Plasma NGAL levels in stable kidney transplant recipients and the risk of allograft loss.

BACKGROUND: The objective of this study was to investigate the utility of neutrophil gelatinase-associated lipocalin (NGAL) and calprotectin (CPT) to predict long-term graft survival in stable kidney transplant recipients (KTR). METHODS: A total of 709 stable outpatient KTR were enrolled >2 months post-transplant. The utility of plasma and urinary NGAL (pNGAL, uNGAL) and plasma and urinary CPT at enrollment to predict death-censored graft loss was evaluated during a 58-month follow-up. RESULTS: Among biomarkers, pNGAL showed the best predictive ability for graft loss and was the only biomarker with an area under the curve (AUC) > 0.7 for graft loss within 5 years. Patients with graft loss within 5 years (n = 49) had a median pNGAL of 304 [interquartile range (IQR) 235-358] versus 182 (IQR 128-246) ng/mL with surviving grafts (P < .001). Time-dependent receiver operating characteristic analyses at 58 months indicated an AUC for pNGAL of 0.795, serum creatinine-based Chronic Kidney Disease Epidemiology Collaboration estimated glomerular filtration rate (eGFR) had an AUC of 0.866. pNGAL added to a model based on conventional risk factors for graft loss with death as competing risk (age, transplant age, presence of donor-specific antibodies, presence of proteinuria, history of delayed graft function) had a strong independent association with graft loss {subdistribution hazard ratio (sHR) for binary log-transformed pNGAL [log2(pNGAL)] 3.4, 95% confidence interval (CI) 2.24-5.15, P < .0001}. This association was substantially attenuated when eGFR was added to the model [sHR for log2(pNGAL) 1.63, 95% CI 0.92-2.88, P = .095]. Category-free net reclassification improvement of a risk model including log2(pNGAL) in addition to conventional risk factors and eGFR was 54.3% (95% CI 9.2%-99.3%) but C-statistic did not improve significantly. CONCLUSIONS: pNGAL was an independent predictor of renal allograft loss in stable KTR from one transplant center but did not show consistent added value when compared with baseline predictors including the conventional marker eGFR. Future studies in larger cohorts are warranted.

Minimally Invasive Breast Biopsy After Neoadjuvant Systemic Treatment to Identify Breast Cancer Patients with Residual Disease for Extended Neoadjuvant Treatment: A New Concept.

BACKGROUND: Breast cancer patients with residual disease after neoadjuvant systemic treatment (NAST) have a worse prognosis compared with those achieving a pathologic complete response (pCR). Earlier identification of these patients might allow timely, extended neoadjuvant treatment strategies. We explored the feasibility of a vacuum-assisted biopsy (VAB) after NAST to identify patients with residual disease (ypT+ or ypN+) prior to surgery. METHODS: We used data from a multicenter trial, collected at 21 study sites (NCT02948764). The trial included women with cT1-3, cN0/+ breast cancer undergoing routine post-neoadjuvant imaging (ultrasound, MRI, mammography) and VAB prior to surgery. We compared the findings of VAB and routine imaging with the histopathologic evaluation of the surgical specimen. RESULTS: Of 398 patients, 34 patients with missing ypN status and 127 patients with luminal tumors were excluded. Among the remaining 237 patients, tumor cells in the VAB indicated a surgical non-pCR in all patients (73/73, positive predictive value [PPV] 100%), whereas PPV of routine imaging after NAST was 56.0% (75/134). Sensitivity of the VAB was 72.3% (73/101), and 74.3% for sensitivity of imaging (75/101). CONCLUSION: Residual cancer found in a VAB specimen after NAST always corresponds to non-pCR. Residual cancer assumed on routine imaging after NAST corresponds to actual residual cancer in about half of patients. Response assessment by VAB is not safe for the exclusion of residual cancer. Response assessment by biopsies after NAST may allow studying the new concept of extended neoadjuvant treatment for patients with residual disease in future trials.

Using short-term endpoints to improve interim decision making and trial duration in two-stage phase II trials with nested binary endpoints.

