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230 citation(s) found for "Da, Fei".

Derivation and External Validation of a Venous Thromboembolism Risk Prediction Model in Patients with Acute Lymphoblastic Leukemia Receiving Asparaginase Therapy
Anderson, Daniela , Gangaraju, Radhika , Sedhom, Wafik, O'Dwyer, Kristen M., Muthiah, Chandrasekar, Liedtke, Michaela , Shimony, Shai , Robinson, Renana , Dinner, Shira, Biemond, Bart J. , Seymour, Kimberly, Goldberg, Leah, Kapadia, Anjani , Levavi, Hannah , Bar‐Natan, Michal , Bansal, Karan, Gerrits, Anke M, Luger, Selina M. , Shomali, William , Shimony, Shai , Hamulyák, Eva N. , Wang, Tzu‐Fei , O'Dwyer, Kristin , Carney, Brian J. , Badar, Talha , Sanfilippo, Kristen , Derkach, Andriy , Biemond, Bart J. , Nemirovsky, David , Hyfte, Grace Van , Carrier, Marc , Fulcher, Jill , Gerrits, Anke M, Murthy, Guru Subramanian Guru , Luskin, Marlise R , Wolach, Ofir , Zwicker, Jeffrey I , Stock, Wendy , Leader, Avi

Blood | December 6, 2024 | Volume: 144 | Issue: Supplement 1 | Pages: 1250-1250

10.1182/blood-2024-201997 Get It

Background: Patients with acute lymphoblastic leukemia (ALL) receiving L-asparaginase (ASP) based induction therapy have a high risk of venous thromboembolism (VTE). Studies investigating universal thromboprophylaxis strategies have yielded sub-optimal results. Risk prediction models are needed to identify high-risk patients who would be candidates for intensification of thromboprophylaxis, and lower risk patients who are unlikely to benefit. Aims: Derive and externally validate a risk prediction model for VTE in patients with ALL receiving ASP therapy. Methods: We conducted a multicenter, international, cohort study of patients with newly-diagnosed ALL receiving ASP-based induction therapy (≥18yrs). The derivation and external validation cohorts included 306 and 97 patients without VTE prior to ASP therapy, respectively. Patients on therapeutic anticoagulation at index were excluded. Patients were followed from date of first ASP dose for 100 days post ALL diagnosis or until VTE, therapeutic anticoagulation or death. Candidate predictors were documented at ALL diagnosis and included demographics, disease and treatment characteristics, VTE history, comorbidities, thromboprophylaxis, complete blood count, fibrinogen and d-dimer. D-dimer was only analyzed within the 7 derivation cohort centers who routinely tested this at ALL diagnosis with <20% missing values. Primary outcome was VTE at any site (centrally confirmed). Secondary outcomes included major bleeding by ISTH criteria. Cause-specific Cox proportional hazard regression was performed to identify VTE risk factors in the derivation cohort while treating death as a competing event. Variables with p-value <0.1 on univariable analysis were included in a multivariable model and subsequently used in the risk model if p-value <0.05. Lastly, the derived VTE risk prediction model was tested in the external validation cohort for association with time to VTE using cause-specific Cox proportional hazard model. All analyses were stratified by