decision aids can improve shared decision making-for example, by eliciting patient values and preferences that can then be shared with clinicians and by providing patients with information that may influence their decisions. However, integrating decision aids into the workflows of routine care is challenging. In this commentary, we explore 3 workflow-related barriers to shared decision making: the who, when, and how of decision aid implementation in clinical practice. We introduce readers to human factors engineering and demonstrate its potential value to decision aid design through a case study of breast cancer surgical treatment decision making. By better employing the methods and principles of human factors engineering, we can improve decision aid integration, shared decision making, and ultimately patient-centered cancer outcomes.

Needs and preferences of breast cancer survivors regarding outcome-based shared decision-making about personalised post-treatment surveillance

PURPOSE

In this study, we explored how patients experience current information provision and decision-making about post-treatment surveillance after breast cancer. Furthermore, we assessed patients' perspectives regarding less intensive surveillance in case of a low risk of recurrence.

METHODS

We conducted semi-structured interviews with 22 women in the post-treatment surveillance trajectory in seven Dutch teaching hospitals.

RESULTS

Although the majority of participants indicated a desire for shared decision-making (SDM) about post-treatment surveillance, participants experienced no SDM. Information provision was often suboptimal and unstructured. Participants were open for using risk information in decision-making, but hesitant towards less intensive surveillance. Perceived advantages of less intensive surveillance were: less distressing moments, leaving the patient role behind, and lower burden. Disadvantages were: fewer moments for reassurance, fear of missing recurrences, and a higher threshold for aftercare for side effects.

CONCLUSIONS

SDM about post-treatment surveillance is desirable. Although women are hesitant about less intensive surveillance, they are open to the use of personalised risk assessment for recurrences in decision-making about surveillance.

IMPLICATIONS FOR CANCER SURVIVORS

To facilitate SDM about post-treatment surveillance, the timing and content of information provision should be improved. Risk information should be provided in an accessible and understandable way. Moreover, fear of cancer recurrence and other personal considerations should be addressed in the process of SDM.

Cancer Survivor Preferences for Models of Breast Cancer Follow-Up Care: Selecting Attributes for Inclusion in a Discrete Choice Experiment

BACKGROUND AND OBJECTIVE

It is critical to evaluate cancer survivors' preferences when developing follow-up care models to better address the needs of cancer survivors. This study was conducted to understand the key attributes of breast cancer follow-up care for use in a future discrete choice experiment (DCE) survey.

METHODS

Key attributes of breast cancer follow-up care models were generated using a multi-stage, mixed-methods approach. Focus group discussions were conducted with cancer survivors and clinicians to generate a range of attributes of current and ideal follow-up care. These attributes were then prioritised using an online survey with survivors and healthcare providers. The DCE attributes and levels were finalised via an expert panel discussion based on the outcomes of the previous stages.

RESULTS

Four focus groups were held, two with breast cancer survivors (n = 7) and two with clinicians (n = 8). Focus groups generated sixteen attributes deemed important for breast cancer follow-up care models. The prioritisation exercise was conducted with 20 participants (14 breast cancer survivors and 6 clinicians). Finally, the expert panel selected five attributes for a future DCE survey tool to elicit cancer survivors' preferences on breast cancer follow-up care. The final attributes included: the care team, allied health and supportive care, survivorship care planning, travel for appointments, and out-of-pocket costs.

CONCLUSIONS

Attributes identified can be used in future DCE studies to elicit cancer survivors' preferences for breast cancer follow-up care. This strengthens the design and implementation of follow-up care programs that best suit the needs and expectations of breast cancer survivors.

Health care professionals' perspectives on shared decision making supported by personalised‐risk‐for‐recurrences‐calculations regarding surveillance after breast cancer

Objective

Breast cancer patients for whom less intensive surveillance is sufficient can be identified based on the risk for locoregional recurrences (LRRs). This study explores health care professionals' (HCPs) perspectives on less intensive surveillance, preferences for shared decision‐making (SDM) about surveillance and perspectives on the use of patients' estimated personal risk for LRRs in decision‐making about surveillance.

Methods

We conducted semi‐structured interviews with 21 HCPs providing follow‐up care for breast cancer patients in seven Dutch teaching hospitals (Santeon hospitals).

Results

HCPs were predominantly positive about less intensive surveillance for women with a low risk for recurrences. They mentioned important prerequisites such as clearly defined surveillance schedules based on risk categories, information provision and communication support for patients and HCPs. Most HCPs supported SDM about surveillance and were positive about using patients' estimated personal risk for LRRs. HCPs specified prerequisites such as clear visualisation and explanation of risk information, attention for fear of cancer recurrence (FCR) and defined surveillance schedules for specific risk groups.

Conclusion

Mentioned prerequisites for less intensive surveillance need to be accounted for. Information needs and existing misconceptions need to be addressed. Outcome information regarding risks for LRRs and FCR can enrich the SDM process about surveillance.

Health care professionals overestimate the risk for locoregional recurrences after breast cancer treatment depending on their specialty

Purpose

For the implementation of personalised surveillance, it is important to create more awareness among HCPs with regard to the risk for locoregional recurrences (LRRs). The aim of this study is to evaluate the current awareness and estimations of individual risks for LRRs after completion of primary treatment for breast cancer among health care professionals (HCPs) in the Netherlands, without using any prediction tools.

Methods

A cross-sectional survey was performed among 60 HCPs working in breast cancer care in seven Dutch hospitals and 25 general practitioners (GPs). The survey consisted of eleven realistic surgically treated breast cancer cases. HCPs were asked to estimate the 5-year risk for LRRs for each case, which was compared to the estimations by the INFLUENCE-nomogram using one-sample Wilcoxon tests. Differences in estimations between HCPs with different specialities were determined using Kruskal–Wallis tests and Dunn tests.

Results

HCPs tended to structurally overestimate the 5-year risk for LRR on each case. Average overestimations ranged from 4.8 to 26.1%. Groups of HCPs with varying specialities differed significantly in risk estimations. GPs tended to overestimate the risk for LRRs on average the most (15.0%) and medical oncologists had the lowest average overestimation (2.7%).

Conclusions

It is important to create more awareness of the risk for LRRs, which is a pre-requisite for the implementation of personalised surveillance after breast cancer. Besides education for HCPs, the use of prediction models such as the INFLUENCE-nomogram can support in estimating an objective estimate of each individual patient’s risk.