In oncology, phase II clinical trials are often planned as single-arm two-stage designs with a binary endpoint, for example, progression-free survival after 12 months, and the option to stop for futility after the first stage. Simon's two-stage design is a very popular approach but depending on the follow-up time required to measure the patients' outcomes the trial may have to be paused undesirably long. To shorten this forced interruption, it was proposed to use a short-term endpoint for the interim decision, such as progression-free survival after 3 months. We show that if the assumptions for the short-term endpoint are misspecified, the decision-making in the interim can be misleading, resulting in a great loss of statistical power. For the setting of a binary endpoint with nested measurements, such as progression-free survival, we propose two approaches that utilize all available short-term and long-term assessments of the endpoint to guide the interim decision. One approach is based on conditional power and the other is based on Bayesian posterior predictive probability of success. In extensive simulations, we show that both methods perform similarly, when appropriately calibrated, and can greatly improve power compared to the existing approach in settings with slow patient recruitment. Software code to implement the methods is made publicly available.

Potential of Lesion-to-Fat Elasticity Ratio Measured by Shear Wave Elastography to Reduce Benign Biopsies in BI-RADS 4 Breast Lesions.

OBJECTIVES: We evaluated whether lesion-to-fat ratio measured by shear wave elastography in patients with Breast Imaging Reporting and Data System (BI-RADS) 3 or 4 lesions has the potential to further refine the assessment of B-mode ultrasound alone in breast cancer diagnostics. METHODS: This was a secondary analysis of an international diagnostic multicenter trial (NCT02638935). Data from 1288 women with breast lesions categorized as BI-RADS 3 and 4a-c by conventional B-mode ultrasound were analyzed, whereby the focus was placed on differentiating lesions categorized as BI-RADS 3 and BI-RADS 4a. All women underwent shear wave elastography and histopathologic evaluation functioning as reference standard. Reduction of benign biopsies as well as the number of missed malignancies after reclassification using lesion-to-fat ratio measured by shear wave elastography were evaluated. RESULTS: Breast cancer was diagnosed in 368 (28.6%) of 1288 lesions. The assessment with conventional B-mode ultrasound resulted in 53.8% (495 of 1288) pathologically benign lesions categorized as BI-RADS 4 and therefore false positives as well as in 1.39% (6 of 431) undetected malignancies categorized as BI-RADS 3. Additional lesion-to-fat ratio in BI-RADS 4a lesions with a cutoff value of 1.85 resulted in 30.11% biopsies of benign lesions which correspond to a reduction of 44.04% of false positives. CONCLUSIONS: Adding lesion-to-fat ratio measured by shear wave elastography to conventional B-mode ultrasound in BI-RADS 4a breast lesions could help reduce the number of benign biopsies by 44.04%. At the same time, however, 1.98% of malignancies were missed, which would still be in line with American College of Radiology BI-RADS 3 definition of <2% of undetected malignancies.

The Potential of Shear Wave Elastography to Reduce Unnecessary Biopsies in Breast Cancer Diagnosis: An International, Diagnostic, Multicenter Trial.

PURPOSE: In this prospective, multicenter trial we evaluated whether additional shear wave elastography (SWE) for patients with BI-RADS 3 or 4 lesions on breast ultrasound could further refine the assessment with B-mode breast ultrasound for breast cancer diagnosis. MATERIALS AND METHODS: We analyzed prospective, multicenter, international data from 1288 women with breast lesions rated by conventional 2 D B-mode ultrasound as BI-RADS 3 to 4c and undergoing 2D-SWE. After reclassification with SWE the proportion of undetected malignancies should be < 2 %. All patients underwent histopathologic evaluation (reference standard). RESULTS: Histopathologic evaluation showed malignancy in 368 of 1288 lesions (28.6 %). The assessment with B-mode breast ultrasound resulted in 1.39 % (6 of 431) undetected malignancies (malignant lesions in BI-RADS 3) and 53.80 % (495 of 920) unnecessary biopsies (biopsies in benign lesions). Re-classifying BI-RADS 4a patients with a SWE cutoff of 2.55 m/s resulted in 1.98 % (11 of 556) undetected malignancies and a reduction of 24.24 % (375 vs. 495) of unnecessary biopsies. CONCLUSION: A SWE value below 2.55 m/s for BI-RADS 4a lesions could be used to downstage these lesions to follow-up, and therefore reduce the number of unnecessary biopsies by 24.24 %. However, this would come at the expense of some additionally missed cancers compared to B-mode breast ultrasound (rate of undetected malignancies 1.98 %, 11 of 556, versus 1.39 %, 6 of 431) which would, however, still be in line with the ACR BI-RADS 3 definition (< 2 % of undetected malignancies).

