Health-related quality of life by type of breast surgery in women with primary breast cancer: prospective longitudinal cohort study.

BACKGROUND: Health-related quality of life and patient-related outcome measures for patients with cancer have gained increased interest over the last decade. However, few prospective studies with longitudinal data evaluated health-related quality of life in patients with breast cancer. This study aimed to investigate how health-related quality of life changed from the time of diagnosis to 1 year after breast cancer surgery for the main surgical techniques. METHODS: This prospective longitudinal single-centre study included patients with primary breast cancer diagnosed in 2019-2020 who underwent surgery. Patients completed a health-related quality of life questionnaire (Breast-Q) at baseline. One year after surgery, they completed the Breast-Q a second time, the EORTC (European Organization for Research and Treatment of Cancer) quality of life questionnaire-C30 and the quality of life questionnaire-BR23. Analysis of variance and Kruskal-Wallis tests were used to evaluate the differences in health-related quality of life between surgical groups. Analysis of covariance with robust standard errors was used to adjust for confounders. RESULTS: In total, 340 patients were included in the study; 160 patients received oncoplastic partial mastectomy, 112 received partial mastectomy, 42 received mastectomy and 26 had mastectomy with immediate reconstruction. Patients that had partial mastectomy or oncoplastic partial mastectomy were more satisfied with their breasts (P < 0.001), had a better body image (P = 0.006) and higher sexual functioning scores (P = 0.027) than patients who had a mastectomy with/without reconstruction. The oncoplastic and mastectomy with reconstruction groups had more breast symptoms than other groups (P < 0.001), and the mastectomy group had the least symptoms from the chest area. CONCLUSION: Partial mastectomy and oncoplastic partial mastectomy have the best outcomes in terms of breast satisfaction, body image and sexual functioning. This highlights the importance of preserving the breast when feasible and underscores that breast reconstruction is not equal to breast conservation. Registration number: NCT04227613 (http://www.clinicaltrials.gov).

Hormone receptor mRNA and protein levels as predictors of premenopausal tamoxifen benefit.

BACKGROUND AND PURPOSE: Tamoxifen remains an important adjuvant treatment in premenopausal patients with hormone receptor-positive breast cancer. Thus, determination of hormone receptors is important. Here, we compare cytosol-based methods, immunohistochemistry (IHC), and gene expression (GEX) analysis for determining hormone receptor status in premenopausal breast cancer patients from a randomised tamoxifen trial, to evaluate their performance in identifying patients that benefit from tamoxifen. PATIENTS AND METHODS: Premenopausal patients (n=564) were randomised to 2 years of tamoxifen or no systemic treatment. Estrogen receptor (ER) and progesterone receptor (PR) status by protein expression measured by cytosol-based methods and IHC, and mRNA by GEX analysis were compared in 313 patients with available data from all methods. Kaplan Meier estimates and Cox regression were used to evaluate the treatment-predictive value for recurrence-free interval (RFi) and overall survival (OS). Median follow-up for event-free patients was 26 (RFi) and 33 (OS) years. RESULTS: The mRNA data of ESR1 and PGR distributed bimodally, patterns confirmed in an independent cohort. Kappa-values between all methods were 0.76 and 0.79 for ER and PR, respectively. Tamoxifen improved RFi in patients with ER-positive (ER+) or PR-positive (PR+) tumours (Hazard Ratio [HR] and 95% confidence interval [CI]), cytosol-ER+ 0.53 [0.36-0.79]; IHC-ER+ 0.55 [0.38-0.79]; GEX-ER+ 0.54 [0.37-0.77]; cytosol-PR+ 0.49 [0.34-0.72]; IHC-PR+ 0.58 [0.40-0.85]; GEX-PR+ 0.55 [0.38-0.80]). Results were similar for OS. INTERPRETATION: These methods can all identify patients that benefit from 2 years of tamoxifen with equal performance, indicating that GEX data might be used to guide adjuvant tamoxifen therapy.

Retrospective validation study of an artificial neural network-based preoperative decision-support tool for noninvasive lymph node staging (NILS) in women with primary breast cancer (ISRCTN14341750).

