Tool For Treatment Decisions Research Articles

Implementation of digital patient decision support tools for Atrial Fibrillation treatment: systematic review

Abstract Background/ Introduction Treating atrial fibrillation (AF) involves complex decisions. Digital patient decision-support tools can facilitate shared decision making by significantly reducing decisional conflict and improving patient knowledge [1,2]. Yet, implementation in clinical practice is lagging [3]. Purpose To systematically review trials of digital patient decision-support tools for AF treatment decisions, focusing on factors influencing their implementation in clinical practice. Methods We conducted a systematic review following Cochrane methods. EMBASE, MEDLINE and Scopus were searched from 2005 to 2023. Eligible randomised controlled trials and quasi-experimental trials that evaluated digital patient decision-support tools for AF treatment decisions were included. Two independent reviewers screened title and abstract, extracted data and assessed risk of bias. The implementation outcomes included a description of when and how the tool was used, as well as its characteristics and user satisfaction. Results Thirteen articles reporting on eleven studies (5 RCTs and 6 quasi-experimental trials) met the inclusion criteria (2,714 participants; mean age 71±4.2 years; 26% women; 92% with non-valvular AF, remaining not reported). Risk of bias was low for 2 studies, moderate for one and high for seven studies. All tools (n=11) focused on anticoagulation choice (1: warfarin vs no warfarin; 1: aspirin vs warfarin; 7: Direct Oral Anticoagulants (DOAC) vs antiplatelet or warfarin; 2: unspecified choice). The tools were used either pre-visit (at home or in the waiting room) or during the consultation (n=5). Tools were delivered using a mobile application (n=4), web-based application (n=5), or a desktop (n=2). Of the eleven tools, 2 could automatically calculate individualized stroke risk using data from electronic health records. Most articles reported favourable user feedback regarding use of the digital patient decision-support tools, such as high perceived usefulness, user-friendliness, and overall satisfaction. No significant difference was found in encounter times between intervention and control arms (2 RCTs). Four tools were publicly available and 3 were implemented in healthcare delivery beyond research. Conclusion Despite demonstrated efficacy in reducing decisional conflict and improving patient knowledge, as well as positive clinician and patient experience, only 3 tools were implemented in clinical practice beyond their trial. Future tools could better leverage digital capabilities to integrate with Electronic Health Records, automate stroke and bleeding risk calculations, and personalise content based on patient values and preferences. Additional robust trials and implementation studies are warranted to understand barriers and enablers to the use of these tools.

Development and validation of survival prediction models for patients with hepatocellular carcinoma treated with transcatheter arterial chemoembolization plus tyrosine kinase inhibitors.

Due to heterogeneity of molecular biology and microenvironment, therapeutic efficacy varies among hepatocellular carcinoma (HCC) patients treated with transcatheter arterial chemoembolization (TACE) and tyrosine kinase inhibitors (TKIs). We examined combined models using clinicoradiological characteristics, mutational burden of signaling pathways, and radiomics features to predict survival prognosis. Two cohorts comprising 111 patients with HCC were used to build prognostic models. The training and test cohorts included 78 and 33 individuals, respectively. Mutational burden was calculated based on 17 cancer-associated signaling pathways. Radiomic features were extracted and selected from computed tomography images using a pyradiomics system. Models based on clinicoradiological indicators, mutational burden, and radiomics score (rad-score) were built to predict overall survival (OS) and progression-free survival (PFS). Eastern Cooperative Oncology Group performance status, Child-Pugh class, peritumoral enhancement, PI3K_AKT and hypoxia mutational burden, and rad-score were used to create a combined model predicting OS. C-indices were 0.805 (training cohort) and 0.768 (test cohort). The areas under the curve (AUCs) were 0.889, 0.900, and 0.917 for 1-year, 2-year, and 3-year OS, respectively. To predict PFS, alpha-fetoprotein level, tumor enhancement pattern, hypoxia and receptor tyrosine kinase mutational burden, and rad-score were used. C-indices were 0.782 (training cohort) and 0.766 (test cohort). AUCs were 0.885 and 0.925 for 6-month and 12-month PFS, respectively. Calibration and decision curve analyses supported the model's accuracy and clinical potential. The nomogram models are hopeful to predict OS and PFS in patients with intermediate-advanced HCC treated with TACE plus TKIs, offering a promising tool for treatment decisions and monitoring patient progress.