Intelligent multi-modal shear wave elastography to reduce unnecessary biopsies in breast cancer diagnosis (INSPiRED 002): a retrospective, international, multicentre analysis.

BACKGROUND: Breast ultrasound identifies additional carcinomas not detected in mammography but has a higher rate of false-positive findings. We evaluated whether use of intelligent multi-modal shear wave elastography (SWE) can reduce the number of unnecessary biopsies without impairing the breast cancer detection rate. METHODS: We trained, tested, and validated machine learning algorithms using SWE, clinical, and patient information to classify breast masses. We used data from 857 women who underwent B-mode breast ultrasound, SWE, and subsequent histopathologic evaluation at 12 study sites in seven countries from 2016 to 2019. Algorithms were trained and tested on data from 11 of the 12 sites and externally validated using the additional site's data. We compared findings to the histopathologic evaluation and compared the diagnostic performance between B-mode breast ultrasound, traditional SWE, and intelligent multi-modal SWE. RESULTS: In the external validation set (n = 285), intelligent multi-modal SWE showed a sensitivity of 100% (95% CI, 97.1-100%, 126 of 126), a specificity of 50.3% (95% CI, 42.3-58.3%, 80 of 159), and an area under the curve of 0.93 (95% CI, 0.90-0.96). Diagnostic performance was significantly higher compared to traditional SWE and B-mode breast ultrasound (P < 0.001). Unlike traditional SWE, positive-predictive values of intelligent multi-modal SWE were significantly higher compared to B-mode breast ultrasound. Unnecessary biopsies were reduced by 50.3% (79 versus 159, P < 0.001) without missing cancer compared to B-mode ultrasound. CONCLUSION: The majority of unnecessary breast biopsies might be safely avoided by using intelligent multi-modal SWE. These results may be helpful to reduce diagnostic burden for patients, providers, and healthcare systems.

Rationale and design of the prevention of paclitaxel-related neurological side effects with lithium trial - Protocol of a multicenter, randomized, double-blind, placebo- controlled proof-of-concept phase-2 clinical trial.

Introduction: Chemotherapy-induced polyneuropathy (CIPN) and post-chemotherapy cognitive impairment (PCCI) are frequent side effects of paclitaxel treatment. CIPN/PCCI are potentially irreversible, reduce quality of life and often lead to treatment limitations, which affect patients' outcome. We previously demonstrated that paclitaxel enhances an interaction of the Neuronal calcium sensor-1 protein (NCS-1) with the Inositol-1,4,5-trisphosphate receptor (InsP3R), which disrupts calcium homeostasis and triggers neuronal cell death via the calcium-dependent protease calpain in dorsal root ganglia neurons and neuronal precursor cells. Prophylactic treatment of rodents with lithium inhibits the NCS1-InsP3R interaction and ameliorates paclitaxel-induced polyneuropathy and cognitive impairment, which is in part supported by limited retrospective clinical data in patients treated with lithium carbonate at the time of chemotherapy. Currently no data are available from a prospective clinical trial to demonstrate its efficacy. Methods and analysis: The PREPARE study will be conducted as a multicenter, randomized, double-blind, placebo-controlled phase-2 trial with parallel group design. N = 84 patients with breast cancer will be randomized 1:1 to either lithium carbonate treatment (targeted serum concentration 0.5-0.8 mmol/l) or placebo with sham dose adjustments as add-on to (nab-) paclitaxel. The primary endpoint is the validated Total Neuropathy Score reduced (TNSr) at 2 weeks after the last (nab-) paclitaxel infusion. The aim is to show that the lithium carbonate group is superior to the placebo group, meaning that the mean TNSr after (nab-) paclitaxel is lower in the lithium carbonate group than in the placebo group. Secondary endpoints include: (1) severity of CIPN, (2) amount and dose of pain medication, (3) cumulative dose of (nab-) paclitaxel, (4) patient-reported symptoms of CIPN, quality of life and symptoms of anxiety and depression, (5) severity of cognitive impairment, (6) hippocampal volume and changes in structural/functional connectivity and (7) serum Neurofilament light chain protein concentrations. Ethics and dissemination: The study protocol was approved by the Berlin ethics committee (reference: 21/232 - IV E 10) and the respective federal agency (Bundesinstitut für Arzneimittel und Medizinprodukte, reference: 61-3910-4044771). The results of the study will be published in peer-reviewed medical journals as well as presented at relevant (inter)national conferences. Clinical trial registration: [https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00027165], identifier [DRKS00027165].