BACKGROUND: Surgical sentinel lymph node biopsy (SLNB) is routinely used to reliably stage axillary lymph nodes in early breast cancer (BC). However, SLNB may be associated with postoperative arm morbidities. For most patients with BC undergoing SLNB, the findings are benign, and the procedure is currently questioned. A decision-support tool for the prediction of benign sentinel lymph nodes based on preoperatively available data has been developed using artificial neural network modelling. METHODS: This was a retrospective geographical and temporal validation study of the noninvasive lymph node staging (NILS) model, based on preoperatively available data from 586 women consecutively diagnosed with primary BC at two sites. Ten preoperative clinicopathological characteristics from each patient were entered into the web-based calculator, and the probability of benign lymph nodes was predicted. The performance of the NILS model was assessed in terms of discrimination with the area under the receiver operating characteristic curve (AUC) and calibration, that is, comparison of the observed and predicted event rates of benign axillary nodal status (N0) using calibration slope and intercept. The primary endpoint was axillary nodal status (discrimination, benign [N0] vs. metastatic axillary nodal status [N+]) determined by the NILS model compared to nodal status by definitive pathology. RESULTS: The mean age of the women in the cohort was 65 years, and most of them (93%) had luminal cancers. Approximately three-fourths of the patients had no metastases in SLNB (N0 74% and 73%, respectively). The AUC for the predicted probabilities for the whole cohort was 0.6741 (95% confidence interval: 0.6255-0.7227). More than one in four patients (n = 151, 26%) were identified as candidates for SLNB omission when applying the predefined cut-off for lymph node-negative status from the development cohort. The NILS model showed the best calibration in patients with a predicted high probability of healthy axilla. CONCLUSION: The performance of the NILS model was satisfactory. In approximately every fourth patient, SLNB could potentially be omitted. Considering the shift from postoperatively to preoperatively available predictors in this validation study, we have demonstrated the robustness of the NILS model. The clinical usability of the web interface will be evaluated before its clinical implementation. TRIAL REGISTRATION: Registered in the ISRCTN registry with study ID ISRCTN14341750. Date of registration 23/11/2018.

Noninvasive Staging of Lymph Node Status in Breast Cancer Using Machine Learning: External Validation and Further Model Development.

BACKGROUND: Most patients diagnosed with breast cancer present with a node-negative disease. Sentinel lymph node biopsy (SLNB) is routinely used for axillary staging, leaving patients with healthy axillary lymph nodes without therapeutic effects but at risk of morbidities from the intervention. Numerous studies have developed nodal status prediction models for noninvasive axillary staging using postoperative data or imaging features that are not part of the diagnostic workup. Lymphovascular invasion (LVI) is a top-ranked predictor of nodal metastasis; however, its preoperative assessment is challenging. OBJECTIVE: This paper aimed to externally validate a multilayer perceptron (MLP) model for noninvasive lymph node staging (NILS) in a large population-based cohort (n=18,633) and develop a new MLP in the same cohort. Data were extracted from the Swedish National Quality Register for Breast Cancer (NKBC, 2014-2017), comprising only routinely and preoperatively available documented clinicopathological variables. A secondary aim was to develop and validate an LVI MLP for imputation of missing LVI status to increase the preoperative feasibility of the original NILS model. METHODS: Three nonoverlapping cohorts were used for model development and validation. A total of 4 MLPs for nodal status and 1 LVI MLP were developed using 11 to 12 routinely available predictors. Three nodal status models were used to account for the different availabilities of LVI status in the cohorts and external validation in NKBC. The fourth nodal status model was developed for 80% (14,906/18,663) of NKBC cases and validated in the remaining 20% (3727/18,663). Three alternatives for imputation of LVI status were compared. The discriminatory capacity was evaluated using the validation area under the receiver operating characteristics curve (AUC) in 3 of the nodal status models. The clinical feasibility of the models was evaluated using calibration and decision curve analyses. RESULTS: External validation of the original NILS model was performed in NKBC (AUC 0.699, 95% CI 0.690-0.708) with good calibration and the potential of sparing 16% of patients with node-negative disease from SLNB. The LVI model was externally validated (AUC 0.747, 95% CI 0.694-0.799) with good calibration but did not improve the discriminatory performance of the nodal status models. A new nodal status model was developed in NKBC without information on LVI (AUC 0.709, 95% CI: 0.688-0.729), with excellent calibration in the holdout internal validation cohort, resulting in the potential omission of 24% of patients from unnecessary SLNBs. CONCLUSIONS: The NILS model was externally validated in NKBC, where the imputation of LVI status did not improve the model's discriminatory performance. A new nodal status model demonstrated the feasibility of using register data comprising only the variables available in the preoperative setting for NILS using machine learning. Future steps include ongoing preoperative validation of the NILS model and extending the model with, for example, mammography images.

Tamoxifen-predictive value of gene expression signatures in premenopausal breast cancer: data from the randomized SBII:2 trial.