Evolution of Colorectal Cancer Trends and Treatment Outcomes: A Comprehensive Retrospective Analysis (2019-2023) in West Kazakhstan.

To determine the demographic and clinical characteristics of individuals diagnosed with colorectal cancer. A retrospective study was conducted on 650 patients diagnosed with colorectal cancer in West Kazakhstan from 2019 to 2023. Statistical analysis was performed to explore the relationships between various factors and outcomes, using significance tests and regression techniques. The study included 650 colorectal cancer patients, with 59.7% males and 40.3% females. Age distribution showed 63.1% between 24-65 years and 36.9% over 65, with no gender-based age differences. Nationality significantly influenced patient composition (63.8% Kazakh, 36.2% Russian, P=0.03). KRAS mutations (76.0% negative) and tumor morphology (40% adenocarcinoma, P=0.02) displayed varied associations. Univariate logistic regression revealed links between demographic/clinical factors and cancer outcomes. Multivariate analysis emphasized age, stage of cancer, expansion, involvement of lymphatic and metastasis in cancer progression. Nomogram predictive modeling incorporated gender, tumor form, stage, and infiltration. Evaluation in a validation cohort showed good differentiation (AUC=0.6293) and calibration. The findings provide insights into colorectal cancer demographics, progression, treatment, and mortality, aiding personalized interventions. this study reveals critical insights into demographics, treatment, and prognosis. Emphasizing the complexity of CRC, the study highlights age, gender, and tumor characteristics' impact on progression and mortality. A developed nomogram model offers clinicians a practical tool for personalized treatment decisions, enhancing prognosis discussions with patients.

Consistency of CSCO AI with Multidisciplinary Clinical Decision-Making Teams in Breast Cancer: A Retrospective Study.

The Chinese Society of Clinical Oncology Artificial Intelligence System (CSCO AI) serves as a clinical decision support system developed utilizing Chinese breast cancer data. Our study delved into the congruence between breast cancer treatment recommendations provided by CSCO AI and their practical application in clinical settings. A retrospective analysis encompassed 537 breast cancer patients treated at the Second Affiliated Hospital of Anhui Medical University between January 2017 and December 2022. Proficient senior oncology researchers manually input patient data into the CSCO AI system. "Consistent" and "Inconsistent" treatment categories were defined by aligning our treatment protocols with the classification system in the CSCO AI recommendations. Cases that initially showed inconsistency underwent a second evaluation by the Multi-Disciplinary Treatment (MDT) team at the hospital. Concordance was achieved when MDTs' treatment suggestions were in the 'Consistent' categories. An impressive 80.4% concurrence was observed between actual treatment protocols and CSCO AI recommendations across all breast cancer patients. Notably, the alignment was markedly higher for stage I (85.02%) and stage III (88.46%) patients in contrast to stage II patients (76.06%, P=0.023). Moreover, there was a significant concordance between invasive ductal carcinoma and lobular carcinoma (88.46%). Interestingly, triple-negative breast cancer (TNBC) exhibited a high concordance rate (87.50%) compared to other molecular subtypes. When contrasting MDT-recommended treatments with CSCO AI decisions, an overall 92.4% agreement was established. Furthermore, a logistic multivariate analysis highlighted the statistical significance of age, menstrual status, tumor type, molecular subtype, tumor size, and TNM stage in influencing consistency. In the realm of breast cancer treatment, the alignment between recommendations offered by CSCO AI and those from MDT is predominant. CSCO AI can be a useful tool for breast cancer treatment decisions.

Use of digital patient decision-support tools for atrial fibrillation treatments: a systematic review and meta-analysis

ObjectivesTo assess the effects of digital patient decision-support tools for atrial fibrillation (AF) treatment decisions in adults with AF.Study designSystematic review and meta-analysis.Eligibility criteriaEligible randomised controlled trials (RCTs) evaluated digital...

