教学课程资源库 更多>>

关键词： Breast cancer   Neoadjuvant chemotherapy   Machine learning   Pathologic complete response  

摘要： Background The aim of this study was to develop a machine learning (ML) based model to accurately predict pathologic complete response (pCR) to neoadjuvant chemotherapy (NAC) using pretreatment clinical and pathological characteristics of electronic medical record (EMR) data in breast cancer (BC). Methods The EMR data from patients diagnosed with early and locally advanced BC and who received NAC followed by curative surgery were reviewed. A total of 16 clinical and pathological characteristics was selected to develop ML model. We practiced six ML models using default settings for multivariate analysis with extracted variables. Results In total, 2065 patients were included in this analysis. Overall, 30.6% (n = 632) of patients achieved pCR. Among six ML models, the LightGBM had the highest area under the curve (AUC) for pCR prediction. After hyper-parameter tuning with Bayesian optimization, AUC was 0.810. Performance of pCR prediction models in different histology-based subtypes was compared. The AUC was highest in HR+HER2- subgroup and lowest in HR-/HER2- subgroup (HR+/HER2- 0.841, HR+/HER2+ 0.716, HR-/HER2 0.753, HR-/HER2- 0.653). Conclusions A ML based pCR prediction model using pre-treatment clinical and pathological characteristics provided useful information to predict pCR during NAC. This prediction model would help to determine treatment strategy in patients with BC planned NAC.

摘要： Patient 1 was a participant in the ARISE phase 2 clinical trial;2 patient 2 had participated in a preceeding phase 1 study.3 The comparison with neuropathological findings from ten patients with progressive supranuclear palsy of similar mean age who had not received anti-tau immunisation, provides three key results: no obvious changes in overall intracellular tau deposition between the treated and untreated patients; no evidence of tau-immunoreactive perivascular vesicular astrocytes, which had been reported to occur after treatment with the N-terminal tau antibody gosuranemab in the brains of patients with progressive supranuclear palsy;4 and no apparent neuropathological evidence of adverse reactions to *** study1 is limited by its small sample size and use of controls who had not been selected to meet the same inclusion and exclusion criteria as were used in the two clinical trials.[...]conclusions need to be drawn with *** has also served as a consultant or scientific adviser for AbbVie, during the conduct of the ARISE study; and has served as a consultant for Alzprotect, Asceneuron, Biogen, Biohaven, Lundbeck, Novartis, Roche, Retrotope, Sanofi, and UCB, outside of the submitted work; has received honoraria for scientific presentations from AbbVie, Bayer Vital, Biogen, Bial, Bristol Myers Squibb, Kyowa Kirin, Roche, Teva, UCB, and Zambon, outside of the submitted work; and has received research support from the German Center for Neurodegenerative Diseases, Deutsche Forschungsgemeinschaft (German Research Foundation) under Germany's Excellence Strategy within the framework of the Munich Cluster for Systems Neurology (EXC 2145 SyNergy ID 390857198) and within the Hannover Cluster RESIST (EXC 2155 ID 390874280), Deutsche Forschungsgemeinschaft (HO2402/6-2 Heisenberg programme; HO2402/18-1 MSAomics), the German Federal Ministry of Education and Research (01KU1403A EpiPD; 01EK1605A HitTau), the EU/EFPIA/Innovative Medicines Initiative Joint Undertak

关键词： Complete response   Ipilimumab   Nephrectomy   Nivolumab   Renal cell carcinoma   Sarcomatoid component  

摘要： Although immuno-oncology combination therapy with nivolumab plus ipilimumab has recently shown a notable antitumor effect for first-line metastatic renal cell carcinoma, the eradication of the disease is extremely rare. Moreover, conventional treatments for renal cell carcinoma show little efficacy in the case of a poor prognostic pathological feature of sarcomatoid dedifferentiation. We report a case of pathological eradication of recurrent metastatic renal cell carcinoma with sarcomatoid component after laparoscopic radical nephrectomy by nivolumab plus ipilimumab combination therapy. A 57-year-old male patient received four cycles of nivolumab plus ipilimumab and thirty cycles of nivolumab for local recurrence and liver metastasis after laparoscopic radical nephrectomy for T3a renal cell carcinoma with sarcomatoid component. He underwent partial hepatectomy for the remaining small hepatic lesion after immuno-oncology therapy. Pathology of the surgical specimen showed no viable cancer cells. The patient was alive with no evidence of disease a year after partial hepatectomy. Our case encourages clinicians to achieve a second cure for patients with recurrent metastatic renal cell carcinoma after radical nephrectomy even though the resected kidney pathology showed sarcomatoid component.

关键词： Rectal cancer   Rectal resection   Distal margin   Neoadjuvant chemoradiation  

摘要： To investigate the discrepancy between the distal resection margin (DRM) assessed by surgeons and pathologists, and the impact of neoadjuvant chemoradiotherapy (nCRT) on DRM. This study included 67 rectal cancer patients undergoing elective surgery. DRMs were assessed through four different techniques: in vivo subjective estimative, made by the surgeon before the rectal resection (by palpation and visual estimative);in vivo objective, measured with a ruler before the rectal transection;ex vivo objective, measured right after resection of the specimen;post-fixation objective measurement, conducted by the pathologist. The DRMs subjectively and objectively assessed by the surgeons were not significantly different (3.40 cm vs. 3.45 cm). There was a mean reduction in the length of DRMs of 35.6%, from 3.45 cm objectively measured by the surgeon to 2.20 cm measured by the pathologist. This difference was significant among patients that did not receive nCRT (3.90 cm vs. 2.30 cm, P < 0.001), but not among those who received nCRT (2.30 vs. 2.05 cm). Surgeons are accurate in assessing rectal cancer DRMs. There are significant differences between intraoperative measurements of DRMs and the final pathologic results. However, these differences are not seen when nCRT is used, a finding that may be useful when sphincter preservation is being considered.

