A radiomic model to classify response to neoadjuvant chemotherapy in breast cancer

BACKGROUND

Medical image analysis has evolved to facilitate the development of methods for high-throughput extraction of quantitative features that can potentially contribute to the diagnostic and treatment paradigm of cancer. There is a need for further improvement in the accuracy of predictive markers of response to neo-adjuvant chemotherapy (NAC). The aim of this study was to develop a radiomic classifier to enhance current approaches to predicting the response to NAC breast cancer.

METHODS

Data on patients treated for breast cancer with NAC prior to surgery who had a pre-NAC dynamic contrast enhanced breast MRI were included. Response to NAC was assessed using the Miller-Payne system on the excised tumor. Tumor segmentation was carried out manually under the supervision of a consultant breast radiologist. Features were selected using least absolute shrinkage selection operator regression. A support vector machine learning model was used to classify response to NAC.

RESULTS

74 patients were included. Patients were classified as having a poor response to NAC (reduction in cellularity < 90%, n = 44) and an excellent response (> 90% reduction in cellularity, n = 30). 4 radiomics features (discretized kurtosis, NGDLM contrast, GLZLM_SZE and GLZLM_ZP) were identified as pertinent predictors of response to NAC. A SVM model using these features stratified patients into poor and excellent response groups producing an AUC of 0.75. Addition of estrogen receptor status improved the accuracy of the model with an AUC of 0.811.

CONCLUSION

This study identified a radiomic classifier incorporating 4 radiomics features to augment subtype based classification of response to NAC in breast cancer.

Preoperative Breast Magnetic Resonance Imaging as a Predictor of Response to Neoadjuvant Chemotherapy

Introduction:

The ability to accurately predict pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) in breast cancer would improve patient selection for specific treatment strategies, would provide important information for patients to aid in the treatment selection process, and could potentially avoid the need for more extensive surgery. The diagnostic performance of magnetic resonance imaging (MRI) in predicting pCR has previously been studied, with mixed results. Magnetic resonance imaging performance may also be influenced by tumour and patient factors.

Methods:

Eighty-seven breast cancer patients who underwent NAC were studied. Pre-NAC and post-NAC MRI findings were compared with pathologic findings postsurgical excision. The impact of patient and tumour characteristics on MRI accuracy was evaluated.

Results:

The mean (SD) age of participants was 48.7 (10.3) years. The rate of pCR based on post-NAC MRI was 19.5% overall (19/87). The sensitivity, specificity, positive predictive value (PPV), negative predictive value, and accuracy in predicting pCR were 52.9%, 77.1%, 36.0%, 87.1%, and 72.4%, respectively. Positive predictive value was the highest in nonluminal versus Luminal A disease (45.0% vs 25.0%, P < .001), with higher rates of false positivity in nonluminal subtypes (P = .002). Tumour grade, T category, and histological subtype were all independent predictors of MRI accuracy regarding post-NAC tumour size.

Conclusion:

Magnetic resonance imaging alone is insufficient to accurately predict pCR in breast cancer patients post-NAC. Magnetic resonance imaging predictions of pCR are more accurate in nonluminal subtypes. Tumour grade, T category, and histological subtype should be considered when evaluating post-NAC tumour sizes.

The opportunity cost of arthroplasty training in orthopaedic surgery

INTRODUCTION

Training the next generation of surgeons is a crucial role fulfilled by consultant orthopaedic surgeons. However we are increasingly constrained by limited time and resources. We sought to compare operative time and length of stay (LOS) for total hip and total knee arthroplasties (THA, TKA) performed by a consultant orthopaedic surgeon with those performed by supervised trainees.

MATERIALS AND METHODS

A prospective database of arthroplasty procedures performed from 2015 to 2018 was collated. Primary surgeon grade was recorded. Patient demographics, ASA grade, LOS and operative time were recorded. For THA both cemented and uncemented arthroplasties were used. SPSS version 23 was used for statistical analysis.

RESULTS

394 arthroplasty procedures were carried out during the study period. Trainee surgeons performed a high proportion of both THA (53.2%, n = 123) and TKA (44.8%, n = 73) surgeries. Trainees performed 57% of cemented THA procedures. LOS did not differ between consultant and trainee surgeons for THA (5.9 ± 4.8 days) or TKA (5.6 ± 4.1 days). Age had a significant effect on LOS (p < 0.001). For THA the mean operative time for trainees was 90.3 ± 19.23 min, 18.2 min longer than the consultant group. For TKA the mean operative time was 89.06 ± 18.87 min for trainees, 24.4 min longer than the consultant group.