BACKGROUND: Gene expression (GEX) signatures in breast cancer provide prognostic information, but little is known about their predictive value for tamoxifen treatment. We examined the tamoxifen-predictive value and prognostic effects of different GEX signatures in premenopausal women with early breast cancer. METHODS: RNA from formalin-fixed paraffin-embedded tumor tissue from premenopausal women randomized between two years of tamoxifen treatment and no systemic treatment was extracted and successfully subjected to GEX profiling (n = 437, NanoString Breast Cancer 360™ panel). The median follow-up periods for a recurrence-free interval (RFi) and overall survival (OS) were 28 and 33 years, respectively. Associations between GEX signatures and tamoxifen effect were assessed in patients with estrogen receptor-positive/human epidermal growth factor receptor 2-negative (ER+ /HER2-) tumors using Kaplan-Meier estimates and Cox regression. The prognostic effects of GEX signatures were studied in the entire cohort. False discovery rate adjustments (q-values) were applied to account for multiple hypothesis testing. RESULTS: In patients with ER+/HER2- tumors, FOXA1 expression below the median was associated with an improved effect of tamoxifen after 10 years with regard to RFi (hazard ratio [HR]FOXA1(high) = 1.04, 95% CI = 0.61-1.76, HRFOXA1(low) = 0.30, 95% CI = 0.14-0.67, qinteraction = 0.0013), and a resembling trend was observed for AR (HRAR(high) = 1.15, 95% CI = 0.60-2.20, HRAR(low) = 0.42, 95% CI = 0.24-0.75, qinteraction = 0.87). Similar patterns were observed for OS. Tamoxifen was in the same subgroup most beneficial for RFi in patients with low ESR1 expression (HRRFi ESR1(high) = 0.76, 95% CI = 0.43-1.35, HRRFi, ESR1(low) = 0.56, 95% CI = 0.29-1.06, qinteraction = 0.37). Irrespective of molecular subtype, higher levels of ESR1, Mast cells, and PGR on a continuous scale were correlated with improved 10 years RFi (HRESR1 = 0.80, 95% CI = 0.69-0.92, q = 0.005; HRMast cells = 0.74, 95% CI = 0.65-0.85, q < 0.0001; and HRPGR = 0.78, 95% CI = 0.68-0.89, q = 0.002). For BC proliferation and Hypoxia, higher scores associated with worse outcomes (HRBCproliferation = 1.54, 95% CI = 1.33-1.79, q < 0.0001; HRHypoxia = 1.38, 95% CI = 1.20-1.58, q < 0.0001). The results were similar for OS. CONCLUSIONS: Expression of FOXA1 is a promising predictive biomarker for tamoxifen effect in ER+/HER2- premenopausal breast cancer. In addition, each of the signatures BC proliferation, Hypoxia, Mast cells, and the GEX of AR, ESR1, and PGR had prognostic value, also after adjusting for established prognostic factors. Trial registration This trial was retrospectively registered in the ISRCTN database the 6th of December 2019, trial ID: https://clinicaltrials.gov/ct2/show/ISRCTN12474687 .

Protocol for the T-REX-trial: tailored regional external beam radiotherapy in clinically node-negative breast cancer patients with 1-2 sentinel node macrometastases - an open, multicentre, randomised non-inferiority phase 3 trial.

INTRODUCTION: Modern systemic treatment has reduced incidence of regional recurrences and improved survival in breast cancer (BC). It is thus questionable whether regional radiotherapy (RT) is still beneficial in patients with sentinel lymph node (SLN) macrometastasis. Postoperative regional RT is associated with an increased risk of arm morbidity, pneumonitis, cardiac disease and secondary cancer. Therefore, there is a need to individualise regional RT in relation to the risk of recurrence. METHODS AND ANALYSIS: In this multicentre, prospective randomised trial, clinically node-negative patients with oestrogen receptor-positive, HER2-negative BC and 1-2 SLN macrometastases are eligible. Participants are randomly assigned to receive regional RT (standard arm) or not (intervention arm). Regional RT includes the axilla level I-III, the supraclavicular fossa and in selected patients the internal mammary nodes. Both groups receive RT to the remaining breast. Chest-wall RT after mastectomy is given in the standard arm, but in the intervention arm only in cases of widespread multifocality according to national guidelines. RT quality assurance is an integral part of the trial.The trial aims to include 1350 patients between March 2023 and December 2028 in Sweden and Norway. Primary outcome is recurrence-free survival (RFS) at 5 years. Non-inferiority will be declared if outcome in the de-escalation arm is not >4.5 percentage units below that with regional RT, corresponding to an HR of 1.41 assuming 88% 5-year RFS with standard treatment. Secondary outcomes include locoregional recurrence, overall survival, patient-reported arm morbidity and health-related quality of life. Gene expression analysis and tumour tissue-based studies to identify prognostic and predictive markers for benefit of regional RT are included. ETHICS AND DISSEMINATION: The trial protocol is approved by the Swedish Ethics Authority (Dnr-2022-02178-01, 2022-05093-02, 2023-00826-02, 2023-03035-02). Results will be presented at scientific conferences and in peer-reviewed journals. TRIAL REGISTRATION NUMBER: NCT05634889.