FIRE-9 - PORT / AIO-KRK-0418: a prospective, randomized, open, multicenter Phase III trial to investigate the efficacy of adjuvant/additive chemotherapy in patients with definitely-treated metastatic colorectal cancer.

BACKGROUND: Additive/adjuvant chemotherapy as concept after local treatment of colorectal metastases has not been proven to be successful by phase III trials. Accordingly, a standard of care to improve relapse rates and long-term survival is not established and adjuvant chemotherapy cannot be recommended as a standard therapy due to limited evidence in literature. The PORT trial aims to generate evidence that post-resection/ablation/radiation chemotherapy improves the survival in patients with metastatic colorectal cancer. METHODS: Patients to be included into this trial must have synchronous or metachronous metastases of colorectal cancer-either resected (R0 or R1) and/or effectively treated by ablation or radiation within 3-10 weeks before randomization-and have the primary tumor resected, without radiographic evidence of active metastatic disease at study entry. The primary endpoint of the trial is progression-free survival after 24 months, secondary endpoints include overall survival, safety, quality of life, treatments (including efficacy) beyond study participation, translational endpoints, and others. One arm of the study comprising 2/3 of the population will be treated for 6 months with modified FOLFOXIRI or modified FOLFOX6 (investigator´s choice, depending on the performance status of the patients but determined before randomization), while the other arm (1/3 of the population) will be observed and undergo scheduled follow-up computed tomography scans according to the interventional arm. DISCUSSION: Optimal oncological management after removal of colorectal metastases is unclear. The PORT trial aims to generate evidence that additive/adjuvant chemotherapy after definitive treatment of colorectal metastases improves progression free and overall survival in patients with colorectal cancer. TRIAL REGISTRATION: This study is registered with clinicaltrials.gov ( NCT05008809 ) and EudraCT (2020-006,144-18).

The importance of multi-modal imaging and clinical information for humans and AI-based algorithms to classify breast masses (INSPiRED 003): an international, multicenter analysis.

OBJECTIVES: AI-based algorithms for medical image analysis showed comparable performance to human image readers. However, in practice, diagnoses are made using multiple imaging modalities alongside other data sources. We determined the importance of this multi-modal information and compared the diagnostic performance of routine breast cancer diagnosis to breast ultrasound interpretations by humans or AI-based algorithms. METHODS: Patients were recruited as part of a multicenter trial (NCT02638935). The trial enrolled 1288 women undergoing routine breast cancer diagnosis (multi-modal imaging, demographic, and clinical information). Three physicians specialized in ultrasound diagnosis performed a second read of all ultrasound images. We used data from 11 of 12 study sites to develop two machine learning (ML) algorithms using unimodal information (ultrasound features generated by the ultrasound experts) to classify breast masses which were validated on the remaining study site. The same ML algorithms were subsequently developed and validated on multi-modal information (clinical and demographic information plus ultrasound features). We assessed performance using area under the curve (AUC). RESULTS: Of 1288 breast masses, 368 (28.6%) were histopathologically malignant. In the external validation set (n = 373), the performance of the two unimodal ultrasound ML algorithms (AUC 0.83 and 0.82) was commensurate with performance of the human ultrasound experts (AUC 0.82 to 0.84; p for all comparisons > 0.05). The multi-modal ultrasound ML algorithms performed significantly better (AUC 0.90 and 0.89) but were statistically inferior to routine breast cancer diagnosis (AUC 0.95, p for all comparisons ≤ 0.05). CONCLUSIONS: The performance of humans and AI-based algorithms improves with multi-modal information. KEY POINTS: • The performance of humans and AI-based algorithms improves with multi-modal information. • Multimodal AI-based algorithms do not necessarily outperform expert humans. • Unimodal AI-based algorithms do not represent optimal performance to classify breast masses.

Intelligent Vacuum-Assisted Biopsy to Identify Breast Cancer Patients With Pathologic Complete Response (ypT0 and ypN0) After Neoadjuvant Systemic Treatment for Omission of Breast and Axillary Surgery.

