Construction and validation of a nomogram for predicting the prognosis of patients with lymph node-positive invasive micropapillary carcinoma of the breast: based on SEER database and external validation cohort.

Background: Invasive micropapillary carcinoma (IMPC) of the breast is a rare subtype of breast cancer with high incidence of aggressive clinical behavior, lymph node metastasis (LNM) and poor prognosis. In the present study, using the Surveillance, Epidemiology, and End Results (SEER) database, we analyzed the clinicopathological characteristics and prognostic factors of IMPC with LNM, and constructed a prognostic nomogram. Methods: We retrospectively analyzed data for 487 breast IMPC patients with LNM in the SEER database from January 2010 to December 2015, and randomly divided these patients into a training cohort (70%) and an internal validation cohort (30%) for the construction and internal validation of the nomogram, respectively. In addition, 248 patients diagnosed with IMPC and LNM at the Fourth Hospital of Hebei Medical University from January 2010 to December 2019 were collected as an external validation cohort. Lasso regression, along with Cox regression, was used to screen risk factors. Further more, the discrimination, calibration, and clinical utility of the nomogram were assessed based on the consistency index (C-index), time-dependent receiver operating characteristic (ROC), calibration curve, and decision curve analysis (DCA). Results: In summary, we identified six variables including molecular subtype of breast cancer, first malignant primary indicator, tumor grade, AJCC stage, radiotherapy and chemotherapy were independent prognostic factors in predicting the prognosis of IMPC patients with LNM (P < 0.05). Based on these factors, a nomogram was constructed for predicting 3- and 5-year overall survival (OS) of patients. The nomogram achieved a C-index of 0.789 (95%CI: 0.759-0.819) in the training cohort, 0.775 (95%CI: 0.731-0.819) in the internal validation cohort, and 0.788 (95%CI: 0.756-0.820) in the external validation cohort. According to the calculated patient risk score, the patients were divided into a high-risk group and a low-risk group, which showed a significant difference in the survival prognosis of the two groups (P<0.0001). The time-dependent ROC curves, calibration curves and DCA curves proved the superiority of the nomogram. Conclusions: We have successfully constructed a nomogram that could predict 3- and 5-year OS of IMPC patients with LNM and may assist clinicians in decision-making and personalized treatment planning.

The furosemide stress test predicts the timing of continuous renal replacement therapy initiation in critically ill patients with acute kidney injury: a double-blind prospective intervention cohort study.

BACKGROUND: Continuous renal replacement therapy (CRRT) remains a crucial treatment for critically ill patients with acute kidney injury (AKI), although the timing of its initiation is still a matter of contention. Furosemide stress testing (FST) may be a practical and beneficial prediction instrument. This research was meant to examine if FST can be used to identify high-risk patients for CRRT. METHODS: This study is a double-blind, prospective interventional cohort study. For patients with AKI receiving intensive care unit (ICU) income, FST was selected with furosemide 1 mg/kg intravenous (1.5 mg/kg intravenous if a loop diuretic was received within 7 days). Urinary volume more than 200 ml at 2 h after FST was FST-responsive, less than 200 ml was FST-nonresponsive. The FST results are kept strictly confidential from the clinician, who decides whether to initiate CRRT based on laboratory testing and clinical symptoms other than the FST data. The FST data are concealed from both the patients and the clinician. RESULTS: FST was delivered to 187 of 241 patients who satisfied the inclusion and exclusion criteria, with 48 patients responding to the test and 139 patients not responding. 18/48 (37.5%) of the FST-responsive patients received CRRT, while 124/139 (89.2%) of the FST-nonresponsive patients received CRRT. There was no significant difference between the CRRT and non-CRRT groups in terms of general health and medical history (P > 0.05). Urine volume after 2 h of FST was considerably lower in the CRRT group than in the non-CRRT group (35 ml, IQR5-143.75 versus 400 ml, IQR210-890; P = 0.000). FST non-responders were 2.379 times more likely to initiate CRRT than FST responders (95% CI 1.644-3.443, P = 0.000). The area under the curve (AUC) for initiating CRRT was 0.966 (cutoff of 156 ml, sensitivity of 94.85%, specificity of 98.04%, P < 0.001). CONCLUSION: This study demonstrated that FST is a safe and practical approach for predicting the initiation of CRRT in critically ill AKI patients. Trial registration www.chictr.org.cn , ChiCTR1800015734, Registered 17 April 2018.