center and use of low molecular weight heparin prophylaxis (at any dose on the date of first ASP dose). Results: The cumulative incidence of VTE in the derivation cohort was 17% at 30 days (95% confidence interval [CI] 13% - 21%) and 22% at 90 days (95% CI 17% - 27%). The multivariable model included hyperlipidemia (hazard ratio [HR] 1.35; 95% CI 0.56 - 3.27), body mass index ≥ 25 kg/m² (HR 1.49; 95% CI 0.75 - 2.95), platelet count ≥ 25 x 10⁹/L (HR 1.42; 95% CI 0.67 - 3.00), increasing hemoglobin per 1 g/dL (HR 1.17; 95% CI 1.03 - 1.32) and d-dimer ≥ 1 µg FEU/mL (HR 2.68; 95% CI 1.08 - 6.66). Hemoglobin as a continuous variable and d-dimer ≥ 1 µg FEU/mL were included in the final model and used to create a risk score which was weighted by estimated log-HR sum of these risk factors. The lowest risk quartile (risk score below 2.1) successfully differentiated between a lower 30-day cumulative VTE incidence (4%, 95% CI 0.72% - 12%) compared with the other quartiles (20%, 95% CI 14% - 27%; HR 4.40, 95% CI 1.54 - 12.5) which were defined as high risk (score ≥2.1). The risk score's negative predictive value (NPV) for VTE at 30 days was 96% and positive predictive value (PPV) was 20%. The validation cohort (n=97 from 3 external cohorts with routine d-dimer measurement) included 16 (16.5%) patients in the low-risk group and 81 (83.5%) in the high-risk group, with a 30-day VTE incidence of 6.3% (95% CI 0% - 17%) and 21% (95% CI 12% - 30%), respectively (HR 6.22; 95% CI 0.85 - 45.8; p = 0.073)). The NPV (93.7%) and PPV (21%) were comparable to the derivation cohort. The 30-day incidence of major bleeding was 0% (95% CI NR - NR) in low-risk patients (HR 1.36; 95% CI 0.27 - 6.77) and 2.0% (95% CI 0.55% - 5.4%) in the high-risk group. Conclusion: Patients with ALL receiving ASP induction therapy have a 17% VTE risk at 30 days. We derived and externally validated a VTE risk prediction model based upon d-dimer and hemoglobin. This model successfully identifies at least 16.5% of patients with ALL who have a low VTE risk after ASP treatment. Using this model, novel prevention strategies which may be associated with cost and risk could now be tailored to patients with higher risk. Prospective studies are needed to validate the model's performance and role in VTE risk management.
The Predictive Value of Cell-of-Origin Subtype By Hans Algorithm in 718 Patients with Large B Cell Lymphoma Receiving Polatuzumab Vedotin
Pelaez, Guido D, Abdel-Razeq, Nayef , Allen, Jessica M, Gould, Patrick, Houshyar, Samin , Lynch, Ryan C. , Fleyshman, Michelle , Kidwell, Adam , Fenske, Timothy S. , Mulvey, Erin , Nowakowski, Grzegorz S. , Torka, Pallawi , Russler‐Germain, David A. , Chung, Kevin , Allen, J. , Allen, Jessica , Russler-Germain, David A , Cliff, Edward R. Scheffer , Pelaez, Guido D, Wan, Fei , Iyengar, Varun , Zhou, Jihao , Chung, Kevin, Major, Ajay , Sharp, John , Epperla, Narendranath , Cherng, Hua‐Jay J. , Wallace, Danielle , Kallam, Avyakta , Mei, Matthew , Merryman, Reid W. , Rhodes, Joanna , Watkins, Marcus P. , Moustafa, Muhamad Alhaj , Hilal, Talal , Wang, Yucai