Longitudinal Assessment of Circulating Tumor Cells and Outcome in Small Cell Lung Cancer: A Sub-Study of RASTEN-A Randomized Trial with Low Molecular Weight Heparin.

Circulating tumor cells (CTCs) may provide a liquid biopsy approach to disease monitoring in small cell lung cancer (SCLC), a particularly aggressive tumor subtype. Yet, the prognostic role of CTCs during and after treatment in relation to baseline remains ill-defined. Here, we assessed the value of longitudinal CTC analysis and the potential of low-molecular-weight heparin (LMWH) to reduce CTC abundance in SCLC patients from a randomized trial (RASTEN). Blood samples were collected at baseline, before chemotherapy Cycle 3, and at 2-month follow-up from 42 patients in total, and CTCs were quantified using the FDA-approved CellSearch system. We found a gradual decline in CTC count during and after treatment, independently of the addition of LMWH to standard therapy. Detectable CTCs at baseline correlated significantly to reduced survival compared to undetectable CTCs (unadjusted hazard ratio (HR) of 2.75 (95% CI 1.05-7.20; p = 0.040)). Furthermore, a persistent CTC count at 2-month follow-up was associated with a HR of 4.22 (95% CI 1.20-14.91; p = 0.025). Our findings indicate that persistently detectable CTCs during and after completion of therapy offer further prognostic information in addition to baseline CTC, suggesting a role for CTC in the individualized management of SCLC.

Serum immuno-oncology markers carry independent prognostic information in patients with newly diagnosed metastatic breast cancer, from a prospective observational study.

BACKGROUND: Metastatic breast cancer (MBC) is a challenging disease, and despite new therapies, prognosis is still poor for a majority of patients. There is a clinical need for improved prognostication where immuno-oncology markers can provide important information. The aim of this study was to evaluate serum immuno-oncology markers in MBC patients and their respective relevance for prediction of survival. PATIENTS AND METHODS: We investigated a broad panel of 92 immuno-oncology proteins in serum from 136 MBC patients included in a prospective observational study (NCT01322893) with long-term follow-up. Serum samples were collected before start of systemic therapy and analyzed using multiplex proximity extension assay (Olink Target 96 Immuno-Oncology panel). Multiple machine learning techniques were used to identify serum markers with highest importance for prediction of overall and progression-free survival (OS and PFS), and associations to survival were further evaluated using Cox regression analyses. False discovery rate was then used to adjust for multiple comparisons. RESULTS: Using random forest and random survival forest analyses, we identified the top nine and ten variables of highest predictive importance for OS and PFS, respectively. Cox regression analyses revealed significant associations (P < 0.005) of higher serum levels of IL-8, IL-10 and CAIX with worse OS in multivariable analyses, adjusted for established clinical prognostic factors including circulating tumor cells (CTCs). Similarly, high serum levels of IL-8, IL-10, ADA and CASP8 significantly associated with worse PFS. Interestingly, high serum levels of FasL significantly associated with improved OS and PFS. In addition, CSF-1, IL-6, MUC16, TFNSFR4 and CD244 showed suggestive evidence (P < 0.05) for an association to survival in multivariable analyses. After correction for multiple comparisons, IL-8 still showed strong evidence for correlation to survival. CONCLUSION: To conclude, we found six serum immuno-oncology markers that were significantly associated with OS and/or PFS in MBC patients, independently of other established prognostic factors including CTCs. Furthermore, an additional five serum immuno-oncology markers provided suggestive evidence for an independent association to survival. These findings highlight the relevance of immuno-oncology serum markers in MBC patients and support their usefulness for improved prognostication. Trial registration Clinical Trials (NCT01322893), registered March 25, 2011.

The implementation of NILS: A web-based artificial neural network decision support tool for noninvasive lymph node staging in breast cancer.