ROLE OF ULTRASONOGRAPHY IN RESPONSE ASSESSMENT FOLLOWING NEOADJUVANT CHEMOTHERAPY IN LOCALLY ADVANCED BREAST CARCINOMA: EXPERIENCE FROM A TERTIARY CARE CENTER

Objective: Neo-adjuvant chemotherapy (NACT) has a pivotal role in the treatment of locally advanced breast carcinoma (LABC). In this study, we assess the efficiency of ultrasound in the response assessment of NACT in patients with LABC using RECIST criteria and its correlation to the final histopathological report. Methods: 40 patients with LABC underwent clinical examination and ultrasonography (USG) of the bilateral breast and axilla before starting NACT. After receiving three cycles of NACT, a repeat USG and clinical examination were done to assess the response to chemotherapy. Patients with responsive disease underwent radical surgery, and we correlate the findings of histopathological examination (HPE) with those of post-NACT USG findings. Results: After three cycles of NACT, clinical examination showed a complete response in 15 (37.5%) patients and a partial response in 21 (52.5%) patients. While USG detected a complete response in 8 (20%) patients and a partial response in 28 (70%) patients, seven patients, in whom clinical examination did not find any disease, were detected by USG. HPE showed a complete pathological response in 5 specimens, and in the rest of 31 cases, HPE revealed a residual tumor. USG did not miss any of the pCR cases but overestimated CR cases by 9% (3 patients). On the other hand, all partial response diagnoses by USG were acknowledged by HPE. Conclusion: To conclude, it can be said that USG can be used as an effective radiological tool for response assessment and subsequent treatment decisions, especially in places where there is a lack of infrastructure and affordability.

Hypogonadism - when does genetic diagnosis help in therapy?

The objective of the study was to describe phenotype-genotype correlation in selected cases with infertility and emphasise the importance of genetic testing as useful tool for proper treatment decision making MATERIAL AND METHODS: Genetic tests were performed in four patients as a part of diagnostic procedure by Sanger sequencing or targeted next generation sequencing (NGS gene panel). We found the genetic causes of hypogonadotropic hypogonadism in 3 males and female with infertility. Genetic testing is carried out when searching for the genetic causes of clinically identified disorders. Genetic diagnostics may also be extremely helpful in treating hypogonadism but requires the assistance of a clinician endocrinologist or andrologist, as well as a geneticist.

Qualitative user experience evaluation of the MS trust's online treatment decision aid tool's accommodation of planning pregnancy.

Decision-making about treatment when planning a pregnancy (family planning) is complex for women living with multiple sclerosis (MS). Decision tools can help this process, in 2016 MS Trust launched their online digital treatment decision tool to support people with MS. To evaluate user-experience of this tool by exploring women's opinions about its content, interface, and usefulness in the context of family planning; and to synthesize recommendations to improve the tool. Thirty participants qualitatively evaluated the tool using Think Aloud methodology. Sessions were conducted online using Microsoft Teams and were video recorded. Transcription was automated and data were thematically analyzed. Women's first impression was that the tool presented a lot of information at once, which was difficult to take in, and they found it difficult to navigate. Although the tool was helpful in allowing them to compare treatment options, the filters were confusing, and the information related to pregnancy sometimes contradicted advice from their healthcare practitioners. They suggested rewording the pregnancy recommendations and filters, updating some content, and making some changes to the interface to meet users' cognitive needs. The MS Trust treatment decision tool is excellent in helping women with treatment choices at initial diagnosis. However, it is not currently as useful when considering family plans. Recommendations were conveyed to MS Trust where some are now applied to the new live version and the rest are to be considered for future updating projects.

Development and Comparison of Treatment Decision Tools for Glucocorticoid-Induced Osteoporosis.

Long-term Glucocorticoid (GC) use results in compromised bone strength and fractures, and several treatment recommendations have been developed to prevent fractures, but none have been validated in a real-world setting. This study aims to create a treatment decision tool and compares this tool to the treatment suggestions from the American College of Rheumatology (ACR), International Osteoporosis Foundation and European Calcified Tissue Society (IOF-ECTS), and GC-adjusted Fracture Risk Assessment Tool (GC-FRAX), above the intervention threshold. We utilized registry data gathered at Chang Gung Memorial Hospital at Kaohsiung, Taiwan, between September 2014 and April 2021. This research is a single-center, observational, and case-controlled study. We recruited participants using prednisone for at least 2.5 mg/day or the equivalent dose for over 3 months, excluding those younger than 40, those with malignancies, or those currently undergoing anti-osteoporosis therapy. The primary endpoint was new fragility fractures within 3 years, including morphometric vertebral fractures detected at baseline and with a follow-up thoracic-lumbar spine X-ray. Participants were randomly allocated into derivation and validation sets. We developed the Steroid-Associated Fracture Evaluation (SAFE) tool in the derivation cohort by assessing the weights of exploratory variables via logistic regression. Prediction performance was compared in the validation set by the receiver operating characteristic (ROC) curve, the area under the curve (AUC), and sensitivity and specificity. A total of 424 treatment-naïve subjects were enrolled, and 83 (19.6%) experienced new fractures within 3 years. The final formula of the SAFE tool includes osteoporosis (1 point), an accumulated GC dose ≥ 750 mg within 6 months (or equivalent prednisolone of ≥4.5 mg/day for 6 months) (1 point), a BMI ≥ 23.5 (1 point), previous fractures (1 point), and elderliness of ≥70 years (2 points). In the validation set, a treatment decision based on the SAFE ≥ 2 points demonstrated an AUC of 0.65, with a sensitivity/specificity/accuracy of 75.9/54.0/58.9, with an ACR of 0.56 (100.0/11.0/31.0), IOF-ECTS 0.61 (75.9/46.0/52.7), and GC-FRAX 0.62 (82.8/42.0/51.2). Among current GIOP recommendations, the SAFE score serves as an appropriate treatment decision tool with increased accuracy and specificity.