Blood | December 5, 2024 | Volume: 144 | Issue: Supplement 1 | Pages: 652-652

10.1182/blood-2024-202153 Get It

Background: Polatuzumab vedotin (Pola) is an antibody drug conjugate targeting CD79b that incorporates the microtubule disrupting monomethyl auristatin E payload. Pola was approved in 2023 for the upfront treatment of diffuse large B cell lymphoma (DLBCL) in combination with rituximab, cyclophosphamide, doxorubicin, and prednisone (polaRCHP) based on the POLARIX trial. However, the activity of pola appears to vary based on DLBCL cell of origin (COO) subtype, with greater efficacy in activated B cell (ABC) DLBCL compared to germinal center B cell (GCB) DLBCL (Russler-Germain Blood 2023). When outcomes in POLARIX are stratified by COO, polaRCHP demonstrated progression free survival (PFS) and overall survival (OS) benefits over RCHOP in patients with ABC but not GCB subtype DLBCL (PFS HR 0.34 ABC vs 1.03 GCB, OS HR 0.27 ABC vs 1.64 GCB; Morschhauser ASH 2023 and FDA data). Most prospective studies of pola used gene expression to assess COO, which is not readily clinically available. This study aims to examine if COO subtype by Hans algorithm (based on CD10, BCL6, and MUM1 expression by immunohistochemistry) is predictive of pola responses and outcomes in patients with large B cell lymphoma (LBCL). Methods: We conducted a retrospective, multicenter observational study of adults with LBCL who received pola (monotherapy or in combination) from 2015-2024 with Hans algorithm COO data and response assessment available. Patients were stratified by receipt of pola in the frontline vs relapsed/refractory (R/R) setting. The primary endpoint was overall response rate (ORR) to pola-based treatment in GCB vs non-GCB subtypes. Secondary endpoints included complete response rate (CRR), PFS, and OS. For time to event endpoints, patients responding to pola who received CAR T or stem cell transplantation prior to progression were censored at time of cellular therapy. Demographics were summarized by descriptive statistics. Comparative and survival analyses used Chi squared/Fischer exact tests and Kaplan Meier analysis. Data cutoff was July 1, 2024. Results: 718 patients were included. Median follow-up was 15 months (interquartile range [IQR] 8-32). Median age at LBCL diagnosis was 66 years (IQR 56-74); 62% were men; 69 (10%) had double hit lymphoma (DHL); 129 (18%) had underlying low grade lymphoma. Pola was used in the frontline setting in 293 (41%) patients, of whom 139 (47%) had GCB vs 154 (53%) non-GCB COO. Of the 426 patients receiving pola for R/R LBCL (including one patient receiving pola retreatment), 224 (53%) had GCB vs 202 (47%) non-GCB COO. Among patients receiving pola-based regimens in the R/R setting (GCB vs non-GCB: pola monotherapy = 7% vs 4%, pola + R = 26% vs 26%, pola + BR = 55% vs 61%, pola + other = 12% vs 9%; p = 0.44), the ORR in GCB vs non-GCB LBCL was 36% vs 61% (p < 0.001), while CRR in GCB vs non-GCB was 17% vs 36% (p < 0.001). COO remained a significant component of logistic multivariate regression models of ORR (p < 0.001) and CRR (p < 0.001) when incorporating IPI at original LBCL diagnosis, histology, DHL status, and refractory status to frontline therapy. Despite this, no significant PFS or OS differences by COO were seen, potentially due to approximately 1/4 patients being censored due to receiving subsequent cellular therapy (e.g. CAR T) prior to progression. In patients receiving frontline pola-based regimens (of which 275 [94%] included an anthracycline), ORR and CRR were similar in GCB vs non-GCB (ORR 89% vs 88% p > 0.5; CRR 76% vs 77% p > 0.5). While PFS and OS were similar between COO groups in the frontline cohort, follow-up and cohort size were limited. Conclusion: Based on this real-world evidence, COO classification by Hans algorithm is a strong predictor of the activity of pola-containing therapy in R/R LBCL, with significantly higher ORR and CRR in patients with non-GCB compared to GCB COO LBCL. This aligns with the cumulative existing evidence. ORR and CRR to pola-containing therapy in the frontline setting did not differ significantly by COO subtype, but longer follow-up of larger cohorts is needed to clarify the predictive role of COO by Hans algorithm in this setting, especially considering the PFS advantage with polaRCHP in POLARIX was not associated with significant differences in ORR or CRR. Overall, clinicians should consider factoring COO subtype into treatment decisions regarding pola-containing regimens, and studies of pola-based therapies should stratify patients and report outcomes by COO subtype.
A High-Fiber Dietary Intervention (NUTRIVENTION) in Precursor Plasma Cell Disorders Improves Biomarkers of Disease and May Delay Progression to Myeloma
Cogrossi, Laura Lucia , Policastro, Anna , Jenna, Blaslov, Adintori, Peter , McAvoy, Devin , Baichoo, Mirae , Anuraj, Aishwarya , Pohl, Charlotte , Sanchez, Jenny Paredes, Gipson, Brianna , Block, Torin , Korde, Neha , Tan, Carlyn , Hultcrantz, Malin , Hassoun, Hani , Scordo, Michael , Landau, Heather J., Chesi, Marta, Bergsagel, P. Leif , Mailankody, Sham , Giralt, S., Iyengar, Neil M. , Pohl, Charlotte , Shah, Urvi A. , Derkach, Andriy , Castro, Francesca , Fei, Teng , DeWolf, Susan , Garcés, Juan‐José , Grioni, Matteo , Sisti, Sofia , Hosszu, Kinga K , Cross, Justin R , Ramos, Ruben, Maclachlan, Kylee , Gradissimo, Ana , Boiocchi, Leonardo , Koche, Richard P , Chaligne, Ronan , Shah, Gunjan L. , Lahoud, Oscar , Chung, David J , Landau, Heather , Peled, Jonathan U. , Clementi, Nicola , Chesi, Marta , Bergsagel, P. Leif , Pollak, Michaël , D’Souza, Anita , Landgren, Ola , Chimonas, Susan , Usmani, Saad Z. , Lesokhin, Alexander M. , Bellone, Matteo , van den Brink, Marcel R M