Objective: To implement artificial neural network (ANN) algorithms for noninvasive lymph node staging (NILS) to a decision support tool and facilitate the option to omit surgical axillary staging in breast cancer patients with low-risk of nodal metastasis. Methods: The NILS tool is a further development of an ANN prototype for the prediction of nodal status. Training and internal validation of the original algorithm included 15 clinical and tumor-related variables from a consecutive cohort of 800 breast cancer cases. The updated NILS tool included 10 top-ranked input variables from the original prototype. A workflow with four ANN pathways was additionally developed to allow different combinations of missing preoperative input values. Predictive performances were assessed by area under the receiver operating characteristics curves (AUC) and sensitivity/specificity values at defined cut-points. Clinical utility was presented by estimating possible sentinel lymph node biopsy (SLNB) reduction rates. The principles of user-centered design were applied to develop an interactive web-interface to predict the patient's probability of healthy lymph nodes. A technical validation of the interface was performed using data from 100 test patients selected to cover all combinations of missing histopathological input values. Results: ANN algorithms for the prediction of nodal status have been implemented into the web-based NILS tool for personalized, noninvasive nodal staging in breast cancer. The estimated probability of healthy lymph nodes using the interface showed a complete concordance with estimations from the reference algorithm except in two cases that had been wrongly included (ineligible for the technical validation). NILS predictive performance to distinguish node-negative from node-positive disease, also with missing values, displayed AUC ranged from 0.718 (95% CI, 0.687-0.748) to 0.735 (95% CI, 0.704-0.764), with good calibration. Sensitivity 90% and specificity 34% were demonstrated. The potential to abstain from axillary surgery was observed in 26% of patients using the NILS tool, acknowledging a false negative rate of 10%, which is clinically accepted for the standard SLNB technique. Conclusions: The implementation of NILS into a web-interface are expected to provide the health care with decision support and facilitate preoperative identification of patients who could be good candidates to avoid unnecessary surgical axillary staging.

Low levels of WRAP53 predict decreased efficacy of radiotherapy and are prognostic for local recurrence and death from breast cancer: a long-term follow-up of the SweBCG91RT randomized trial.

Downregulation of the DNA repair protein WD40-encoding RNA antisense to p53 (WRAP53) has been associated with radiotherapy resistance and reduced cancer survival. The aim of this study was to evaluate WRAP53 protein and RNA levels as prognostic and predictive markers in the SweBCG91RT trial, in which breast cancer patients were randomized for postoperative radiotherapy. Using tissue microarray and microarray-based gene expression, 965 and 759 tumors were assessed for WRAP53 protein and RNA levels, respectively. Correlation with local recurrence and breast cancer-related death was assessed for prognosis, and the interaction between WRAP53 and radiotherapy in relation to local recurrence was assessed for radioresistance prediction. Tumors with low WRAP53 protein levels had a higher subhazard ratio (SHR) for local recurrence [1.76 (95% CI 1.10-2.79)] and breast cancer-related death [1.55 (1.02-2.38)]. Low WRAP53 RNA levels were associated with almost a three-fold decreased effect of radiotherapy in relation to ipsilateral breast tumor recurrence [IBTR; SHR 0.87 (95% CI 0.44-1.72)] compared with high RNA levels [0.33 (0.19-0.55)], with a significant interaction (P = 0.024). In conclusion, low WRAP53 protein is prognostic for local recurrence and breast cancer-related death. Low WRAP53 RNA is a potential marker for radioresistance.

Gene expression in metastatic breast cancer-patterns in primary tumors and metastatic tissue with prognostic potential.

Background: Metastatic breast cancer (MBC) is the main cause of breast cancer-related death. The outcome of MBC varies, and there is a lack of biomarkers to aid in prognostication. The primary aim of this study was to evaluate the prognostic value of gene expression (GEX) signatures in the primary tumor (PT) and distant metastasis (DM) for progression-free survival (PFS) and overall survival (OS). The secondary aim was to describe GEX changes through MBC evolution and to identify MBC subtypes. Methods: RNA was extracted from the PT, lymph node metastasis (LNM), and DM from MBC patients in a prospective observational study (n = 142; CTC-MBC NCT01322893) and was subjected to GEX analysis retrospectively using the NanoString Breast Cancer 360™ panel. 31 continuous GEX variables in DMs and PTs were analyzed for PFS and OS by Cox regression analysis and Kaplan-Meier estimates. Multivariable Cox regressions were adjusted for number of DM sites and CTCs, visceral metastasis, ECOG status, age at MBC diagnosis and, in additional analyses, PAM50 subtype. Differential GEX analyses and Euclidean distances were used to describe subgroup differences and visualize within-patient heterogeneity. Results: Compared to DM GEX, GEX of the PT was at least equally useful for predicting MBC outcome. The strongest marker for a favorable PFS, both when expressed in the PT and the DM was AR, even after adjustment for prognostic markers including PAM50. GEX signatures related to hormone responsiveness, including ESR1, FOXA1, PGR, and AR were favorable prognostic markers, and the p53 signature was unfavorable for PFS when expressed in PT or DM. The previously published PAM50MET signature was prognostic for both PFS and OS. We established five distinct DM GEX profiles where two associated with liver and bone metastases, respectively. Finally, we identified four DM GEX profiles able to identify MBCs with poor OS in this cohort. Conclusion: GEX of both DM and PT are useful in MBC prognostication. GEX of AR adds prognostic information for MBC. Our descriptive analyses illuminate the biological differences between MBCs in relation to outcome and metastatic site.