HoLy-Net: Segmentation of histological images of diffuse large B-cell lymphoma

Over the last years, there has been large progress in automated segmentation and classification methods in histological whole slide images (WSIs) stained with hematoxylin and eosin (H&E). Current state-of-the-art (SOTA) techniques are based on diverse datasets of H&E-stained WSIs of different types of predominantly solid cancer. However, there is a scarcity of methods and datasets enabling segmentation of tumors of the lymphatic system (lymphomas). Here, we propose a solution for segmentation of diffuse large B-cell lymphoma (DLBCL), the most common non-Hodgkin's lymphoma. Our method applies to both H&E-stained slides and to a broad range of markers stained with immunohistochemistry (IHC). While IHC staining is an important tool in cancer diagnosis and treatment decisions, there are few automated segmentation and classification methods for IHC-stained WSIs. To address the challenges of nuclei segmentation in H&E− and IHC-stained DLBCL images, we propose HoLy-Net - a HoVer-Net-based deep learning model for lymphoma segmentation. We train two different models, one for segmenting H&E− and one for IHC-stained images and compare the test results with the SOTA methods as well as with the original version of HoVer-Net. Subsequently, we segment patient WSIs and perform single cell-level analysis of different cell types to identify patient-specific tumor characteristics such as high level of immune infiltration. Our method outperforms general-purpose segmentation methods for H&E staining in lymphoma WSIs (with an F1 score of 0.899) and is also a unique automated method for IHC slide segmentation (with an F1 score of 0.913). With our solution, we provide a new dataset we denote LyNSeC (lymphoma nuclear segmentation and classification) containing 73,931 annotated cell nuclei from H&E and 87,316 from IHC slides. Our method and dataset open up new avenues for quantitative, large-scale studies of morphology and microenvironment of lymphomas overlooked by the current automated segmentation methods.

Predictive Value of Minimal Residual Disease for Efficacy of Rituximab Maintenance in Mantle Cell Lymphoma: Results From the European Mantle Cell Lymphoma Elderly Trial.

The outcome of older patients with mantle cell lymphoma (MCL) has improved by the introduction of immunochemotherapy, followed by rituximab (R)-maintenance. Assessment of minimal residual disease (MRD) represents a promising tool for individualized treatment decisions and was a prospectively planned part of the European MCL Elderly trial. We investigated how MRD status influenced the efficacy of R-maintenance and how MRD can enable tailored consolidation strategies. Previously untreated patients with MCL age 60 years or older have been randomly assigned to R versus interferon-alpha maintenance after response to rituximab, fludarabine, cyclophosphamide (R-FC) versus rituximab, cyclophosphamide, doxorubicin, vincristine, prednisone (R-CHOP). MRD monitoring was performed by real-time quantitative polymerase chain reaction (qPCR) following EuroMRD guidelines. A qPCR assay with a median sensitivity of 1 × 10-5 could be generated in 80% of 288 patients in an international, multicenter, multilaboratory setting. More extensive tumor dissemination facilitated the identification of a molecular marker. The efficacy of R-maintenance in clinical remission was confirmed for MRD-negative patients at the end of induction in terms of progression-free survival (PFS; hazard ratio [HR], 0.38 [95% CI, 0.21 to 0.63]) and overall survival (OS; HR, 0.37 [95% CI, 0.20 to 0.68]), particularly in R-CHOP-treated patients (PFS-HR, 0.23 [95% CI, 0.10 to 0.52]; OS-HR, 0.19 [95% CI, 0.07 to 0.52]). R-maintenance appeared less effective in MRD-positive patients (PFS-HR, 0.51 [95% CI, 0.26 to 1.02]) overall and after R-CHOP induction (PFS-HR, 0.59 [95% CI, 0.28 to 1.26]). R-FC achieved more frequent and faster MRD clearance compared with R-CHOP. MRD positivity in clinical remission after induction was associated with a short median time to clinical progression of approximately 1-1.7 years. The results confirm the strong efficacy of R-maintenance in patients who are MRD-negative after induction. Treatment de-escalation for MRD-negative patients is discouraged by our results. More effective consolidation strategies should be explored in MRD-positive patients to improve their long-term prognosis.