PURPOSE: Neoadjuvant systemic treatment (NST) elicits a pathologic complete response in 40%-70% of women with breast cancer. These patients may not need surgery as all local tumor has already been eradicated by NST. However, nonsurgical approaches, including imaging or vacuum-assisted biopsy (VAB), were not able to accurately identify patients without residual cancer in the breast or axilla. We evaluated the feasibility of a machine learning algorithm (intelligent VAB) to identify exceptional responders to NST. METHODS: We trained, tested, and validated a machine learning algorithm using patient, imaging, tumor, and VAB variables to detect residual cancer after NST (ypT+ or in situ or ypN+) before surgery. We used data from 318 women with cT1-3, cN0 or +, human epidermal growth factor receptor 2-positive, triple-negative, or high-proliferative Luminal B-like breast cancer who underwent VAB before surgery (ClinicalTrials.gov identifier: NCT02948764, RESPONDER trial). We used 10-fold cross-validation to train and test the algorithm, which was then externally validated using data of an independent trial (ClinicalTrials.gov identifier: NCT02575612). We compared findings with the histopathologic evaluation of the surgical specimen. We considered false-negative rate (FNR) and specificity to be the main outcomes. RESULTS: In the development set (n = 318) and external validation set (n = 45), the intelligent VAB showed an FNR of 0.0%-5.2%, a specificity of 37.5%-40.0%, and an area under the receiver operating characteristic curve of 0.91-0.92 to detect residual cancer (ypT+ or in situ or ypN+) after NST. Spiegelhalter's Z confirmed a well-calibrated model (z score -0.746, P = .228). FNR of the intelligent VAB was lower compared with imaging after NST, VAB alone, or combinations of both. CONCLUSION: An intelligent VAB algorithm can reliably exclude residual cancer after NST. The omission of breast and axillary surgery for these exceptional responders may be evaluated in future trials.

Diagnosing Pathologic Complete Response in the Breast After Neoadjuvant Systemic Treatment of Breast Cancer Patients by Minimal Invasive Biopsy: Oral Presentation at the San Antonio Breast Cancer Symposium on Friday, December 13, 2019, Program Number GS5-03.

OBJECTIVE: We evaluated the ability of minimally invasive, image-guided vacuum-assisted biopsy (VAB) to reliably diagnose a pathologic complete response in the breast (pCR-B). SUMMARY BACKGROUND DATA: Neoadjuvant systemic treatment (NST) elicits a pathologic complete response in up to 80% of women with breast cancer. In such cases, breast surgery, the gold standard for confirming pCR-B, may be considered overtreatment. METHODS: This multicenter, prospective trial enrolled 452 women presenting with initial stage 1-3 breast cancer of all biological subtypes. Fifty-four women dropped out; 398 were included in the full analysis. All participants had an imaging-confirmed partial or complete response to NST and underwent study-specific image-guided VAB before guideline-adherent breast surgery. The primary endpoint was the false-negative rate (FNR) of VAB-confirmed pCR-B. RESULTS: Image-guided VAB alone did not detect surgically confirmed residual tumor in 37 of 208 women [FNR, 17.8%; 95% confidence interval (CI), 12.8-23.7%]. Of these 37 women, 12 (32.4%) had residual DCIS only, 20 (54.1%) had minimal residual tumor (<5 mm), and 19 of 25 (76.0%) exhibited invasive cancer cellularity of ≤10%. In 19 of the 37 cases (51.4%), the false-negative result was potentially avoidable. Exploratory analysis showed that performing VAB with the largest needle by volume (7-gauge) resulted in no false-negative results and that combining imaging and image-guided VAB into a single diagnostic test lowered the FNR to 6.2% (95% CI, 3.4%-10.5%). CONCLUSIONS: Image-guided VAB missed residual disease more often than expected. Refinements in procedure and patient selection seem possible and necessary before omitting breast surgery.

Vacuum-Assisted Breast Biopsy After Neoadjuvant Systemic Treatment for Reliable Exclusion of Residual Cancer in Breast Cancer Patients.