Evolution and clinical significance of HER2-low status after neoadjuvant therapy for breast cancer.

Background: The emergence of HER2 antibody-drug conjugates provides new treatment decisions for breast cancer patients, especially those with HER2-low expression. In order to explore the biological characteristics of breast cancer with HER2-low expression, the HER2-low category in primary breast cancer and residual tumor after neoadjuvant therapy was investigated to reflect the evolution of HER2 expression. Methods: HER2 was assessed according to the latest ASCO/CAP guidelines. The cut-off value for staining of HER2-positive cells was >10%. HER2-negative cases were divided into HER2-low (IHC=1+/2+ and no ISH amplification) and HER2-zero (IHC-0), and the clinicopathological characteristics of the cases were collected. Results: This study included 1140 patients with invasive breast cancer who received preoperative neoadjuvant therapy from 2018 to 2021, of which 365 patients achieved pCR and 775 were non-pCR. In the non-pCR cohort, HER2-low cases accounted for 59.61% of primary tumors and 55.36% of residual tumors. Among HER2-negative cases, HR-positive tumors had a higher incidence of low HER2 expression compared with triple-negative tumors (80.27% vs 60.00% in primary tumors and 72.68% vs 50.77% in residual tumors). The inconsistency rate of HER2 expression was 21.42%, mainly manifested as the conversion of HER2-low cases to HER2-zero (10.19%) and the conversion of HER2-zero to HER2-low (6.45%). Among the HER2-negative cases in the primary tumor, the HER2 discordance rate of HR-positive cases was lower than that of triple-negative cases (23.34% VS 36.92%). This difference was mainly caused by the case switching from HER2-low to HER2-zero. Compared with HER2-zero cases, there were statistically significant differences in RCB grade, MP grade and the number of metastatic lymph nodes in HER2-low cases. Patients with low HER2 expression had a lower pathological response rate and a higher number of metastatic lymph nodes. Conclusion: HER2-low breast cancer is highly unstable during disease evolution and has certain biological characteristics. HER2-low breast cancer is not only correlated with positive HR, but also has a certain correlation with positive AR. Re-detection of HER2 in breast cancer after neoadjuvant therapy may lead to new treatment opportunities for a certain proportion of patients.

The Role of Artificial Intelligence in Accurate Interpretation of HER2 Immunohistochemical Scores 0 and 1+ in Breast Cancer.

The new human epidermal growth factor receptor (HER)2-targeting antibody-drug conjugate offers the opportunity to treat patients with HER2-low breast cancer. Distinguishing HER2 immunohistochemical (IHC) scores of 0 and 1+ is not only critical but also challenging owing to HER2 heterogeneity and variability of observers. In this study, we aimed to increase the interpretation accuracy and consistency of HER2 IHC 0 and 1+ evaluation through assistance from an artificial intelligence (AI) algorithm. In addition, we examined the value of our AI algorithm in evaluating HER2 IHC scores in tumors with heterogeneity. AI-assisted interpretation consisted of AI algorithms and an augmenting reality module with a microscope. Fifteen pathologists (5 junior, 5 midlevel, and 5 senior) participated in this multi-institutional 2-round ring study that included 246 infiltrating duct carcinoma cases that were not otherwise specified. In round 1, pathologists analyzed 246 HER2 IHC slides by microscope without AI assistance. After a 2-week washout period, the pathologists read the same slides with AI algorithm assistance and rendered the definitive results by adjusting to the AI algorithm. The accuracy of interpretation accuracy with AI assistance (0.93 vs 0.80), thereby the evaluation precision of HER2 0 and the recall of HER2 1+. In addition, the AI algorithm improved the total consistency (intraclass correlation coefficient = 0.542-0.812), especially in HER2 1+ cases. In cases with heterogeneity, accuracy improved significantly (0.68 to 0.89) and to a similar level as in cases without heterogeneity (accuracy, 0.97). Both accuracy and consistency improved more for junior pathologists than those for the midlevel and senior pathologists. To the best of our knowledge, this is the first study to show that the accuracy and consistency of HER2 IHC 0 and 1+ evaluation and the accuracy of HER2 IHC evaluation in breast cancers with heterogeneity can be significantly improved using AI-assisted interpretation.