Blood | December 5, 2024 | Volume: 144 | Issue: Supplement 1 | Pages: 671-671

10.1182/blood-2024-202224 Get It

Introduction Poor diet quality, elevated body mass index (BMI), insulin resistance, microbiome dysbiosis, inflammation as well as immune dysfunction have all been implicated in progression from monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM) to multiple myeloma (MM). Plant-based diets have been associated with reduced risk of MGUS and MM in epidemiological studies. Whether a dietary intervention can impact these modifiable risk factors and delay disease progression has not been investigated. Methods We conducted a pilot, single-arm trial providing controlled high fiber plant based dietary (HFPBD) intervention for 12 weeks and health coaching for 24 weeks in 20 patients with MGUS/SMM with BMI≥25 (NCT04920084). The primary endpoint was feasibility (adherence and BMI reduction). Secondary and exploratory endpoints included quality of life, metabolic markers (insulin, adiponectin, leptin, LDL cholesterol), microbiome (diversity and composition by 16S and shotgun sequencing) and immune profiling in peripheral blood (flow cytometry and Olink inflammation panel) and bone marrow (scRNAseq and ATACseq). We also conducted an in vivo study in transgenic Vk*MYC mice fed a high fiber or control diet at the phase of mouse(m)SMM. The mice were monitored for the progression to active mMM. Differences in microbiome and immune response profiles between high fiber- and control-treated mice were assessed via microbiome 16S sequencing and flow cytometry. Results The HFPBD intervention was safe, feasible, improved quality of life and addressed modifiable risk factors - metabolic profile (improved BMI, insulin resistance, adiponectin leptin ratio), microbiome profile (increased alpha-diversity and butyrate producers) and immune (decreased inflammation and increased anti-inflammatory classical monocyte) subsets. A reduction in long-term progression trajectory was observed in 2 patients. Consistently, the high fiber diet delayed progression from mSMM to mMM in Vk*MYC mice increasing median progression-free survival from 12 weeks in the control arm to 30 weeks in the high fiber diet intervention arm. Additionally, in the intervention arm 40% of mice did not progress to mMM during the study period whereas all mice in the control arm progressed. Both human and mouse data showed that HFPBD modulated gut microbiota composition favoring the expansion of butyrate-producing bacteria. Additionally, short-chain fatty acids were increased in the feces of mice fed a high fiber diet. Integrated analysis from human bone marrow and peripheral blood analysis indicated that the dietary intervention reduced inflammatory biomarkers and skewed the immune response towards T helper and CD14+ monocytes. Consistently, the bone marrow of Vk*MYC mice fed high fiber diet was more infiltrated by IFNg-producing T lymphocytes while displaying less exhausted T cells and immunosuppressive myeloid cells. Conclusion This is the first interventional clinical trial and in vivo study to show that a HFPBD intervention may delay progression from MGUS/SMM to MM. To our knowledge there has been no similar dietary interventional study in hematological cancers or solid tumors. Together our in vivo and clinical data support the beneficial anti-inflammatory role of a HFPBD providing a link between diet, microbiota, and immune modulation to delay disease progression in MGUS/SMM.
The Contribution of Corn Trypsin Inhibitor on Thrombin Generation Kinetics in Trauma Patients: A Comparative Analysis
Navarro, Sergio M. , Thompson, Riley J., Spears, Grant M. , Bailey, Kent R. , Dong, Jing-fei, Kozar, Rosemary A. , Pruthi, Rajiv K. , Park, Myung S., Navarro, Sergio Michael , Chen, Dong