BACKGROUND: About 40 % of women with breast cancer achieve a pathologic complete response in the breast after neoadjuvant systemic treatment (NST). To identify these women, vacuum-assisted biopsy (VAB) was evaluated to facilitate risk-adaptive surgery. In confirmatory trials, the rates of missed residual cancer [false-negative rates (FNRs)] were unacceptably high (> 10%). This analysis aimed to improve the ability of VAB to exclude residual cancer in the breast reliably by identifying key characteristics of false-negative cases. METHODS: Uni- and multivariable logistic regressions were performed using data of a prospective multicenter trial (n = 398) to identify patient and VAB characteristics associated with false-negative cases (no residual cancer in the VAB but in the surgical specimen). Based on these findings FNR was exploratively re-calculated. RESULTS: In the multivariable analysis, a false-negative VAB result was significantly associated with accompanying ductal carcinoma in situ (DCIS) in the initial diagnostic biopsy [odds ratio (OR), 3.94; p < 0.001], multicentric disease on imaging before NST (OR, 2.74; p = 0.066), and age (OR, 1.03; p = 0.034). Exclusion of women with DCIS or multicentric disease (n = 114) and classication of VABs that did not remove the clip marker as uncertain representative VABs decreased the FNR to 2.9% (3/104). CONCLUSION: For patients without accompanying DCIS or multicentric disease, performing a distinct representative VAB (i.e., removing a well-placed clip marker) after NST suggests that VAB might reliably exclude residual cancer in the breast without surgery. This evidence will inform the design of future trials evaluating risk-adaptive surgery for exceptional responders to NST.

The potential of combined shear wave and strain elastography to reduce unnecessary biopsies in breast cancer diagnostics - An international, multicentre trial.

BACKGROUND: Shear wave elastography (SWE) and strain elastography (SE) have shown promising potential in breast cancer diagnostics by evaluating the stiffness of a lesion. Combining these two techniques could further improve the diagnostic performance. We aimed to exploratorily define the cut-offs at which adding combined SWE and SE to B-mode breast ultrasound could help reclassify Breast Imaging Reporting and Data System (BI-RADS) 3-4 lesions to reduce the number of unnecessary breast biopsies. METHODS: We report the secondary results of a prospective, multicentre, international trial (NCT02638935). The trial enrolled 1288 women with BI-RADS 3 to 4c breast masses on conventional B-mode breast ultrasound. All patients underwent SWE and SE (index test) and histopathologic evaluation (reference standard). Reduction of unnecessary biopsies (biopsies in benign lesions) and missed malignancies after recategorising with SWE and SE were the outcome measures. RESULTS: On performing histopathologic evaluation, 368 of 1288 breast masses were malignant. Following the routine B-mode breast ultrasound assessment, 53.80% (495 of 920 patients) underwent an unnecessary biopsy. After recategorising BI-RADS 4a lesions (SWE cut-off ≥3.70 m/s, SE cut-off ≥1.0), 34.78% (320 of 920 patients) underwent an unnecessary biopsy corresponding to a 35.35% (320 versus 495) reduction of unnecessary biopsies. Malignancies in the new BI-RADS 3 cohort were missed in 1.96% (12 of 612 patients). CONCLUSION: Adding combined SWE and SE to routine B-mode breast ultrasound to recategorise BI-RADS 4a patients could help reduce the number of unnecessary biopsies in breast diagnostics by about 35% while keeping the rate of undetected malignancies below the 2% ACR BI-RADS 3 definition.

A new basket trial design based on clustering of homogeneous subpopulations.

As new findings in oncology suggest a focus on individualized and targeted therapies, the demand for adequate clinical trial designs rises, whereby the focus is mainly on early development phases (phase I and II). Phase II oncology trials are often planned and analysed by Simon two-stage design, which corresponds to a one-armed trial design with the option to stop early for futility. Whereas a classical phase II study focuses on one tumour type and location, the relatively new basket trial design allows testing the efficacy of a single drug simultaneously in a number of patient subsets, which correspond to different tumour types. Such trials can be analysed in various ways, including separate analyses of all baskets or by pooling across all baskets. The work presented here tries to find an adequate compromise between these two extremes by implying rules for clustering some baskets, which are reasonably homogeneous. By means of Monte-Carlo simulations, we compare the efficiency of our proposed cluster-based basket trial design with a standard approach proposed recently which only allows for complete pooling or separate analyses. The results suggest that our new design offers a considerable advantage in power, sensitivity and specificity as well as in average sample size compared to the standard approach. The proposed clustering design is an attractive option to conduct basket trials in oncology with higher efficiency and better performance.

Serum creatinine and cystatin C-based estimates of glomerular filtration rate are misleading in acute heart failure.

