Publications by authors named "Rauch G"

Background: Infective endocarditis during pregnancy is a rare condition that compromises the health of both the mother and the foetus, presenting high rates of morbidity and mortality. The clinical manifestations of this disease are varied, with embolic phenomena being a frequent presentation.

Case Summary: We report the case of a Hispanic 37-year-old patient, at 29 weeks of pregnancy, with no known cardiovascular history, who presented with 48 h of sudden mandibular and lingual pain.

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Molecular breast imaging (MBI) is a functional imaging modality that utilizes technetium 99m sestamibi radiotracer uptake to evaluate the biology of breast tumors. Molecular breast imaging can be a useful tool for supplemental screening of women with dense breasts, for breast cancer diagnosis and staging, and for evaluation of treatment response in patients with breast cancer undergoing neoadjuvant systemic therapy. In addition, MBI is useful in problem-solving when mammography and US imaging are insufficient to arrive at a definite diagnosis and for patients who cannot undergo breast MRI.

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Triple negative breast cancer (TNBC) that fails to respond to neoadjuvant chemotherapy (NACT) can be lethal. Developing effective strategies to eradicate chemoresistant disease requires experimental models that recapitulate the heterogeneity characteristic of TNBC. To that end, we established a biobank of 92 orthotopic patient-derived xenograft (PDX) models of TNBC from the tumors of 75 patients enrolled in the ARTEMIS clinical trial ( NCT02276443 ) at MD Anderson Cancer Center, including 12 longitudinal sets generated from serial patient biopsies collected throughout NACT and from metastatic disease.

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Purpose To combine deep learning and biology-based modeling to predict the response of locally advanced, triple-negative breast cancer before initiating neoadjuvant chemotherapy (NAC). Materials and Methods In this retrospective study, a biology-based mathematical model of tumor response to NAC was constructed and calibrated on a patient-specific basis using imaging data from patients enrolled in the MD Anderson A Robust TNBC Evaluation FraMework to Improve Survival trial (ARTEMIS; ClinicalTrials.gov registration no.

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Article Synopsis
  • The study investigates the effectiveness of the anti-EGFR monoclonal antibody panitumumab combined with carboplatin and paclitaxel for treating chemotherapy-resistant triple-negative breast cancer (TNBC) patients.
  • It included 43 patients who had not sufficiently responded to prior doxorubicin and cyclophosphamide treatment, achieving a combined pathological complete response/residual cancer burden class I rate of 30.2%.
  • The results indicate that panitumumab shows promise as part of neoadjuvant therapy for TNBC, warranting further evaluation in larger clinical trials.
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Background: In clinical trials, the determination of an adequate sample size is a challenging task, mainly due to the uncertainty about the value of the effect size and nuisance parameters. One method to deal with this uncertainty is a sample size recalculation. Thereby, an interim analysis is performed based on which the sample size for the remaining trial is adapted.

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It is unknown if radiation therapy provides additional benefit among patients who achieve pathologic complete response (pCR) following neoadjuvant systemic therapy (NST). We sought to assess feasibility of radiation omission after breast conserving surgery in early-stage, node-negative, HER2+ breast cancer patients with pCR after NST. This was a single-arm study of women 30 years and older with cT2N0 disease based on imaging.

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  • There is a high demand for effective treatments to reduce distress caused by auditory verbal hallucinations (AVHs), and this study explores the potential benefits of adding "Relating Therapy" (RT) to standard treatment.
  • The study was conducted in Germany with 85 participants who struggled with AVHs, showing that RT combined with usual care led to high retention and adherence rates, indicating it is a feasible and safe intervention.
  • Although the results don't show significant reductions in AVH distress compared to standard treatment alone, there were positive trends, suggesting further research on RT's efficacy is warranted.
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Background: Triple negative breast cancer (TNBC) is an aggressive subtype with poor prognosis. We aimed to determine whether circulating tumor DNA (ctDNA) and circulating tumor cell (CTC) could predict response and long-term outcomes to neoadjuvant chemotherapy (NAC).

Methods: Patients with TNBC were enrolled between 2017-2021 at The University of Texas MD Anderson Cancer Center (Houston, TX).

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Many clinical trials assess time-to-event endpoints. To describe the difference between groups in terms of time to event, we often employ hazard ratios. However, the hazard ratio is only informative in the case of proportional hazards (PHs) over time.