Blood | December 5, 2024 | Volume: 144 | Issue: Supplement 1 | Pages: 5529-5529

10.1182/blood-2024-201035 Get It

Trauma-induced coagulopathy (TIC) is common after injury and reliable quantification of its severity is lacking. The objective of this study was to evaluate whether thrombin generation would be significantly altered if whole blood samples from trauma patients were collected without (citrate-only) and with corn trypsin inhibitor (CTI+). In a prospective cohort study, 36 trauma pts presenting to a Level I Trauma Center within 12 hours of injury, had whole blood collected simultaneously in citrate-only (3.2%) and citrated plus CTI (CTI+ [final 25 ug/mL]), and processed to platelet free plasma by double centrifugation (3000g, 15 minutes). Samples were stored at -80C with no thawing until analysis. Thrombin generation profiles were measured using the ST Genesia assay (Diagnostica STAGO SAS) and parameters included endogenous thrombin potential (ETP), lag time (LT), peak height, start of tail, velocity index, and time to peak (ttPeak) were analyzed for trauma pts. Data presented as median [IQR] or n (%), with paired t-test and Spearman's correlation analysis were performed between citrated non-CTI and citrated CTI spiked blood samples, with p-value <0.05 statistically significant. Pts presented with significant injury ISS 13 [5, 21], age 45 [29, 59] years, 80.6% male, BMI 26.9 [25.4, 28.3], 94.4% blunt trauma, 22.3% had surgery by day 1 of admission. Significant differences were found between the citrated-only and CTI +tubes in several thrombin generation parameters: ETP (1339 Nm*min [1172.5,1417], 1124.5 [925.4,1285], p<0.001), peak height (222.3 Nm [186.0, 275.6], 160.6 [132.7,208.3], p<0.001), ttPeak (5.64 min [4.86,6.63], 6.19 [5.36, 7.34], p<0.001), start of tail (19.4 min [17.6,21.3], 21.6 [18.9, 23.6], p=0.014), and velocity index (117.6 Nm/min [77.9, 163.1], 71.9 [54.9,106.0], p<0.001). However, LT (3.14 min [2.74, 3.90], 3.08 [2.84, 3.96], p=0.665) did not show a statistically significant difference. Spearman's correlation analysis showed high correlation between citrate-only and CTI+ citrated plasma samples, with Spearman's rank correlation coefficients for LT (0.941), peak height (0.760), ttPeak (0.928), ETP (0.770), start of tail (0.869), and velocity index (0.766) respectively. The results suggest that use of CTI+ decrease thrombin generation kinetics from blood samples obtained from trauma patients. These findings underscore the need for careful consideration of sample collection and processing for use of thrombin generation assays in clinical setting. However, there is very strong correlation of the thrombin parameters obtained from citrated-only plasma to CTI+ plasma samples, suggesting they capture similar information. CTI-spiked citrated tubes appear to reduce contact activation with respect to thrombin generation profiles compared to standard citrated only tubes. This should be a consideration for platform-based lab processing of thrombin generation assays for assessment of coagulopathy after injury; however, given the cost of CTI, citrated-only tubes can be an option for characterization of thrombin generation profile in clinical samples.
Evaluating large language models in echocardiography reporting: opportunities and challenges
Chao, Chieh-Ju, Banerjee, Imon , Arsanjani, Reza , Ayoub, Chadi , Tseng, Andrew S. , Delbrouck, Jean-Benoit, Kane, Garvan C. , López-Jiménez, Francisco , Oh, Jae K. , Fei-Fei, Li , Adeli, Ehsan, Tseng, A S , Erickson, Bradley, Banerjee, Imon , Lopez-Jimenez, Francisco , Arsanjani, Reza , Chao, Chieh‐Ju , Attia, Zachi I. , Erickson, Bradley J. , Adeli, Ehsan , Langlotz, Curtis P.