One-year recovery from breast cancer: Importance of tumor and treatment-related factors, resilience, and sociodemographic factors for health-related quality of life.

Aim: This study investigated the changes in health-related quality of life from diagnosis to 1 year after diagnosis in breast cancer (BC) patients and the influence of clinical, psychological, and sociodemographic variables. An additional aim was to explore the mediating and moderating effects of resilience on changes in health-related quality of life. Methods: A longitudinal population-based study was conducted in southern Sweden. Newly diagnosed BC patients filled in measures of health-related quality of life, resilience, and sociodemographic variables at diagnosis (N = 980) and 1 year post-diagnosis (N = 780). Clinical variables were extracted from the Swedish national breast cancer quality registry. Mixed-model analyses were performed. Results: Most health-related quality of life outcomes declined from diagnosis to 1 year post-diagnosis. Role limitations due to emotional problems remained the same, whereas mental health improved. Lower health-related quality of life outcomes were associated with symptomatic detection and axillary dissection. Patients with a higher TNM stage and histologic grade and estrogen receptor (ER)-negative and human epidermal growth factor 2 (HER2)-positive status, who received chemotherapy, antibody therapy, or bisphosphonate therapy, had a steeper decline in outcomes. Changes in resilience were positively associated with all outcomes but did not mediate or moderate changes in any. Resilience at baseline moderated changes in bodily pain, vitality, and mental health, with higher baseline resilience being associated with a steeper decline, possibly due to floor or ceiling effects. Patients with lower socioeconomic status, educational level, and older age had a lower health-related quality of life. Conclusion: Physical health-related quality of life among breast cancer patients declined 1 year post-diagnosis, whereas mental health-related quality of life improved. Low resilient patients may be especially vulnerable at diagnosis. Biopsychosocial assessment at diagnosis can help identify patients who may require additional support. A multidimensional treatment plan should be started early to help overcome the problems in everyday activities.

RNA sequencing-based single sample predictors of molecular subtype and risk of recurrence for clinical assessment of early-stage breast cancer.

Multigene assays for molecular subtypes and biomarkers can aid management of early invasive breast cancer. Using RNA-sequencing we aimed to develop single-sample predictor (SSP) models for clinical markers, subtypes, and risk of recurrence (ROR). A cohort of 7743 patients was divided into training and test set. We trained SSPs for subtypes and ROR assigned by nearest-centroid (NC) methods and SSPs for biomarkers from histopathology. Classifications were compared with Prosigna in two external cohorts (ABiM, n = 100 and OSLO2-EMIT0, n = 103). Prognostic value was assessed using distant recurrence-free interval. Agreement between SSP and NC for PAM50 (five subtypes) was high (85%, Kappa = 0.78) for Subtype (four subtypes) very high (90%, Kappa = 0.84) and for ROR risk category high (84%, Kappa = 0.75, weighted Kappa = 0.90). Prognostic value was assessed as equivalent and clinically relevant. Agreement with histopathology was very high or high for receptor status, while moderate for Ki67 status and poor for Nottingham histological grade. SSP and Prosigna concordance was high for subtype (OSLO-EMIT0 83%, Kappa = 0.73 and ABiM 80%, Kappa = 0.72) and moderate and high for ROR risk category (68 and 84%, Kappa = 0.50 and 0.70, weighted Kappa = 0.70 and 0.78). Pooled concordance for emulated treatment recommendation dichotomized for chemotherapy was high (85%, Kappa = 0.66). Retrospective evaluation suggested that SSP application could change chemotherapy recommendations for up to 17% of postmenopausal ER+/HER2-/N0 patients with balanced escalation and de-escalation. Results suggest that NC and SSP models are interchangeable on a group-level and nearly so on a patient level and that SSP models can be derived to closely match clinical tests.

The implementation of a noninvasive lymph node staging (NILS) preoperative prediction model is cost effective in primary breast cancer.