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  • Triple-negative breast cancer (TNBC) patients often undergo neoadjuvant systemic therapy (NAST) to improve treatment outcomes.
  • A study analyzed multiparametric MRI scans from 163 TNBC patients at different stages of NAST to see if radiomic models could predict the likelihood of achieving a pathologic complete response (pCR).
  • The best predictive model, based on changes in MRI features after two cycles of treatment, showed a strong ability to forecast pCR with high accuracy, indicating that MRI could be useful for early treatment response assessments in TNBC.
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Luminal androgen receptor (LAR)-enriched triple-negative breast cancer (TNBC) is a distinct subtype. The efficacy of AR inhibitors and the relevant biomarkers in neoadjuvant therapy (NAT) are yet to be determined. We tested the combination of the AR inhibitor enzalutamide (120 mg daily by mouth) and paclitaxel (80 mg/m weekly intravenously) (ZT) for 12 weeks as NAT for LAR-enriched TNBC.

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Cervical cancer is a common gynecological malignancy worldwide. Cervical cancer is staged based on the International Federation of Gynecology and Obstetrics (FIGO) classification system, which was revised in 2018 to incorporate radiologic and pathologic data. Imaging plays an important role in pretreatment assessment including initial staging and treatment response assessment of cervical cancer.

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Background: Group sequential designs incorporating the option to stop for futility at the time point of an interim analysis can save time and resources. Thereby, the choice of the futility boundary importantly impacts the design's resulting performance characteristics, including the power and probability to correctly or wrongly stop for futility. Several authors contributed to the topic of selecting good futility boundaries.

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Early detection of breast cancer through screening mammography saves lives. However, the sensitivity of mammography for breast cancer detection is reduced in women with dense breast tissue. Imaging modalities for supplemental breast cancer screening include MRI, whole breast US, contrast-enhanced mammography, and molecular breast imaging (MBI).

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Due to the dependency structure in the sampling process, adaptive trial designs create challenges in point and interval estimation and in the calculation of P-values. Optimal adaptive designs, which are designs where the parameters governing the adaptivity are chosen to maximize some performance criterion, suffer from the same problem. Various analysis methods which are able to handle this dependency structure have already been developed.

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Background: Sample size calculation is a central aspect in planning of clinical trials. The sample size is calculated based on parameter assumptions, like the treatment effect and the endpoint's variance. A fundamental problem of this approach is that the true distribution parameters are not known before the trial.

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The heterogeneity inherent in cancer means that even a successful clinical trial merely results in a therapeutic regimen that achieves, on average, a positive result only in a subset of patients. The only way to optimize an intervention for an individual patient is to reframe their treatment as their own, personalized trial. Toward this goal, we formulate a computational framework for performing personalized trials that rely on four mathematical techniques.

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Article Synopsis
  • A deep learning model was trained to predict how well patients with triple negative breast cancer (TNBC) respond to neoadjuvant systemic therapy (NAST) using MRI scans taken before and after treatment.
  • The model showed strong predictive performance, achieving high accuracy scores (AUCs) for different testing groups, indicating it can reliably identify patients who have a pathologic complete response (pCR).
  • This technology could lead to more personalized treatment strategies for TNBC patients by allowing early identification of those likely to benefit from NAST based on MRI data.
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  • Some breast cancer patients don’t fully respond to treatment, which makes it harder for them to recover.
  • Researchers looked at a special biopsy method called VAB to see if it could help detect these patients before surgery.
  • They found that VAB always showed if there was leftover cancer after treatment, while regular imaging methods weren't as reliable.
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Article Synopsis
  • Early prediction of response to neoadjuvant systemic therapy (NAST) in patients with triple-negative breast cancer (TNBC) can help tailor treatments and prevent unnecessary side effects from ineffective therapies.
  • The study analyzed 163 TNBC patients using dynamic contrast-enhanced MRI to identify radiomic features that could indicate treatment response, focusing on areas around and within the tumors at different treatment stages.
  • Results showed promising predictive capabilities with certain radiomic features, as well as multivariate models, demonstrating significant accuracy in distinguishing between patients who achieved pathologic complete response (pCR) and those who did not, potentially enhancing early, non-invasive treatment assessments.
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Introduction: The Berlin Long-term Observation of Vascular Events is a prospective cohort study that aims to improve prediction and disease-overarching mechanistic understanding of cardiovascular (CV) disease progression by comprehensively investigating a high-risk patient population with different organ manifestations.

Methods And Analysis: A total of 8000 adult patients will be recruited who have either suffered an acute CV event (CVE) requiring hospitalisation or who have not experienced a recent acute CVE but are at high CV risk. An initial study examination is performed during the acute treatment phase of the index CVE or after inclusion into the chronic high risk arm.

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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.

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Purpose: Advances in radiation therapy have enabled the ability to deliver ablative treatments, but there has been limited application of these treatments to early-stage breast cancers with a goal of omitting surgery. The purpose of this study was to explore patient interest in pursuing nonsurgical treatment approaches for their early-stage breast cancer.

Methods And Materials: We conducted a qualitative study involving interviews with 21 patients with early-stage breast cancer who were eligible for participation in a phase 2 clinical trial offering omission of definitive surgery.

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