Development and internal-external validation of statistical and machine learning models for breast cancer prognostication: cohort study

Objective To develop a clinically useful model that estimates the 10 year risk of breast cancer related mortality in women (self-reported female sex) with breast cancer of any stage, comparing results from regression and machine learning approaches. Design Population based cohort study. Setting QResearch primary care database in England, with individual level linkage to the national cancer registry, Hospital Episodes Statistics, and national mortality registers. Participants 141 765 women aged 20 years and older with a diagnosis of invasive breast cancer between 1 January 2000 and 31 December 2020. Main outcome measures Four model building strategies comprising two regression (Cox proportional hazards and competing risks regression) and two machine learning (XGBoost and an artificial neural network) approaches. Internal-external cross validation was used for model evaluation. Random effects meta-analysis that pooled estimates of discrimination and calibration metrics, calibration plots, and decision curve analysis were used to assess model performance, transportability, and clinical utility. Results During a median 4.16 years (interquartile range 1.76-8.26) of follow-up, 21 688 breast cancer related deaths and 11 454 deaths from other causes occurred. Restricting to 10 years maximum follow-up from breast cancer diagnosis, 20 367 breast cancer related deaths occurred during a total of 688 564.81 person years. The crude breast cancer mortality rate was 295.79 per 10 000 person years (95% confidence interval 291.75 to 299.88). Predictors varied for each regression model, but both Cox and competing risks models included age at diagnosis, body mass index, smoking status, route to diagnosis, hormone receptor status, cancer stage, and grade of breast cancer. The Cox model’s random effects meta-analysis pooled estimate for Harrell’s C index was the highest of any model at 0.858 (95% confidence interval 0.853 to 0.864, and 95% prediction interval 0.843 to 0.873). It appeared acceptably calibrated on calibration plots. The competing risks regression model had good discrimination: pooled Harrell’s C index 0.849 (0.839 to 0.859, and 0.821 to 0.876, and evidence of systematic miscalibration on summary metrics was lacking. The machine learning models had acceptable discrimination overall (Harrell’s C index: XGBoost 0.821 (0.813 to 0.828, and 0.805 to 0.837); neural network 0.847 (0.835 to 0.858, and 0.816 to 0.878)), but had more complex patterns of miscalibration and more variable regional and stage specific performance. Decision curve analysis suggested that the Cox and competing risks regression models tested may have higher clinical utility than the two machine learning approaches. Conclusion In women with breast cancer of any stage, using the predictors available in this dataset, regression based methods had better and more consistent performance compared with machine learning approaches and may be worthy of further evaluation for potential clinical use, such as for stratified follow-up

Construction of the secondary care administrative records frailty (SCARF) index and validation on older women with operable invasive breast cancer in England and Wales:a cohort study

OBJECTIVES: Studies that use national datasets to evaluate the management of older women with breast cancer are often constrained by a lack of information on patient fitness. This study constructed a frailty index for use with secondary care administrative records and evaluated its ability to improve models of treatment patterns and overall survival in women with breast cancer. DESIGN: Retrospective cohort study. PARTICIPANTS: Women aged ≥50 years with oestrogen receptor (ER) positive early invasive breast cancer diagnosed between 2014 and 2017 in England. METHODS: The secondary care administrative records frailty (SCARF) index was based on the cumulative deficit model of frailty, using International Statistical Classification of Diseases, Injuries and Causes of Death, 10th revision codes to define a set of deficits. The index was applied to administrative records that were linked to national cancer registry datasets. The ability of the SCARF index to improve the performance of regression models to explain observed variation in the rate of surgery and overall survival was evaluated using Harrell's c-statistic and decision curve analysis. External validation was performed on a dataset of similar women diagnosed in Wales. RESULTS: The SCARF index captured 32 deficits that cover functional impairment, geriatric syndromes, problems with nutrition, cognition and mood, and medical comorbidities. In the English dataset (n=67 925), the prevalence of frailty in women aged 50-69, 70-79 and ≥80 years was 15%, 28% and 47%, respectively. Adding a frailty measure to regression models containing age, tumour characteristics and comorbidity improved their ability to: (1) discriminate between whether a woman was likely to have surgery and (2) predict overall survival. Similar results were obtained when the models were applied to the Welsh cohort (n=4 230). CONCLUSION: The SCARF index provides a simple and consistent method to identify frailty in population level data and could help describe differences in breast cancer treatments and outcomes

The influence of age, comorbidity and frailty on treatment with surgery and systemic therapy in older women with operable triple negative breast cancer (TNBC) in England: A population-based cohort study.