PURPOSE: The need for sentinel lymph node biopsy (SLNB) in clinically node-negative (cN0) patients is currently questioned. Our objective was to investigate the cost-effectiveness of a preoperative noninvasive lymph node staging (NILS) model (an artificial neural network model) for predicting pathological nodal status in patients with cN0 breast cancer (BC). METHODS: A health-economic decision-analytic model was developed to evaluate the utility of the NILS model in reducing the proportion of cN0 patients with low predicted risk undergoing SLNB. The model used information from a national registry and published studies, and three sensitivity/specificity scenarios of the NILS model were evaluated. Subgroup analysis explored the outcomes of breast-conserving surgery (BCS) or mastectomy. The results are presented as cost (€) and quality-adjusted life years (QALYs) per 1000 patients. RESULTS: All three scenarios of the NILS model reduced total costs (-€93,244 to -€398,941 per 1000 patients). The overall health benefit allowing for the impact of SLNB complications was a net health gain (7.0-26.9 QALYs per 1000 patients). Sensitivity analyses disregarding reduced quality of life from lymphedema showed a small loss in total health benefits (0.4-4.0 QALYs per 1000 patients) because of the reduction in total life years (0.6-6.5 life years per 1000 patients) after reduced adjuvant treatment. Subgroup analyses showed greater cost reductions and QALY gains in patients undergoing BCS. CONCLUSION: Implementing the NILS model to identify patients with low risk for nodal metastases was associated with substantial cost reductions and likely overall health gains, especially in patients undergoing BCS.

PAM50 subtyping and ROR score add long-term prognostic information in premenopausal breast cancer patients.

PAM50 intrinsic subtyping and risk of recurrence (ROR) score are approved for risk profiling in postmenopausal women. We aimed to examine their long-term prognostic value in terms of breast cancer-free interval (BCFi) and overall survival (OS) (n = 437) in premenopausal women randomised to 2 years of tamoxifen versus no systemic treatment irrespective of hormone-receptor status. Intrinsic subtyping added independent prognostic information in patients with oestrogen receptor-positive/human epidermal growth factor 2-negative tumours for BCFi and OS after maximum follow-up (overall P-value 0.02 and 0.006, respectively) and those with high versus low ROR had worse prognosis (maximum follow-up: hazard ratio (HR)BCFi: 1.70, P = 0.04). The prognostic information by ROR was similar regarding OS and in multivariable analysis. These results support that PAM50 subtyping and ROR score provide long-term prognostic information in premenopausal women. Moreover, tamoxifen reduced the incidence of breast cancer events only in patients with Luminal APAM50 tumours (0-10 years: HRBCFi(Luminal A): 0.41, HRBCFi(Luminal B): 1.19, Pinteraction = 0.02).Trial registration: This trial is registered in the ISRCTN database, trial ID: ISRCTN12474687.

Circulating Levels of the Cardiovascular Biomarkers ST2 and Adrenomedullin Predict Outcome within a Randomized Phase III Lung Cancer Trial (RASTEN).

Cardiovascular comorbidity is common in small cell lung cancer (SCLC) and may significantly affect treatment tolerability and patient outcome. Still, there are no established biomarkers for objective and dynamic assessment as a tool for improved treatment decisions. We have investigated circulating levels of midregional-pro-adrenomedullin (MR-proADM), midregional-pro-atrial-natriuretic peptide (MR-proANP), copeptin (surrogate for vasopressin) and suppression-of-tumorigenicity-2 (ST2), all known to correlate with various aspects of cardiovascular function, in a SCLC cohort (N = 252) from a randomized, controlled trial (RASTEN). For all measured biomarkers, protein levels were inversely associated with survival, particularly with ST2 and MR-proADM, where the top versus bottom quartile was associated with an adjusted hazard ratio of 2.40 (95% CI 1.44−3.98; p = 0.001) and 2.18 (95% CI 1.35−3.51; p = 0.001), respectively, in the entire cohort, and 3.43 (95% CI 1.73−6.79; p < 0.001) and 3.49 (95% CI 1.84−6.60; p < 0.001), respectively, in extensive disease patients. A high combined score of MR-proADM and ST2 was associated with a significantly reduced median OS of 7.0 months vs. 14.9 months for patients with a low combined score. We conclude that the cardiovascular biomarkers MR-proADM and ST2 strongly correlate with survival in SCLC, warranting prospective studies on the clinical utility of MR-proADM and ST2 for improved, individualized treatment decisions.

The NILS Study Protocol: A Retrospective Validation Study of an Artificial Neural Network Based Preoperative Decision-Making Tool for Noninvasive Lymph Node Staging in Women with Primary Breast Cancer (ISRCTN14341750).