AIMS: We aimed to test whether the endogenous filtration markers serum creatinine or cystatin C and equation-based estimates of glomerular filtration rate (GFR) based on these markers appropriately reflect changes of measured GFR in patients with acute heart failure. METHODS: In this prospective cohort study of 50 hospitalized acute heart failure patients undergoing decongestive therapy, we applied an intravenous visible fluorescent injectate (VFI), consisting of a low molecular weight component to measure GFR and a high molecular weight component to correct for measured plasma volume. Thirty-eight patients had two sequential GFR measurements 48 h apart. The co-primary endpoints of the study were safety of VFI and plasma stability of the high molecular weight component. A key secondary endpoint was to compare changes in measured GFR (mGFR) to changes of serum creatinine, cystatin C and estimated GFR. RESULTS: VFI-based GFR measurements were safe and consistent with plasma stability of the high molecular weight component and glomerular filtration of the low molecular weight component. Filtration marker-based point estimates of GFR, when compared with mGFR, provided only moderate correlation (Pearson's r, range 0.80-0.88, depending on equation used), precision (r2 , range 0.65-0.78) and accuracy (56%-74% of estimates scored within 30% of mGFR). Correlations of 48-h changes GFR estimates and changes of mGFR were significant (P < 0.05) but weak (Pearson's r, range 0.35-0.39). Observed decreases of eGFR by more than 15% had a low sensitivity (range 38%-46%, depending on equation used) in detecting true worsening mGFR, defined by a >15% decrease in mGFR. CONCLUSIONS: In patients hospitalized for acute heart failure, serum creatinine- and cystatin C-based predictions performed poorly in detecting actual changes of GFR. These data challenge current clinical strategies to evaluate dynamics of kidney function in acute heart failure.

Identification of breast cancer patients with pathologic complete response in the breast after neoadjuvant systemic treatment by an intelligent vacuum-assisted biopsy.

BACKGROUND: Neoadjuvant systemic treatment elicits a pathologic complete response (pCR) in about 35% of women with breast cancer. In such cases, breast surgery may be considered overtreatment. We evaluated multivariate algorithms using patient, tumor, and vacuum-assisted biopsy (VAB) variables to identify patients with breast pCR. METHODS: We developed and tested four multivariate algorithms: a logistic regression with elastic net penalty, an Extreme Gradient Boosting (XGBoost) tree, Support Vector Machines (SVM), and neural network. We used data from 457 women, randomly partitioned into training and test set (2:1), enrolled in three trials with stage 1-3 breast cancer, undergoing VAB before surgery. False-negative rate (FNR) and specificity were the main outcome measures. The best performing algorithm was validated in an independent fourth trial. RESULTS: In the test set (n = 152), the logistic regression with elastic net penalty, XGboost tree, SVM, and neural network revealed an FNR of 1.2% (1 of 85 patients with missed residual cancer). Specificity of the logistic regression with elastic net penalty was 52.2% (35 of 67 women with surgically confirmed breast pCR identified), of the XGBoost tree 55.2% (37 of 67), of SVM 62.7% (42 of 67), and of the neural network 67.2% (45 of 67). External validation (n = 50) of the neural network showed an FNR of 0% (0 of 27) and a specificity of 65.2% (15 of 23). Area under the ROC curve for the neural network was 0.97 (95% CI, 0.94-1.00). CONCLUSION: A multivariate algorithm can accurately select breast cancer patients without residual cancer after neoadjuvant treatment.

Reevaluation of risk factors for time to subsequent events after first stroke occurrence using a new weighted all-cause effect measure.

BACKGROUND: Risk diseases and risk factors for stroke include atrial fibrillation, hypertension, diabetes mellitus, smoking, and elevated LDL-cholesterol. Due to modern treatment options, the impact of these risk diseases on subsequent cardiovascular events or death after a first stroke is less clear and needs to be elucidated. We therefore aimed to get insights into the persistence of adverse prognostic effects of these risk diseases and risk factors on subsequent stroke or death events 1 year after the first stroke by using the new weighted all-cause hazard ratio. METHODS: This study evaluates the 1 year follow-up of 470 first ever stroke cases identified in the area of Ludwigshafen, Germany, with 23 deaths and 34 subsequent stroke events. For this purpose, the recently introduced "weighted all-cause hazard ratio" was used, which allows a weighting of the competing endpoints within a composite endpoint. Moreover, we extended this approach to allow an adjustment for covariates. RESULTS: None of these risk factors and risk diseases, most probably being treated after the first stroke, remained to be associated with a subsequent death or stroke [weighted hazard ratios (95% confidence interval) for diabetes mellitus, atrial fibrillation, high cholesterol, hypertension, and smoking are 0.4 (0.2-0.9), 0.8 (0.4-2.2), 1.3 (0.5-2.5), 1.2 (0.3-2.7), 1.6 (0.8-3.6), respectively]. However, when analyzed separately in terms of death and stroke, the risk factors and risk diseases under investigation affect the subsequent event rate to a variable degree. CONCLUSIONS: Using the new weighted hazard ratio, established risk factors and risk diseases for the occurrence of a first stroke do not remain to be significant predictors for subsequent events like death or recurrent stroke. It has been demonstrated that the new weighted hazard ratio can be used for a more adequate analysis of cardiovascular risk and disease progress. The results have to be confirmed within a larger study with more events.