A clinical diagnostic test on the detection of sentinel lymph node metastasis in breast neoplasms using a 1-step RT-PCR.

Background: Currently, assessment of sentinel lymph node (SLN) requires cytology, hematoxylin-eosin (HE), and immunohistochemistry (IHC). However, routine pathological slides still suffer from certain sampling errors and have time limitations. This study sought to investigate the sensitivity and specificity of SLN detection by reverse transcription-polymerase chain reaction (RT-PCR), which quantifies the expression of mammaglobin and cytokeratin-19 genes to determine SLN status. Methods: The RT-PCR detection of cycles threshold (CT) values has a direct relationship with the lymph node metastasis. This study prospectively collected 256 sentinel lymph nodes from 150 patients diagnosed with breast cancer between August and November 2017. In the detection of metastases in lymph nodes, molecular markers can be verified at the cell-level and tissue-level of tumor cells. In this study, IHC results were used as the gold standard for judging sentinel lymph node status. Results: (I) According to the established cell models, as the lymph nodes in tumor cells increase, RT-PCR CT values decrease. (II) 83 lymph nodes were first collected, and the interpretation criteria for the molecular detection results were determined based on the IHC results. (III) The statistical analysis showed that the sensitivity of the RT-PCR was 80.49% and the specificity was 91.55%. The positive predictive and negative predictive values were 64.71% and 96.06%, respectively. There was no significant difference between RT-PCR detection and IHC detection (P=0.076). Statistical chi-square analysis also showed that the difference between intraoperative freezing and immunohistochemistry was statistically significant (P=0.000). There was a statistically significant difference between intraoperative freezing and RT-PCR detection (P=0.000). RT-PCR detection is more sensitive than intraoperative frozen detection, and is closer to the results of immunohistochemistry. Conclusions: RT-PCR had objective and rapid output advantages, and was proven to be true and reliable. RT-PCR detection can not only rapidly assess sentinel lymph node status in breast cancer patients during surgery, but its accuracy is also close to that of IHC. Correctly determine whether to perform axillary lymph node dissection and improve the survival rate of patients.

The prognosis and risk factors for acute kidney injury in high-risk patients after surgery for type A aortic dissection in the ICU.

BACKGROUND: Acute kidney injury (AKI) is a major complication of cardiac surgery, with high rates of morbidity and mortality. The aim of this study was to identify risk factors for the incidence and prognosis of AKI in high-risk patients before and after surgery for acute type A aortic dissection (TAAD) in the intensive care unit (ICU). METHODS: We performed a retrospective cohort study from April 2018 to April 2019. The primary end points of this study were morbidity due to AKI and risk factors for incidence, and the secondary end points were mortality at 28 days and risk factors for death. RESULTS: We enrolled 60 patients, 52 (86.67%) patients developed postoperative AKI, 28 (53.84%) patients died. Preoperative lactic acid level (P=0.022) and cardiopulmonary bypass (CPB) duration (P=0.009) were identified as independent risk factors for postoperative AKI. The 28-day mortality for postoperative patients with TAAD was 46.67%, 53.84% for those with TAAD and AKI, 67.5% for those who required continue renal replacement therapy (CRRT). The risk factors for 28-day mortality due to postoperative AKI for patients requiring CRRT were CPB duration (P=0.019) and norepinephrine dose upon diagnosis of AKI (P=0.037). CONCLUSIONS: Morbidity due to AKI in postoperative patients with TAAD was 86.67%, and preoperative lactic acid level and CPB duration were independent risk factors. The 28-day mortality of postoperative patients with TAAD was 46.67%, 53.84% for those with TAAD and AKI, and 67.5% for those requiring CRRT. CPB duration and norepinephrine dose upon diagnosis of AKI may influence patients' short-term prognosis.