A Novel Online Decision Support Tool to Determine Practice Patterns and Concordance with Experts in the Treatment of Patients with Immune Thrombocytopenia

Background: Immune thrombocytopenia (ITP) is a complex disease involving dysregulation of the immune system with inadequate platelet production and increased platelet destruction. When treatment is warranted, corticosteroids are frequently used as first-line therapy. Steroid-refractory patients eventually require alternative treatments, of which there are several approved and well-studied options. However, these second-line treatments have not been rigorously compared in clinical trials. To assist healthcare professionals (HCPs) in managing patients with ITP, we developed an online interactive decision support tool to provide expert recommendations for treatment. Here we report an analysis of practice patterns among HCPs and experts for ITP cases after initial therapy failure and the impact of expert recommendations on HCP decisions. Methods: An online tool was developed with 4 experts providing recommendations on management of 332 unique patient cases based on patient- and disease-specific factors that the experts considered relevant to making treatment decisions. HCPs entered patient case details including age, treatment setting, platelet count, current presentation, and presence of risk factors for bleeding, along with their intended management approach, before being shown the expert recommendations for their specific scenario. Results: Between October 2022 and July 2023, 311 patient cases were entered by 256 HCPs, including 194 (62.4%) cases of treatment-exposed patients (Table). Of the treatment-exposed cases, 72.1% were submitted by physicians, and 23.2% were submitted by HCPs in North America. There was strong alignment between HCP treatment selection and at least 1 expert recommendation (69%; P = .0001). There was consensus among experts for 94.4% of cases with patients ≥21 years of age who were treatment exposed. In these cases, experts recommended thrombopoietin receptor agonists (TPO-RA) for 83.5% of cases in contrast to HCPs recommending them in 38.2% of cases. Alternatives for TPO-RA chosen by HCPs in cases with patients ≥21 years of age who were treatment exposed included rituximab (29.6%), immunoglobulin (23.5%), fostamatinib (12.5%), splenectomy (9.8%), observation (8.6%), or unsure (16%). There was consensus among experts for 72% of cases with patients <21 years of age who were treatment exposed. For cases with patients <21 of age who were treatment exposed, HCPs chose immunoglobulin (28.6%), observation (28.6%), rituximab (14.3%), splenectomy (4.7%), or unsure (23.8%). In 47.6% of cases where HCPs indicated an alternative selection, they indicated that expert recommendations changed their treatment choice. HCPs indicated there were barriers to implementation in 7% of indicated cases. Conclusion: Based on our analysis of an online treatment decision tool, practice patterns for the management of patients with ITP aligned between HCPs and at least 1 tool expert in 69% of treatment-experienced cases. For previously treated patients, HCPs were less likely to choose a TPO-RA compared with tool experts, although very few identified barriers to implementation. Although specific treatment utilization patterns differed between HCPs and experts based on data from this tool, HCPs appeared amenable to practice changes based on expert recommendations. Online decision support tools can offer opportunities for HCPs to receive education and expert guidance in choosing optimal treatment regimens for ITP, a condition where treatment guidelines may not address every unique patient scenario.

Non-invasive CT imaging biomarker to predict immunotherapy response in gastric cancer: a multicenter study

BackgroundDespite remarkable benefits have been provided by immune checkpoint inhibitors in gastric cancer (GC), predictions of treatment response and prognosis remain unsatisfactory, making identifying biomarkers desirable. The aim of this...

Psychiatric mental health nurse practitioner student knowledge and perceptions of pharmacogenetic testing.

