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.

Inequalities in the omission of axillary dissection in sentinel lymph node positive patients in the Netherlands: Innovative hospitals are early adopters of a de-escalating approach.

During the last decade completion axillary lymph node dissection (cALND) was gradually omitted in sentinel lymph node positive (SLN+) breast cancer patients. However, adoption varies among hospitals. We analyzed factors associated with the omission of cALND in all Dutch SLN+ patients. As one of the focus hospital-related factors we defined "innovative" as the percentage of gene-expression profile (GEP) deployment within the indicated group of patients per hospital as a proxy for early adoption of innovations. cT1-2N0M0 SLN+ patients treated between 2011 and 2018 were selected from the Netherlands Cancer Registry. Hospitals were defined to be innovative based on their GEP use. Multivariable logistic regression (MLR) was performed to assess the relationship between innovative capacity, patient-, treatment- and hospital-related characteristics and cALND performance. 14 317 patients were included. Treatment in a hospital with high innovative capacity was associated with a lower probability of receiving cALND (OR 0.69, OR 0.46 and OR 0.35 in modestly, fairly and very innovative, respectively). Other factors associated with a lower probability of receiving a cALND were age 70 and 79 years and ≥79 years (ORs 0.59 [95% CI: 0.50-0.68] and 0.21 [95% CI: 0.17-0.26]) and treatment in an academic hospital (OR 0.41 [95% CI: 0.33-0.51]). Factors associated with an increased probability of undergoing cALND were HR-/HER2- tumors (OR 1.46 [95% CI: 1.19-1.80]), macrometastatic lymph node involvement (OR 6.37 [95% CI: 5.70-7.13]) and mastectomy (OR 4.57 [95% CI: 4.09-5.10]). Patients treated in a hospital that early adopted innovations were less likely to receive cALND. Our findings endorse the need for studies on barriers and facilitators of implementing innovations.

A conditional model predicting the 10-year annual extra mortality risk compared to the general population: a large population-based study in Dutch breast cancer patients.

OBJECTIVE: Many cancer survivors are facing difficulties in getting a life insurance; raised premiums and declinatures are common. We generated a prediction model estimating the conditional extra mortality risk of breast cancer patients in the Netherlands. This model can be used by life insurers to accurately estimate the additional risk of an individual patient, conditional on the years survived. METHODOLOGY: All women diagnosed with stage I-III breast cancer in 2005-2006, treated with surgery, were selected from the Netherlands Cancer Registry. For all stages separately, multivariable logistic regression was used to estimate annual mortality risks, conditional on the years survived, until 10 years after diagnosis, resulting in 30 models. The conditional extra mortality risk was calculated by subtracting mortality rates of the general Dutch population from the patient mortality rates, matched by age, gender and year. The final model was internally and externally validated, and tested by life insurers. RESULTS: We included 23,234 patients: 10,101 stage I, 9,868 stage II and 3,265 stage III. The final models included age, tumor stage, nodal stage, lateralization, location within the breast, grade, multifocality, hormonal receptor status, HER2 status, type of surgery, axillary lymph node dissection, radiotherapy, (neo)adjuvant systemic therapy and targeted therapy. All models showed good calibration and discrimination. Testing of the model by life insurers showed that insurability using the newly-developed model increased with 13%, ranging from 0%-24% among subgroups. CONCLUSION: The final model provides accurate conditional extra mortality risks of breast cancer patients, which can be used by life insurers to make more reliable calculations. The model is expected to increase breast cancer patients' insurability and transparency among life insurers.