Improving Ki67 assessment concordance by the use of an artificial intelligence-empowered microscope: a multi-institutional ring study.

AIMS: The nuclear proliferation biomarker Ki67 plays potential prognostic and predictive roles in breast cancer treatment. However, the lack of interpathologist consistency in Ki67 assessment limits the clinical use of Ki67. The aim of this article was to report a solution utilising an artificial intelligence (AI)-empowered microscope to improve Ki67 scoring concordance. METHODS AND RESULTS: We developed an AI-empowered microscope in which the conventional microscope was equipped with AI algorithms, and AI results were provided to pathologists in real time through augmented reality. We recruited 30 pathologists with various experience levels from five institutes to assess the Ki67 labelling index on 100 Ki67-stained slides from invasive breast cancer patients. In the first round, pathologists conducted visual assessment on a conventional microscope; in the second round, they were assisted with reference cards; and in the third round, they were assisted with an AI-empowered microscope. Experienced pathologists had better reproducibility and accuracy [intraclass correlation coefficient (ICC) = 0.864, mean error = 8.25%] than inexperienced pathologists (ICC = 0.807, mean error = 11.0%) in visual assessment. Moreover, with reference cards, inexperienced pathologists (ICC = 0.836, mean error = 10.7%) and experienced pathologists (ICC = 0.875, mean error = 7.56%) improved their reproducibility and accuracy. Finally, both experienced pathologists (ICC = 0.937, mean error = 4.36%) and inexperienced pathologists (ICC = 0.923, mean error = 4.71%) improved the reproducibility and accuracy significantly with the AI-empowered microscope. CONCLUSION: The AI-empowered microscope allows seamless integration of the AI solution into the clinical workflow, and helps pathologists to obtain higher consistency and accuracy for Ki67 assessment.

Predictive efficacy of weaning index on mechanical ventilation evacuation.

BACKGROUND: The timely weaning of mechanical ventilation can shorten intensive care unit (ICU) stay times and reduce the complications related to mechanical ventilation. This study sought to investigate the predictive role of a weaning index (WI) on mechanical ventilation evacuation by measuring minute ventilation volume (MVV) across different ventilation modes. METHODS: Patients suffering from respiratory failure for a variety of reasons were included in the study if they received mechanical ventilation for more than 48 hours in the ICU. The patients were randomly allocated to either the assist/control (A/C) group or the pressure support ventilation (PSV) group according to the ventilator mode. The factors associated with weaning success and failure were analyzed. RESULTS: A total of 40 patients participated in this study. Of these, 25 weaning cases were successful and 15 were failures. There were 19 cases in the A/C group, yielding a success rate of 63%, and 21 cases in the PSV group, yielding a success rate of 62%. There were no significant differences between the two groups in terms of age, gender, ideal weight, Acute Physiology and Chronic Health Evaluation (APACHE) II score, ICU stay time and hospitalization time. There were significant differences in the mechanical ventilation duration between the two groups (P<0.05). When the WI was less than 50.44, the sensitivity and specificity of predicting weaning success were 72% and 98%. The area under the receiver operating characteristic (ROC) curve was 0.928±0.03. When the WI of the A/C group was less than 61.45, the sensitivity and specificity of predicting weaning success were 98% and 72%, respectively. The area under the ROC curve was 0.917±0.068. When the WI of the PSV group was less than 51.45, the sensitivity and specificity of predicting weaning success were 74.6% and 100%, respectively. The area under the ROC curve was 0.933±0.046. CONCLUSIONS: Compared with RSBI, WI shows a better value in predicting weaning, especially for mechanically ventilated patients in PSV mode, WI has greater value in predicting weaning.