Psychotropic medications are typically prescribed in a trial-and-error fashion, and some providers are beginning to utilize pharmacogenetic testing (PGx) as a supplemental prescribing tool in treatment decision making. PGx testing shows potential in enhancing provider insights into personalized prescribing for patients by examining genetic information related to drug metabolism. Literature points to providers' lack of knowledge in PGx interpretation as a main barrier, including psychiatric mental health nurse practitioners (PMHNPs). The aim of this study was to measure a difference, if any, in the knowledge and perceptions of PGx after implementation using a pre-post design. This study implemented an educational intervention on graduate nursing students (n = 15). Data were collected by using a pre- and post-interventional questionnaire. Results demonstrated a significant difference in findings related to students' knowledge (p < 0.001), students' skills related to pharmacogenetics, (p < 0.001), as well as students' perceived ability to implement pharmacogenetics into their practice, (p = 0.028). The authors propose that the knowledge gained from the study demonstrates the importance of introducing PGx education into the PMHNP curricula and to prepare future PMHNPs to confidently utilize PGx in their clinical practice.

Advanced cervical cancer therapy: Comparison of contemporary expert and healthcare professional recommendations from an online treatment decision tool.

5528 Background: Practice patterns for the management of advanced cervical cancer are rapidly evolving given the emergence of novel treatment options. We developed an online Interactive Decision Support Tool (IDST) for advanced cervical cancer to provide expert guidance to healthcare professionals (HCPs). Methods: With input from 5 experts, an IDST was developed for patient scenarios with newly diagnosed (ND) and recurrent/second-line (2L) advanced cervical cancer. The IDST included expert insights on 352 scenarios based on criteria such as adenopathy, disseminated disease status, previous therapy, and actionable biomarkers (PD-L1, MMR/MSI, TMB). Users were asked to enter specific patient criteria and their intended management approach. The IDST then showed the 5 expert recommendations for that specific scenario and HCPs were asked to indicate whether the recommendations changed their intended treatment plan. Expert recommendations vs user-selected therapy for different scenarios were analyzed. We present self-reported practice patterns in this disease setting and the impact of expert recommendations on treatment choice. Results: At this interim analysis, 141 unique learners used the IDST, entering 232 unique patient scenarios. Data from the IDST also showed areas of consensus and controversy in treating patients with advanced cervical cancer. For locally advanced, ND, no adenopathy and no metastases, all experts recommended pelvic chemoradiation with or without brachytherapy vs only 61% of HCPs; 16% and 3% of those entering cases for the locally advanced ND setting indicated expert recommendation changed their treatment choice and that barriers impeded the recommendations, respectively. For advanced ND, with adenopathy, metastatic, PD-L1–positive cervical cancers, all experts vs 50% of HCPs chose an immunotherapy-containing platinum-based chemotherapy regimen with/without bevacizumab; 9% of those indicated barriers to implementing expert recommendations. In 2L recurrent disease, all experts chose either single-agent immunotherapy (if PD-L1 positive) or tisotumab vedotin (if PD-L1 negative) vs 45% and 40% of HCPs, respectively; 19% of those selecting 2L therapy in the recurrent setting said the expert recommendations had changed their intended choice. Conclusions: Analysis from this IDST indicates differences in practice patterns between experts and HCPs for various case scenarios of advanced cervical cancer. Online decision support tools may increase the number of HCPs making optimal treatment decisions for advanced cervical cancer, particularly when new data, indications, and guideline updates must be considered. Updated and detailed analyses from the IDST will be presented.

Estimating individual treatment effects on COPD exacerbations by causal machine learning on randomised controlled trials

RationaleEstimating the causal effect of an intervention at individual level, also called individual treatment effect (ITE), may help in identifying response prior to the intervention.ObjectivesWe aimed to develop machine learning...

Molecular Profiling in Early ER + Breast Cancer to Aid Systemic Therapy Decisions.

Clinical decisions for (neo)adjuvant treatment in early breast cancer (eBC) have been based mostly on clinical factors over the last decades. We have reviewed development and validation of such assays in the HR + /HER2 eBC and discuss possible future directions in this field. Increasing knowledge about the biology of hormone-sensitive eBC, based on the precise and reproducible multigene expression analysis, has led to a significant change in the treatment pathways and reduction of overtreatment in particular by chemotherapy in HR + /HER2 eBC with up to 3 positive lymph nodes based on results from several retrospective-prospective trials used several genomic assays and in particular prospective trials (TAILORx, RxPonder, MINDACT, and ADAPT used OncotypeDX® and Mammaprint®). Precise evaluation of tumor biology together with endocrine responsiveness assessment appears as promising tools for individualized treatment decisions together with clinical factors and menopausal status in early hormone-sensitive/HER2-negative breast cancer.

