The association between methods of biopsy and survival following breast cancer: A hospital registry based cohort study

Correlations of Imaging and Therapy in Breast Cancer Based on Molecular Patterns: An Important Issue in the Diagnosis of Breast Cancer

Breast cancer is a global health issue affecting countries worldwide, imposing a significant economic burden due to expensive treatments and medical procedures, given the increasing incidence. In this review, our focus is on exploring the distinct imaging features of known molecular subtypes of breast cancer, underlining correlations observed in clinical practice and reported in recent studies. The imaging investigations used for assessment include screening modalities such as mammography and ultrasonography, as well as more complex investigations like MRI, which offers high sensitivity for loco-regional evaluation, and PET, which determines tumor metabolic activity using radioactive tracers. The purpose of this review is to provide a better understanding as well as a revision of the imaging differences exhibited by the molecular subtypes and histopathological types of breast cancer.

Minimally invasive biopsy-based diagnostics in support of precision cancer medicine

Precision cancer medicine (PCM) to support the treatment of solid tumors requires minimally invasive diagnostics. Here, we describe the development of fine-needle aspiration biopsy-based (FNA) molecular cytology which will be increasingly important in diagnostics and adaptive treatment. We provide support for FNA-based molecular cytology having a significant potential to replace core needle biopsy (CNB) as a patient-friendly potent technique for tumor sampling for various tumor types. This is not only because CNB is a more traumatic procedure and may be associated with more complications compared to FNA-based sampling, but also due to the recently developed molecular methods used with FNA. Recent studies show that image-guided FNA in combination with ultrasensitive molecular methods also offers opportunities for characterization of the tumor microenvironment which can aid therapeutic decisions. Here we provide arguments for an increased implementation of molecular FNA-based sampling as a patient-friendly diagnostic method, which may, due to its repeatability, facilitate regular sampling that is needed during different treatment lines, to provide tumor information, supporting treatment decisions, shortening lead times in healthcare, and benefit healthcare economics.

A Comparison of the Prognostic Effects of Fine Needle Aspiration and Core Needle Biopsy in Patients with Breast Cancer: A Nationwide Multicenter Prospective Registry

(1) Background: Breast core needle biopsy (CNB) is preferred over fine needle aspiration (FNA) as it has higher sensitivity and specificity and enables immunohistochemical evaluation. However, breast FNA remains widely used because of its low cost, minimally invasive nature, and quick results. Studies analyzing the effects of each test on the prognoses of patients with breast cancer are scarce and controversial, and the criteria for test selection remain unknown. (2) Methods: This study included adult female patients who underwent breast cancer surgery at 102 general hospitals. The trend of breast biopsies over time was analyzed, and the prognoses of patients with breast cancer who underwent CNB and FNA were compared. (3) Results: This study included 73,644 patients who underwent FNA (n = 8027) and CNB (n = 65,617). A multivariate Cox regression analysis showed that patients diagnosed using FNA had significantly worse overall survival (OS) and breast-cancer-specific survival (BCSS) than those diagnosed using CNB. In the subgroup analysis, patients with breast imaging reporting and data system (BI-RADS) 5 lesions, palpable tumors, or centrally located tumors had significantly worse OS and BCSS with FNA than with CNB. (4) Conclusions: CNB should be performed preferentially instead of FNA in patients with BI-RADS 5 lesions and nonpalpable or centrally located tumors.

Development and validation of a radiomic nomogram based on pretherapy dual-energy CT for distinguishing adenocarcinoma from squamous cell carcinoma of the lung

Objective

Based on pretherapy dual-energy computed tomography (DECT) images, we developed and validated a nomogram combined with clinical parameters and radiomic features to predict the pathologic subtypes of non-small cell lung cancer (NSCLC) - adenocarcinoma (ADC) and squamous cell carcinoma (SCC).

Methods

A total of 129 pathologically confirmed NSCLC patients treated at the Second Affiliated Hospital of Nanchang University from October 2017 to October 2021 were retrospectively analyzed. Patients were randomly divided in a ratio of 7:3 (n=90) into training and validation cohorts (n=39). Patients' pretherapy clinical parameters were recorded. Radiomics features of the primary lesion were extracted from two sets of monoenergetic images (40 keV and 100 keV) in arterial phases (AP) and venous phases (VP). Features were selected successively through the intra-class correlation coefficient (ICC) and the least absolute shrinkage and selection operator (LASSO). Multivariate logistic regression analysis was then performed to establish predictive models. The prediction performance between models was evaluated and compared using the receiver operating characteristic (ROC) curve, DeLong test, and Akaike information criterion (AIC). A nomogram was developed based on the model with the best predictive performance to evaluate its calibration and clinical utility.

Results

A total of 87 ADC and 42 SCC patients were enrolled in this study. Among the five constructed models, the integrative model (AUC: Model 4 = 0.92, Model 5 = 0.93) combining clinical parameters and radiomic features had a higher AUC than the individual clinical models or radiomic models (AUC: Model 1 = 0.84, Model 2 = 0.79, Model 3 = 0.84). The combined clinical-venous phase radiomics model had the best predictive performance, goodness of fit, and parsimony; the area under the ROC curve (AUC) of the training and validation cohorts was 0.93 and 0.90, respectively, and the AIC value was 60.16. Then, this model was visualized as a nomogram. The calibration curves demonstrated it's good calibration, and decision curve analysis (DCA) proved its clinical utility.