European Heart Journal - Digital Health | November 27, 2024 | Volume: 6 | Issue: 3 | Pages: 326-339

10.1093/ehjdh/ztae086 | PMID 40395412 Get It

Abstract Aims The increasing need for diagnostic echocardiography tests presents challenges in preserving the quality and promptness of reports. While Large Language Models (LLMs) have proven effective in summarizing clinical texts, their application in echo remains underexplored. Methods and results Adult echocardiography studies, conducted at the Mayo Clinic from 1 January 2017 to 31 December 2017, were categorized into two groups: development (all Mayo locations except Arizona) and Arizona validation sets. We adapted open-source LLMs (Llama-2, MedAlpaca, Zephyr, and Flan-T5) using In-Context Learning and Quantized Low-Rank Adaptation fine-tuning (FT) for echo report summarization from ‘Findings’ to ‘Impressions.’ Against cardiologist-generated Impressions, the models’ performance was assessed both quantitatively with automatic metrics and qualitatively by cardiologists. The development dataset included 97 506 reports from 71 717 unique patients, predominantly male (55.4%), with an average age of 64.3 ± 15.8 years. EchoGPT, a fine-tuned Llama-2 model, outperformed other models with win rates ranging from 87% to 99% in various automatic metrics, and produced reports comparable to cardiologists in qualitative review (significantly preferred in conciseness (P < 0.001), with no significant preference in completeness, correctness, and clinical utility). Correlations between automatic and human metrics were fair to modest, with the best being RadGraph F1 scores vs. clinical utility (r = 0.42) and automatic metrics showed insensitivity (0–5% drop) to changes in measurement numbers. Conclusion EchoGPT can generate draft reports for human review and approval, helping to streamline the workflow. However, scalable evaluation approaches dedicated to echo reports remains necessary.
OPTIMIZING PERIPROSTHETIC JOINT INFECTION DIAGNOSTICS: THE IMPACT OF INTRAOPERATIVE DIRECT SONICATION ON TIME TO POSITIVITY
Xu, Boyong , Li, Yicheng , Zhang, Xiaogang , Cao, Li , Mu, Wenbo , Tarabichi, Saad , Wang, Fei , Lizcano, Juan D , Parvizi, Javad

Orthopaedic Proceedings | November 22, 2024 | Volume: 106-B | Issue: SUPP_19 | Pages: 42-42

10.1302/1358-992x.2024.19.042 Get It

AimThis study aimed to evaluate the impact of intraoperative direct sonication on the yield of traditional culture and the time to positivity (TTP) of cultures obtained for periprosthetic joint infection (PJI), thereby assessing its potential to improve diagnostic efficiency and reduce contamination risk.MethodA prospective cohort study was conducted at a tertiary care center, involving 190 patients undergoing revision surgery for PJI from August 2021 to January 2024. Patients were included based on the 2018 International Consensus Meeting definition of PJI. The study utilized a novel sonication protocol, which involved direct intraoperative sonication of the implant and tissue, followed by incubation in a BACT/ALERT 3D system. The primary outcomes measured were the number and percentage of positive culture samples, identified microorganisms, and the TTP of each culture. Statistical analysis was performed using R software, with various tests applied to assess the significance of findings.ResultsThe study included 510 positive cultures from 190 patients, demonstrating that sonication significantly improved the positivity rate for both tissue and prosthesis specimens (p < 0.05). The median TTP for all samples was 3.13 days, with sonicated samples showing a significantly shorter TTP compared to non-sonicated samples (p < 0.05). Specifically, the shortest median TTP was observed in prosthesis post-sonication samples. Furthermore, the study found that Gram-positive organisms had a shorter TTP than gram-negative organisms, and specific microorganisms like Staphylococcus aureus and MRSE showed the fastest TTP. The analysis also revealed higher positivity rates in chronic PJIs compared to acute PJIs for sonicated tissue samples.ConclusionsThe study demonstrates that intraoperative direct sonication combined with the BACT/ALERT 3D system can significantly enhance the diagnostic yield of cultures and reduce the TTP for common PJI pathogens. This novel technique not only improves pathogen detection, facilitating the tailoring of antibiotic therapy, but also potentially reduces the risk of contamination associated with sonication. These findings suggest that direct intraoperative sonication could be a valuable addition to the current diagnostic protocols for PJI, contributing to more effective management and treatment of this complex condition. Further research is necessary to explore the clinical significance of TTP and its correlation with patient outcomes in PJI.
Targeted therapeutic strategies for the kidney
Yuan, Fei , Lerman, Lilach O., Yuan, Fei