关键词： Breast cancer   HER2 gene   Pathological complete response   Personalised medicine   Precision medicine  

摘要： 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) 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://***/licenses/by/4.0/).

关键词： ANCA-associated vasculitic kidney injury   Clinical data   Pathology   Crescent  

摘要： Objective To analyze the clinical and pathological features of patients with anti-neutrophilic cytoplasmic antibody (ANCA)-associated vasculitic (AASV)-kidney injury (AASVKI). Methods From January 2015 to December 2018, a total of 101 AASVKI patients treated in the First Hospital of Jilin University were divided into 2 groups (the pANCA-positive group and the cANCA-positive group) for comparison;63 patients were performed renal biopsy and divided into 3 groups according to pathological results [the non-crescent nephritis group (non-C), the crescent nephritis group (C), and the sclerotic nephritis group (S)] for comparison. Results Compared with the Group pANCA, Group cANCA exhibited higher incidence of eye involvement (P = 0.039) and skin mucosa destruction (P = 0.045), higher serum creatinine (Scr) (P < 0.001), higher 24-h urine protein quantification (P = 0.045), but lower hemoglobin (Hb) (P < 0.001). Compared with Group non-C, Group C had higher Scr (P < 0.001) and urinary red blood cells (P = 0.010), lower estimated glomerular filtration rate (eGFR) (P = 0.003), hemoglobin (HD)-dependence (P = 0.042), and higher mortality rate within 1 year (P = 0.005);compared with Group S, Group C had faster onset of erythrocyte sedimentation rate (ESR) (P = 0.031), higher urinary red blood cells (P = 0.029), and lower incidence of HD-dependence (P = 0.038). Conclusions AASVKI patients with positive cANCA have poor renal function, among whom the patients with crescent type have poorer renal function than those with non-crescent type, have higher urinary red blood cells while lower HD-dependence than those with sclerotic type.

关键词： Solid State Physics   Spectroscopy/Spectrometry   Atoms and Molecules in Strong Fields   Laser Matter Interaction   Physical Chemistry   Organic Chemistry  

摘要： The purpose of this manuscript is to provide an overview of methods that are termed EPR oximetry and to describe how these techniques have been successfully applied to characterize oxygenation status in normal and pathological tissues as well as in malignant tumors. Values in oxygenation status are presented for the following tissues: brain, kidney, liver, heart, skeletal muscle, skin, and grafts. We report basal pO(2) values recorded in physiological conditions, values that may considerably vary depending on the anesthesia used. We also present the evolution of the oxygenation under pathological or ischemic states, under oxygen-enriched breathing challenge, and after pharmacological intervention. Because tumor hypoxia is a key detrimental factor in tumor progression and resistance to radiation therapy, EPR oximetry has been increasingly being used not only to characterize hypoxic tumor phenotypes but also to monitor changes in oxygen status after therapeutic interventions (i.e. oxygen or carbogen breathing, modulators of perfusion, inhibitors of oxygen consumption rate, irradiation). EPR oximetry has also been used to qualify or disqualify other oxygen imaging (PET, MRI) biomarkers. Overall, this paper presents a large comprehensive database on pO(2) values recorded in different tissues and in different physiological conditions using EPR oximetry.

关键词： Liver neoplasms   Machine learning   Biomarkers   Tomography   X-ray   Computed   Deep learning  

摘要： Histopathological growth patterns (HGPs) are independent prognosticators for colorectal liver metastases (CRLM). Currently, HGPs are determined postoperatively. In this study, we evaluated radiomics for preoperative prediction of HGPs on computed tomography (CT), and its robustness to segmentation and acquisition variations. Patients with pure HGPs [i.e. 100% desmoplastic (dHGP) or 100% replacement (rHGP)] and a CT-scan who were surgically treated at the Erasmus MC between 2003-2015 were included retrospectively. Each lesion was segmented by three clinicians and a convolutional neural network (CNN). A prediction model was created using 564 radiomics features and a combination of machine learning approaches by training on the clinician's and testing on the unseen CNN segmentations. The intra-class correlation coefficient (ICC) was used to select features robust to segmentation variations;ComBat was used to harmonize for acquisition variations. Evaluation was performed through a 100 x random-split cross-validation. The study included 93 CRLM in 76 patients (48% dHGP;52% rHGP). Despite substantial differences between the segmentations of the three clinicians and the CNN, the radiomics model had a mean area under the curve of 0.69. ICC-based feature selection or ComBat yielded no improvement. Concluding, the combination of a CNN for segmentation and radiomics for classification has potential for automatically distinguishing dHGPs from rHGP, and is robust to segmentation and acquisition variations. Pending further optimization, including extension to mixed HGPs, our model may serve as a preoperative addition to postoperative HGP assessment, enabling further exploitation of HGPs as a biomarker.