Prediction of pathological complete response in breast cancer patients during neoadjuvant chemotherapy: Is shear wave elastography a useful tool in clinical routine?

OBJECTIVE: To compare the validity of Shear Wave Elastography (SWE) for the preoperative assessment of pathological complete response (pCR) to standard clinical assessment in breast cancer patients undergoing neoadjuvant chemotherapy (NACT). MATERIALS AND METHODS: This prospective, consecutive clinical trial was conducted under routine clinical practice. Analysis included 134 patients. SWE served as index test, final pathology from surgical specimen as reference standard. PCR (ypT0) was defined as primary endpoint. Elasticity changes were compared for the pCR- vs. non-pCR group. To determine the validity of shear wave velocity (Vs), ROC analyses and diagnostic accuracy parameters were calculated and compared to the final standard clinical assessment by physical examination, mammography and B-mode ultrasound (ycT + vs. ycT0). RESULTS: Vs was significantly reduced in pCR and non-pCR groups during NACT (pCR: ΔVs(abs) = 3.90 m/s, p < 0.001; non-pCR: ΔVs(abs) = 3.10 m/s, p < 0.001). The pCR-group showed significant lower Vs for all control visits (t1,2,END: p < 0.001). ROC analysis of Vs yielded moderate AUCs for the total population (t0: 0.613, t1: 0.745, t2: 0.685, tEND: 0.718). Compared to standard clinical assessment, Vs(tEND) (cut-off: ≤3.35 m/s) was superior in sensitivity (79.6 % vs. 54.5 %), NPV (86.4 % vs. 77.5 %), FNR (20.4 % vs. 45.5 %), inferior in specificity (58.6 % vs. 77.5 %), PPV (46.3 % vs. 54.5 %), FPR (41.4 % vs. 22.5 %). CONCLUSION: SWE measures significant differences in tumour elasticity changes in pCR vs. non-pCR cases. SWE shows improved sensitivity compared to standard clinical assessment, high NPV and low FNR, but failed in specificity in order to predict pCR under routine conditions.

Efficacy of intraoperative specimen radiography as margin assessment tool in breast conserving surgery.

PURPOSE: To explore the ability of intraoperative specimen radiography (SR) to correctly identify positive margins in patients receiving breast conserving surgery (BCS). To assess whether the reoperation rate can be reduced by using this method. METHODS: This retrospective study included 470 consecutive cases receiving BCS due to a primarily diagnosed breast cancer. SR was carried out in two planes, assessing the specimen regarding the presence of the lesion and its relation to all margins. If indicated, re-excision of selective orientations was advised. Under consideration of gross inspection and the SR-findings, it was up to the surgeon whether to perform re-resections. The recommendations for re-excision were, separately for each orientation, compared to the histopathological results, serving as gold standard. RESULTS: Intraoperative SR was performed in 470 cases, thus 2820 margins were assessed. Of those, 2510 (89.0%) were negative and 310 (11.0%) positive. SR identified 2179 (77.3%) margins correctly as negative, whereas 331 (11.7%) clear margins were misjudged as positive. Of 310 infiltrated margins, SR identified 114 (4.0%) correctly, whereas 196 (7.0%) infiltrated margins were missed. This resulted in a sensitivity/specificity of 36.8%/86.8% and PPV/NPV of 25.6%/91.8%. Through targeted re-resections positive margins could be reduced by 31.0% [310 to 214 (7.6%)]. On case level, the rate of secondary procedures could be reduced by 37.0% [from 162 to 102 (21.7%)]. CONCLUSIONS: SR is a helpful tool to identify infiltrated margins and to reduce the rate of secondary surgeries by recommending targeted re-excisions of according orientations in order to obtain a final negative margin status.