Expert Opinion on Therapeutic Targets | November 4, 2024 | Volume: 28 | Issue: 11 | Pages: 979-989

10.1080/14728222.2024.2421756 | PMID 39491501 Get It

Longevity biotechnology: bridging AI, biomarkers, geroscience and clinical applications for healthy longevity
Lyu, Yu-Xuan, Wilczok, Dominika , Antebi, Adam , Vojta, Aleksandar , Stolzing, Alexandra , Moskalev, Alexey , Georgievskaya, Anastasia , Maier, Andrea B. , Olsen, Andrea, Groth, Anja , Brunet, Anne , Jamil, Aisyah, Kulaga, Anton , Bhatti, A.R., Yaden, Benjamin C., Djordjevic, Boris, Chen, Chieh, Huang, Christine Yuan, Chen, Danica , Sołdacki, Dariusz, Meyer, David H. , Chini, Eduardo N. , Morgen, Eric , Vernet, Erik , Pinilla, Estefano, Mercken, Evi M. , Finger, Fabian , Kuipers, Folkert , Gyülvészi, Gábor, Zmudze, Garri, Blander, Gil , Pincus, Harold A., McClure, Joshua, Kirkland, James L. , Peyer, James , McLaughlin, Jerry L., Mannick, Joan B. , Betts-LaCroix, Joe , Sedivy, John M. , Speakman, John R. , Shlain, Jordan, Maltzahn, Julia von , Andreasson, Katrin I. , Moody, Kelsey , Fortney, Kristen , Niedernhofer, Laura J., Veenhoff, Liesbeth M. , Melton, Lisa , Quarta, Marco , Koval, Maria, Marinova, Maria B., Hamalainen, Mark, Unfried, Maximilian , Ringel, Michael S. , Filipović, Miloš R. , Topors, Mourad, Mitin, Natalia , Roy, N. N., Pintar, Nika, Barzilai, Nir , Binetti, Paolo, Kohlhaas, Paul, Rubin, Paul , Kamya, Petrina, Muñoz‐Cánoves, Pura , Конрад, Р. , Ripa, Roberto , Mansukhani, Robin, Büttner, Sabrina , Brunemeier, Sebastian, Jakimov, Sergey, Rosenzweig‐Lipson, Sharon, Tsai, Shih‐Yin , Rando, Thomas A. , Peterson, Timothy R. , Woods, Tina , Wyss‐Coray, Tony , Finkel, Toren , Strauss, Tzipora , Longo, Valter D. , Sorrentino, Vincenzo , Sebastiano, Vittorio , Li, Wenbin , Suh, Yousin , Niedernhofer, Laura J. , Lu, Yuxuan , Passos, Joao, Niedernhofer, Laura J , Wyss-Coray, Tony , Bakula, Daniela , Lyu, Yu-Xuan, Fu, Qiang , Ying, Kejun , King, Aaron, Olsen, Andrea, Simon, Anna Katharina , Jamil, Aisyah, Bhatti, Asif, Pedersen, Bente Klarlund , Schumacher, Björn , Kennedy, Brian Keith , Huang, Christine Yuan, Correll, Christoph Ulrich , Murphy, Coleen Tara , Ewald, Collin Y. , Valenzano, Dario Riccardo , Erritzøe, David , Sinclair, David , Teeling, Emma C. , Verdin, Eric , Pinilla, Estéfano , Fang, Evandro Fei , Bischof, Evelyne Y. , Pun, Frank W. , Civiletto, Gabriele , Justice, Jamie N. , Vijg, Jan , Gruhn, Jennifer R. , McLaughlin, Jerry, Passos, João F. , Baur, Joseph A. , Shlain, Jordan, Palikaras, Konstantinos , Rasmussen, Lene Juel , Ferrucci, Luigi , Koval, Maria, Topors, Mourad, Roy, Nawal, Pintar, Nika , Singh, Parminder Pal , Robbins, Paul D. , Fedichev, Peter O. , Cabo, Rafael de , Faragher, Richard , Konrad, Rob, Wickström, Sara A. , Brunemeier, Sebastian A., Luo, Shan , Dimmeler, Stefanie , Gladyshev, Vadim N. , Dwaraka, Varun B. , Gorbunova, Vera , Acosta-Rodríguez, Victoria A. , Suh, Yousin , Zhavoronkov, Alex , Scheibye‐Knudsen, Morten