Nomogram based on preoperative conventional ultrasound and shear wave velocity for predicting central lymph node metastasis in papillary thyroid carcinoma.

To establish a nomogram for predicting cervical lymph node metastasis (CLNM) based on the preoperative conventional ultrasound (US) and shear wave velocity (SWV) features of papillary thyroid carcinoma (PTC). A total of 101 patients with pathologically confirmed thyroid nodules were enrolled. These patients were divided into the CLNM-positive (n = 40) and CLNM-negative groups (n = 61). All patients underwent the preoperative conventional US and shear wave elastography (SWE) evaluation, and the US parameters and SWV data were collected. The association between SWV ratio and CLNM was compared to assess the diagnostic efficacy of SWV ratio alone as opposed to SWV ratio in combination with the conventional US for predicting CLNM. There were significant differences in shape, microcalcification, capsule contact, SWV mean, and SWV ratio between the CLNM-positive and CLNM-negative groups (P < 0.05). Logistic regression analysis showed that taller-than-wide shape, microcalcification, capsule contact, and SWV ratio > 1.3 were risk factors for CLNM; Logistic(P)=-6.93 + 1.647 * (microcalcification)+1.138 * (taller-than-wide-shape)+1.612 * (capsule contact)+2.933 * (SWV ratio > 1.3). The area under the curve (AUC) of the receiver operating characteristic (ROC) of the model for CLNM prediction was 0.87, with 81.19% accuracy, 77.5% sensitivity, and 85.25% specificity. The nomogram based on conventional US imaging in combination with SWV ratio has the potential for preoperative CLNM risk assessment. This nomogram serves as a useful clinical tool for active surveillance and treatment decisions.

Relapse-free and overall survival in patients with non-seminomatous testicular germ cell tumours with teratoma-free primaries.

421 Background: Characteristics and outcome of non-seminomatous testicular germ cell tumours (NSGCT) with teratoma-containing primaries are still under debate. Methods: We performed a retrospective analysis including 557 patients with metastatic NSGCT as a registry study within the "German Testicular Cancer Study Group". Results: Of the eligible 557 patients with NSGCT, 237 (42%) of all orchiectomy specimens had teratoma-containing primaries, while 320 (58%) were teratoma-free. Teratoma-containing primaries had a significantly higher clinical stage (p=0.002) and worse prognosis (p=0.051) compared to teratoma-free specimens. Lymph node metastasis were significantly larger before (4.5 vs 2.5cm; p&lt;0.001) and after chemotherapy (3.5 vs 2.5 cm; p&lt;0.001) in teratoma-containing primaries. Post-chemotherapy retroperitoneal lymph node dissection was performed in 57% of all patients. As teratoma-containing specimens revealed a significantly lower number of complete responses after chemotherapy, PC-PRLND was more often performed, with teratomatous elements being more often present in the PC-RPLND specimens compared to non-teratoma containing primaries. Kaplan-Meier estimates revealed that 19% of all patients relapsed during a median follow-up of 56 months [29-112] with a median time to relapse of 10 months. Teratoma-containing had a significantly lower relapse-free survival (RFS) compared to teratoma-free NSGCT (relapse rate 24% vs 16%, p=0.020). 8% (45/533) of all patients died due to their disease. There was no difference regarding the tumour-specific survival between teratoma-containing NSGCT and teratoma-free NSGCT when looking at the entire cohort of patients (8% vs. 9%, p=0.563), however median overall survival was not reached. Conclusions: In our study, NSGCT patients with teratoma-containing primaries showed a significantly higher clinical stage and worse prognosis at time of presentation compared to teratoma-free primaries. Furthermore, patients with teratoma-containing primaries showed a significantly worse relapse-free survival. Consequently, treating physicians should be aware of these patients portending a dismal prognosis and the presence of teratomatous elements might act as a reliable stratification tool for treatment decision in TGCT patients.

Safety and efficacy of an artificial intelligence-enabled decision tool for treatment decisions in neovascular age-related macular degeneration and an exploration of clinical pathway integration and implementation: protocol for a multi-methods validation study

IntroductionNeovascular age-related macular degeneration (nAMD) management is one of the largest single-disease contributors to hospital outpatient appointments. Partial automation of nAMD treatment decisions could reduce demands on clinician time. Established...