Newly diagnosed breast cancer (BC) patients with clinical T1-T2 N0 disease undergo sentinel-lymph-node (SLN) biopsy, although most of them have a benign SLN. The pilot noninvasive lymph node staging (NILS) artificial neural network (ANN) model to predict nodal status was published in 2019, showing the potential to identify patients with a low risk of SLN metastasis. The aim of this study is to assess the performance measures of the model after a web-based implementation for the prediction of a healthy SLN in clinically N0 BC patients. This retrospective study was designed to validate the NILS prediction model for SLN status using preoperatively available clinicopathological and radiological data. The model results in an estimated probability of a healthy SLN for each study participant. Our primary endpoint is to report on the performance of the NILS prediction model to distinguish between healthy and metastatic SLNs (N0 vs. N+) and compare the observed and predicted event rates of benign SLNs. After validation, the prediction model may assist medical professionals and BC patients in shared decision making on omitting SLN biopsies in patients predicted to be node-negative by the NILS model. This study was prospectively registered in the ISRCTN registry (identification number: 14341750).

High CYP27A1 expression is a biomarker of favorable prognosis in premenopausal patients with estrogen receptor positive primary breast cancer.

27-hydroxycholesterol (27HC), synthesized from cholesterol by the enzyme CYP27A1, differentially impacts estrogen receptor positive (ER+) breast cancer (BC) cell growth depending on estrogen levels. This study examined the association between CYP27A1 expression and prognosis in a cohort of 193 premenopausal patients with lymph node-negative primary BC with limited exposure to adjuvant systemic cancer treatments. In multivariable analyses among patients with ER+ tumors, high CYP27A1 protein and mRNA expressions were associated with four- and eight-fold reductions in the incidence of distant recurrence-free survival events: HRadj = 0.26, 95% CI = 0.07-0.93 and HRadj = 0.13, 95% CI = 0.03-0.60, respectively. In vitro studies revealed that 27HC treatment potently inhibited ER+ BC cell proliferation under lipid-depleted conditions regardless of estradiol levels, transcriptionally mediated through the downregulation of ER signaling with a concomitant upregulation of cholesterol export. Importantly, if validated, these results may have implications for adjuvant treatment decisions in premenopausal patients, especially when de-escalation of therapy is being considered.

Psychological Resilience and Health-Related Quality of Life in 418 Swedish Women with Primary Breast Cancer: Results from a Prospective Longitudinal Study.

Psychological resilience is considered a major protective psychological mechanism that enables a person to successfully handle significant adversities, e.g., a cancer diagnosis. Higher levels of resilience have been associated with higher levels of health-related quality of life (HRQoL) in breast cancer (BC) patients, but research examining the longitudinal process of resilience is limited. The aim of this population-based longitudinal study was to investigate resilience and HRQoL from diagnosis to one year later in 418 Swedish women with primary BC. Resilience was measured with the Connor-Davidson Resilience Scale 25, and HRQoL was measured with the Short Form Health Survey. The participants responded to questions regarding demographic and study-specific variables. Clinicopathological variables were collected from the Swedish National Quality Register for Breast Cancer. The mean score for resilience was 70.6 (standard deviation, SD = 13.0) at diagnosis and 68.9 (SD = 14.0) one year later, p < 0.001. The level of trust in the treatment and financial situation demonstrated the greatest association with the change in resilience levels. No oncological treatment modality was associated with a change in resilience levels. HRQoL decreased over time in the cohort. Resilience was positively associated with HRQoL at one year post diagnosis, which demonstrates that resilience is an important factor in maintaining HRQoL.

PAM50 Intrinsic Subtype Profiles in Primary and Metastatic Breast Cancer Show a Significant Shift toward More Aggressive Subtypes with Prognostic Implications.

BACKGROUND: PAM50 breast cancer intrinsic subtyping adds prognostic information in early breast cancer; however, the role in metastatic disease is unclear. We aimed to identify PAM50 subtypes in primary tumors (PTs) and metastases to outline subtype changes and their prognostic role. METHODS: RNA was isolated from PTs, lymph node metastases (LNMs), and distant metastases (DMs) in metastatic breast cancer patients (n = 140) included in a prospective study (NCT01322893). Gene expression analyses were performed using the Breast Cancer 360 (BC360) assay from Nano-String. The subtype shifts were evaluated using McNemar and symmetry tests, and clinical outcomes were evaluated with log-rank tests and Cox regression. RESULTS: The PAM50 subtype changed in 25/59 of paired samples between PTs and LNMs (Psymmetry = 0.002), in 31/61 between PTs and DMs (Psymmetry < 0.001), and in 16/38 between LNMs and DMs (Psymmetry = 0.004). Shifts toward subtypes with worse outcomes were the most common. Patients with shifts from the luminal PT to non-luminal DM subtypes had worse progression-free survival compared to patients with a stable subtype (hazard ratio (HR): 2.3; 95% confidence interval (CI): 1.14-4.68, p = 0.02). CONCLUSION: Strong evidence of PAM50 subtype shifts toward unfavorable subtypes were seen between PTs and metastatic samples. For patients with a shift in subtype from luminal PT to non-luminal DM, a worse prognosis was noted.