Aging | October 16, 2024 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.18632/aging.206135 | PMID 39418098 Get It

Development of a Breast Cancer Risk Prediction Model Integrating Monogenic, Polygenic, and Epidemiologic Risk
Kalia, Sarah S. , Boddicker, Nicholas , Yadav, Siddhartha , Huang, Hongyan , Na, Jie , Ambrosone, Christine B. , Yao, Song , Haiman, Christopher A. , Chen, Fei , John, Esther M. , Kurian, Allison W. , Guo, Boya , Lindström, Sara , Auer, Paul L. , Taylor, Jack A. , Hodge, James M. , Lori, Adriana , Bodelón, Clara , Vachon, Celine M. , Goldgar, David E. , Nathanson, Katherine L. , Weitzel, Jeffrey N. , Boddicker, Nicholas J , Hu, Chunling , Ambrosone, Christine B , Yao, Song , Haiman, Christopher A , Chen, Fei , John, Esther M , Kurian, Allison W , Guo, Boya , Lindstrom, Sara , Auer, Paul , Lacey, James V. , Neuhausen, Susan L. , Martı́nez, Marı́a Elena , Sandler, Dale P , O'Brien, Katie M , Taylor, Jack A , Teras, Lauren R , Hodge, James M , Lori, Adriana , Bodelon, Clara , Trentham-Dietz, Amy , Burnside, Elizabeth S , Vachon, Celine M. , Winham, Stacey J , Goldgar, David E , Domchek, Susan M , Nathanson, Katherine L , Weitzel, Jeffrey N , Couch, Fergus J. , Kraft, Peter , Yadav, Siddhartha , Na, Jie , Hu, Chunling , Sandler, Dale P. , O’Brien, Katie M. , Teras, Lauren R. , Trentham‐Dietz, Amy , Burnside, Elizabeth S. , Winham, Stacey J. , Domchek, Susan M. , Couch, Fergus J. , Kraft, Peter

Cancer Epidemiology, Biomarkers & Prevention | September 11, 2024 | Volume: 33 | Issue: 11 | Pages: 1490-1499

10.1158/1055-9965.epi-24-0594 | PMID 39259185 Get It

Abstract Background: Breast cancer has been associated with monogenic, polygenic, and epidemiologic (clinical, reproductive, and lifestyle) risk factors, but studies evaluating the combined effects of these factors have been limited. Methods: We extended previous work in breast cancer risk modeling, incorporating pathogenic variants (PV) in six breast cancer predisposition genes and a 105-SNP polygenic risk score (PRS), to include an epidemiologic risk score (ERS) in a sample of non-Hispanic White women drawn from prospective cohorts and population-based case–control studies, with 23,518 cases and 22,832 controls, from the Cancer Risk Estimates Related to Susceptibility (CARRIERS) Consortium. Results: The model predicts 4.4-fold higher risk of breast cancer for postmenopausal women with no predisposition PV and median PRS, but with the highest versus lowest ERS. Overall, women with CHEK2 PVs had &gt;20% lifetime risk of breast cancer. However, 15.6% of women with CHEK2 PVs and a family history of breast cancer, and 45.1% of women with CHEK2 PVs but without a family history of breast cancer, had low (&lt;20%) predicted lifetime risk and thus were below the threshold for MRI screening. CHEK2 PV carriers at the 10th percentile of the joint distribution of ERS and PRS, without a family history of breast cancer, had a predicted lifetime risk similar to the general population. Conclusions: These results illustrate that an ERS, alone and combined with the PRS, can contribute to clinically relevant risk stratification. Impact: Integrating monogenic, polygenic, and epidemiologic risk factors in breast cancer risk prediction models may inform personalized screening and prevention efforts.