Conclusion

The combined clinical-radiomics model based on pretherapy DECT showed good performance in distinguishing ADC and SCC of the lung. The nomogram constructed based on the best-performing combined clinical-venous phase radiomics model provides a relatively accurate, convenient and noninvasive method for predicting the pathological subtypes of ADC and SCC in NSCLC.

Theory and Practice of Integrating Machine Learning and Conventional Statistics in Medical Data Analysis

The practice of medical decision making is changing rapidly with the development of innovative computing technologies. The growing interest of data analysis with improvements in big data computer processing methods raises the question of whether machine learning can be integrated with conventional statistics in health research. To help address this knowledge gap, this paper presents a review on the conceptual integration between conventional statistics and machine learning, focusing on the health research. The similarities and differences between the two are compared using mathematical concepts and algorithms. The comparison between conventional statistics and machine learning methods indicates that conventional statistics are the fundamental basis of machine learning, where the black box algorithms are derived from basic mathematics, but are advanced in terms of automated analysis, handling big data and providing interactive visualizations. While the nature of both these methods are different, they are conceptually similar. Based on our review, we conclude that conventional statistics and machine learning are best to be integrated to develop automated data analysis tools. We also strongly believe that machine learning could be explored by health researchers to enhance conventional statistics in decision making for added reliable validation measures.

Survival Outcomes of Patients With Breast Cancer Diagnosed Using Vacuum-Assisted Biopsy: A Nationwide Study From the Korean Breast Cancer Society

PURPOSE

Breast cancer is mainly diagnosed using core needle biopsy (CNB), although other biopsy methods, including vacuum-assisted biopsy (VAB), may also be used. We compared differences in clinical characteristics and prognoses of patients with breast cancer according to biopsy methods used for diagnosis.

METHODS

A total of 98,457 patients who underwent various biopsy methods (CNB, fine-needle aspiration [FNA], VAB, and excisional biopsy) for diagnosing breast cancer were recruited. Using CNB as a reference, related clinicopathological factors and prognostic differences between biopsy methods were analyzed retrospectively using large-scale data from the Korean Breast Cancer Society Registration System. The associations between biopsy methods and clinicopathological factors were compared using multinomial logistic regression analysis, and the prognoses of patients undergoing the different biopsy methods, as breast cancer-specific survival (BCSS) and overall survival (OS), were compared using the Kaplan-Meier method and Cox proportional hazard model.

RESULTS

Univariate and multivariate analyses showed that unlike FNA, both VAB and excisional biopsy were significantly associated with tumor size, palpability, tumor stage, and histologic grade as relatively good prognostic factors compared to CNB. In particular, VAB showed lower odds ratios for these factors than excisional biopsy. In the univariate analysis, the prognosis of patients undergoing VAB was better than that of those undergoing CNB with respect to BCSS (hazard ratio [HR], 0.188, p < 0.001) and OS (HR, 0.359; p < 0.001). However, in the multivariate analysis, there were no significant prognostic differences from CNB in both BCSS and OS; differences were only evident for FNA.

CONCLUSION

In this study, we showed that the characteristics of breast cancer differed according to various biopsy methods. Although VAB is not a standard method for breast cancer diagnosis, it showed no prognostic differences to CNB.

The influence of preoperative biopsy on the surgical method in breast cancer patients: a single-center experience of 3,966 cases in China

Background

The National Surgical Adjuvant Breast and Bowel Project (NSABP) B32 trial reported that the detection rate of sentinel lymph nodes by core needle biopsy (CNB) is higher than that by segmental resection. However, there are few reports regarding the detection rate of sentinel lymph nodes by vacuum-assisted breast biopsy (VABB). Therefore, we analyzed the impact of preoperative biopsy methods on the surgical modes of 3,966 patients with breast cancer in our center.

Methods

In total, 3,966 female breast cancer patients [clinical tumor node metastasis (TNM) stage I-III] were enrolled in this study. Preoperative pathological diagnosis methods included fine needle aspiration (FNA) biopsy, CNB, excision biopsy, and VABB. According to the time of diagnosis. The data were analysis by chi square test, variance analysis and the Kaplan-Meier time series in SPSS 22.0.

Results

There was a decrease in the number of patients that underwent excision biopsy (7.3% to 2.7%) and intraoperative freezing (89.4% to 28.9%) over time, while CNB exhibited an increasing trend (1.6% to 55.3%). The positive rates of VABB, CNB, excision biopsy, and FNA were 99.5%, 97.1%, 97.9%, and 82.2%, respectively, and the false negative rates were 0%, 1.8%, 0.34%, and 8.9%, respectively. The overall breast-conserving rate was 36.7%, while the breast-conserving rate for VABB was 57.1%. The axillary sentinel lymph node biopsy rate of cN0 patients was 48.3%, and the intraoperative frozen group (36.7%) and excision biopsy group (39.5%) were lower than the CNB (57.1%) and VABB (77.9%) groups. Until December 2019, there were 350 cases with tumor recurrence or metastasis. The methods of biopsy were not correlated to the cumulative survival time.

Conclusions

Changes to the diagnosis and treatment of breast cancer has a profound impact on the method of tumor biopsy. VABB biopsy offers advantages such as accurate diagnosis, a greater volume of tissue taken at one time, minimally invasive and repeatable, and does not affect the surgical approach and prognosis of patients. It will gradually become the primary method of preoperative pathological evaluation of breast cancer.