DISCUSSION

At our institution trainee surgeons can be expected to take between 18 and 24 min longer to perform arthroplasty procedures. This should be factored into resource planning, as the training of orthopaedic surgeons is crucial to sustaining and improving health service provision.

Clinicopathological response to neoadjuvant therapies and pathological complete response as a biomarker of survival in human epidermal growth factor receptor-2 enriched breast cancer - A retrospective cohort study

BACKGROUND

Human epidermal growth factor receptor-2 (HER2) is overexpressed in 20-25% of breast cancers. Complete eradication of disease following neoadjuvant therapies and chemotherapy has been referred to as pathological complete response (pCR).

AIMS

To determine clinicopathological predictors of pCR to neoadjuvant therapies and to evaluate pCR as a surrogate to enhanced survival.

METHODS

Consecutive female patients with HER2 positive (HER+) breast cancer managed surgically in a single institution between 2005 and 2015 were included. Descriptive statistics and binary logistic regression were used to determine predictors of pCR. Appraisal of pCR as a predictor of survival was performed using Kaplan-Meier curves and Cox regression analysis.

RESULTS

451 patients were included with a mean age of 56.6 ± 13.4 years (range 23-95). Disease-free (DFS) and overall survival (OS) was 82.3% (371/451) and 82.6% (376/451) respectively with a median follow-up of 108.0 months (range 3-184.0). 118 were treated in the neoadjuvant setting (26.2%): tumour size <50 mm (Odds Ratio (OR): 12.156, P = 0.023) and progesterone receptor negativity (OR: 2.762, P = 0.008) independently predicted breast pCR, while ductal carcinoma (OR: 3.203, P = 0.030) and grade 3 disease (OR: 2.788, P = 0.018) predicted axillary pCR. Both breast and axillary pCR predicted enhanced DFS (Hazard Ratio (HR): 0.470 & HR: 0.449) and OS (HR: 0.383 & HR: 0.307). Axillary pCR independently predicted improved OS (HR: 0.326).

CONCLUSION

pCR is sensitive biomarker and surrogate to survival outcomes in HER2+ breast cancer. Patients likely to achieve pCR may be predicted from traditional clinicopathological characteristics and molecular parameters.

C-Reactive Protein-Lymphocyte Ratio Identifies Patients at Low Risk for Major Morbidity after Oesophagogastric Resection for Cancer

INTRODUCTION

Complications following oesophagogastric surgery have significant implications for patient recovery.

OBJECTIVE

identify cost-effective biomarkers which can predict morbidity.

METHODS

Analysis of all upper gastrointestinal resections in Galway University Hospital from 2014 to 2018 was performed. The ability of C-reactive protein (CRP), neutrophil-lymphocyte ratio (NLR), and CRP-lymphocyte ratio (CLR) to predict morbidity, including anastomotic leak (AL), was assessed and compared.

RESULTS

Seventy-one oesophagectomies and 77 gastrectomies were performed. There were 2 (1%) 30-day mortalities and 83 (56%) morbidities of which 30 (20%) were of Clavien-Dindo grade 3 or higher. The rate of major morbidity within the oesophagectomy cohort was 27% and was 14% in the gastrectomy cohort. There were 11 (7%) ALs, 7 in the oesophagectomy cohort, and 4 in the gastrectomy cohort. From post-operative day (POD) 2 onwards, CRP could predict AL (POD2 AUC = 0.705, p = 0.025; POD3 AUC = 0.757, p = 0.005, POD4 AUC = 0.811, p = 0.001; and POD5 AUC = 0.824, p = 0.001). CLR predicted AL on POD2 onwards (POD2 AUC = 0.722, p = 0.005; POD3 AUC = 0.736, p = 0.01; POD4 AUC = 0.775, p = 0.003; and POD5 AUC = 0.817, p = 0.001). CRP level of 218 mg/dL and CLR level of 301 at POD 2 generated negative predictive values of 97 and 98%, respectively, for AL. Post-operative NLR did not display sufficient discriminatory ability for the outcomes.