BACKGROUND: Surgery and chemotherapy use were studied among older women with early stage triple negative breast cancer (TNBC) in a population-based cohort. METHODS: Women aged ≥50 years with unilateral early (stage 1-3a) TNBC diagnosed in 2014-2017 were identified from English cancer registration data. Information on surgery and chemotherapy was from linked Hospital Episode Statistics and Systemic Anti-Cancer Therapy datasets, respectively. Logistic regression was used to investigate the influences of patient age, comorbidity and frailty on uptake of surgery and chemotherapy. RESULTS: There were 7094 women with early stage TNBC. Overall rate of surgery was 94%, which only decreased among women aged ≥85 years (74%) and among the most frail. Among the 6681 women receiving surgery, 16% had neoadjuvant and 42% had adjuvant chemotherapy; the use of both decreased with age. More comorbidities and greater frailty were associated with lower rates of chemotherapy. There were differences in the uptake of chemotherapy across geographical regions and in the neoadjuvant and adjuvant chemotherapy regimens between age groups. CONCLUSION: Majority of older women with early TNBC had surgery, although some physically fit older women did not. Chemotherapy use varied by age and fitness

Mastectomy patterns among older women with early invasive breast cancer in England and Wales: A population-based cohort study.

INTRODUCTION: Older women with early invasive breast cancer (EIBC) are more likely to receive a mastectomy compared with younger women. This study assessed factors associated with receiving a mastectomy among older women with EIBC, with a particular focus on comorbidity and frailty. MATERIALS AND METHODS: Women diagnosed with EIBC (stages I-IIIa) aged ≥50 years from 2014 to 2019 in English and Welsh NHS organisations who received breast surgery were identified from cancer registration datasets linked to routine hospital data. Separate multivariable logistic regression models explored factors associated with mastectomy use, within each tumour stage (T1-T3). For each tumour stage, risk-adjusted rates of mastectomy were calculated for each NHS organisation and displayed using funnel plots. RESULTS: We included 106,952 women with EIBC: 23.4% received a mastectomy as their first breast cancer surgery. Receipt of mastectomy was more common among patients with a higher tumour stage (T1: 12.3%; T2: 37.6%; T3: 77.5%), and mastectomy use increased with age within each tumour stage category (50-59 vs 80 + years: 11.8% vs 26.3% for T1; 31.5% vs 56.9% for T2; 73.4% vs 90.3% for T3). Results from a multivariable regression model showed that more severe frailty was associated with mastectomy use for women with T1 (p = 0.002) or T2 (p = 0.003) tumours, but may not be for women with T3 tumours (p = 0.041). There was no association between comorbidity and mastectomy use after accounting for frailty (all p > 0.1). Adjusting for clinical and patient factors only slightly reduced the association between age and mastectomy use. Variation in mastectomy use between NHS organisations was greatest for women with T2 EIBC (unadjusted range: 17.7% to 68.4%). DISCUSSION: Older women with EIBC are more commonly treated with mastectomy. This could not be explained by tumour characteristics or physical fitness, raising questions about whether surgical decision-making inconsistently incorporates information on patient fitness and functional age

in breast cancer

PSMD9 expression predicts radiotherapy respons

A systematic review of methods to immobilise breast tissue during adjuvant breast irradiation

Greater use of 3D conformal, Intensity Modulated Radiotherapy (IMRT) and external beam partial breast irradiation following local excision (LE) for breast cancer has necessitated a review of the effectiveness of immobilisation methods to stabilise breast tissue. To identify the suitability of currently available breast (rather than thorax) immobilisation techniques an appraisal of the literature was undertaken. The aim was to identify and evaluate the benefit of additional or novel immobilisation approaches (beyond the standard supine, single arm abducted and angled breast board technique adopted in most radiotherapy departments). A database search was supplemented with an individual search of key radiotherapy peer-reviewed journals, author searching, and searching of the grey literature. A total of 27 articles met the inclusion criteria. The review identified good reproducibility of the thorax using the standard supine arm-pole technique. Reproducibility with the prone technique appears inferior to supine methods (based on data from existing randomised controlled trials). Assessing the effectiveness of additional breast support devices (such as rings or thermoplastic material) is hampered by small sample sizes and a lack of randomised data for comparison. Attention to breast immobilisation is recommended, as well as agreement on how breast stability should be measured using volumetric imaging. Keywords: Breast, immobilisation, positioning, reproducibility, review.</p