CONCLUSION

CRP and CLR are reliable negative predictors of major morbidity, including AL, after oesophagogastric resection. Their use can inform patient intervention and recovery.

Serial CRP levels following oesophagectomy: a marker for anastomotic dehiscence

BACKGROUND

Following oesophagectomy, the most concerning complication is that of anastomotic leak (AL). Prompt diagnosis and intervention are crucial to facilitate an optimal outcome. Other complications, particularly respiratory, are not infrequent. Early identification of AL versus other sources of the inflammatory response can be problematic.

AIMS

To evaluate the role of serial CRP as a prognosticator for oesophagogastric AL.

METHODS

All oesophagectomies carried out at our institution from 2010 to 2017 were included. Serial C-reactive protein (CRP) and white cell count (WCC) were recorded pre-operatively and on each consecutive day up to day 10 post-op. All complications were recorded and the timing of diagnosis compared with serial CRP and WCC measurements to determine any correlation.

RESULTS

One hundred and two patients underwent oesophagectomy (84 male, 18 female) with a mean age of 62.5 years (± 9.8). Forty-seven patients developed post-operative complications, with pulmonary (n = 28) the most common. There were 5 cases of AL. Patients in the AL group (n = 5) had a significantly higher mean CRP compared to those who did not develop AL (n = 97) pre-operatively (50 vs. 14, p = 0.046), on post-op day 3 (300 vs. 218, p = 0.02) and on post-op day 4 (279 vs. 184, p = 0.009). There was no significant difference in mean daily CRP between patients with pulmonary complications (PC, n = 29) and those who did not develop complications (NC, n = 54).

CONCLUSIONS

Elevated CRP may be a useful marker in facilitating the prompt diagnosis of AL following oesophagectomy. Serial CRP may not contribute to identifying lower respiratory tract infections, partly as a result of the pro-inflammatory response following surgery.

Circulating microRNAs miR-331 and miR-195 differentiate local luminal a from metastatic breast cancer

BACKGROUND

Breast cancer is the leading cause of cancer related death in women, with metastasis the principle cause of mortality. New non-invasive prognostic markers are needed for the early detection of metastasis, facilitating treatment decision optimisation. MicroRNA (miRNA) are small, non-coding RNAs regulating gene expression and involved in many cellular processes, including metastasis. As biomarkers, circulating miRNAs (in blood) hold great promise for informing diagnosis or monitoring treatment responses.

METHODS

Plasma extracted RNA from age matched local Luminal A (n = 4) or metastatic disease (n = 4) were profiled using Next Generation Sequencing. Selected differentially expressed miRNA were validated on a whole blood extracted miRNA cohort [distant metastatic disease (n = 22), local disease (n = 31), healthy controls (n = 21)]. Area Under the Curve (AUC) in Receiver Operating Characteristic (ROC) analyses was performed.

RESULTS

Of 4 miRNA targets tested (miR-181a, miR-329, miR-331, miR-195), mir-331 was significantly over-expressed in patients with metastatic disease, compared to patients with local disease (p < 0.001) or healthy controls (p < 0.001). miR-195 was significantly under-expressed in patients with metastatic disease, compared to patients with local disease (p < 0.001) or healthy controls (p = 0.043). In combination, miR-331 and miR-195 produced an AUC of 0.902, distinguishing metastatic from local breast cancer.

CONCLUSIONS

We identified and validated two circulating miRNAs differentiating local Luminal A breast cancers from metastatic breast cancers. Further investigation will reveal the molecular role of these miRNAs in metastasis, and determine if they are subtype specific. This work demonstrates the ability of circulating miRNA to identify metastatic disease, and potentially inform diagnosis or treatment effectiveness.

Role of micro-RNAs in breast cancer surgery

BACKGROUND

The management of breast cancer has changed dramatically in the molecular era. Micro-RNAs can contribute to multiple facets of cancer surgery.

METHODS

This narrative review, based on years of research on the role of micro-RNAs, focused on the potential of these small, robust RNAs to influence all aspects of breast cancer surgery.

RESULTS

Micro-RNAs have a potential role as biomarkers in the diagnosis, prognosis and evaluation of response to therapy in breast cancer. They may also contribute to future therapeutic strategies.

CONCLUSION

The molecular era has changed understanding of cancer. Micro-RNAs have the potential for use in personalized cancer strategies.