Objectives: To estimate the proportion and correlates of self-reported financial difficulty among patients with multiple myeloma (MM) or chronic lymphocytic leukemia (CLL). Setting: 23 U.S. community and minority oncology practice sites affiliated with the National Cancer Institute Community Oncology Research Program (NCORP). Participants: 521 patients (≥18 years) with MM or CLL were consented and 416 responded to a survey (completion rate=79.8%). Respondents had a MM diagnosis (74.0%), an associate degree or higher (53.4%), were White (89.2%), insured (100%) and treated with clinician-administered drugs (68.0%). Interventions: Observational, prospective, protocol-based survey administered in 2019-2020. Primary and secondary outcome measures: Financial difficulty was assessed using a single-item standard measure, the EORTC QLQC30: Has your physical condition or medical treatment caused you financial difficulties in the past year? and using an any-or-none composite measure of 22 items assessing financial difficulty, worries and the use of cost-coping strategies. Multivariable logistic regression models assessed the association between financial difficulty, diagnosis, and socioeconomic and treatment characteristics. Results: 16.8% reported experiencing financial difficulty using the single-item measure and 60.3% using the composite measure. Most frequently endorsed items in the composite measure were financial worry about having to pay large medical bills related to cancer and difficulty paying medical bills. Financial difficulty using the single-item measure was associated with having MM versus CLL (adjusted odds ratio [aOR], 0.34; 95% CI, 0.13-0.84; P=.02), having insurance other than Medicare (aOR, 2.53; 95% CI, 1.37-4.66; P=.003), being non-White (aOR, 2.21; 95% CI, 1.04-4.72; P=.04), and having a high school education or below (aOR, 0.36; 95% CI, 0.21-0.64; P=.001). Financial difficulty using the composite measure was associated with having a high school education or below (aOR, 0.62; 95% CI, 0.41-0.94; P=.03). Conclusions: U.S. patients with blood cancer report financial difficulty, especially those with low socio-economic status. Evidence-based and targeted interventions are needed.
{"title":"Self Reported Financial Difficulties Among Patients with Multiple Myeloma and Chronis Lymphocytic Leukemia Treated at U.S. Community Oncology Clinics (Alliance A231602CD)","authors":"Rena M. Conti, Shaylene McCue, Travis Dockter, Heather Gunn, Stacie Dusetzina, Antonia Bennett, Bruce Rapkin, Gabriela Gracia, Shelley Jazowski, Elisa Weiss","doi":"10.1101/2024.09.13.24311098","DOIUrl":"https://doi.org/10.1101/2024.09.13.24311098","url":null,"abstract":"Objectives: To estimate the proportion and correlates of self-reported financial difficulty among patients with multiple myeloma (MM) or chronic lymphocytic leukemia (CLL). Setting: 23 U.S. community and minority oncology practice sites affiliated with the National Cancer Institute Community Oncology Research Program (NCORP). Participants: 521 patients (≥18 years) with MM or CLL were consented and 416 responded to a survey (completion rate=79.8%). Respondents had a MM diagnosis (74.0%), an associate degree or higher (53.4%), were White (89.2%), insured (100%) and treated with clinician-administered drugs (68.0%). Interventions: Observational, prospective, protocol-based survey administered in 2019-2020. Primary and secondary outcome measures: Financial difficulty was assessed using a single-item standard measure, the EORTC QLQC30: Has your physical condition or medical treatment caused you financial difficulties in the past year? and using an any-or-none composite measure of 22 items assessing financial difficulty, worries and the use of cost-coping strategies. Multivariable logistic regression models assessed the association between financial difficulty, diagnosis, and socioeconomic and treatment characteristics. Results: 16.8% reported experiencing financial difficulty using the single-item measure and 60.3% using the composite measure. Most frequently endorsed items in the composite measure were financial worry about having to pay large medical bills related to cancer and difficulty paying medical bills. Financial difficulty using the single-item measure was associated with having MM versus CLL (adjusted odds ratio [aOR], 0.34; 95% CI, 0.13-0.84; P=.02), having insurance other than Medicare (aOR, 2.53; 95% CI, 1.37-4.66; P=.003), being non-White (aOR, 2.21; 95% CI, 1.04-4.72; P=.04), and having a high school education or below (aOR, 0.36; 95% CI, 0.21-0.64; P=.001). Financial difficulty using the composite measure was associated with having a high school education or below (aOR, 0.62; 95% CI, 0.41-0.94; P=.03). Conclusions: U.S. patients with blood cancer report financial difficulty, especially those with low socio-economic status. Evidence-based and targeted interventions are needed.","PeriodicalId":501437,"journal":{"name":"medRxiv - Oncology","volume":"44 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142268161","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-18DOI: 10.1101/2024.09.17.24312241
Maxime Brunner, Jenny Meylan-Merlini, Maude Muriset, Sergey Oreshkov, Andrea Messina, Mahmoud Messerer, Roy Thomas Daniel, Ekkehard Hewer, Jean Philippe Brouland, Federico Santoni
The pituitary gland is a main component of the endocrine system and a master controller of hormone production and secretion. Unlike neoplastic formation in other organs, Pituitary Neuroendocrine Tumors (PitNETs) are frequent in the population (16%) and, for unknown reasons, almost exclusively benign. So far, few genes have been identified as drivers for PitNETs, such as GNAS in somatotroph tumors and USP8 in corticotroph tumors. Using whole genome sequencing, we uncover a potential novel driver, the histone methyltransferase KMT2D, in a patient in his 50s suffering from a mixed somato-lactotroph tumor. Coverage ratio between germline and tumor revealed extensive chromosomal alterations. Single-cell RNA sequencing of the tumor shows up-regulation of known tumorigenic pathways compared to a healthy reference, as well as a different immune infiltration profile compared to other PitNETs, more closely resembling the profile of carcinomas than adenomas. Genome-wide DNA methylation analysis identified 792 differentially methylated regions, including notable hypomethylation in the promoter of SPON2, an immune-related gene. Our results show that tumors considered as quiet and non-aggressive can share drivers, features, and epigenetic alterations with metastatic forms of cancer, raising questions about the biological mechanisms controlling their homeostasis.
{"title":"Whole Genome Sequencing and single-cell transcriptomics identify KMT2D as a potential new driver for pituitary adenomas","authors":"Maxime Brunner, Jenny Meylan-Merlini, Maude Muriset, Sergey Oreshkov, Andrea Messina, Mahmoud Messerer, Roy Thomas Daniel, Ekkehard Hewer, Jean Philippe Brouland, Federico Santoni","doi":"10.1101/2024.09.17.24312241","DOIUrl":"https://doi.org/10.1101/2024.09.17.24312241","url":null,"abstract":"The pituitary gland is a main component of the endocrine system and a master controller of hormone production and secretion. Unlike neoplastic formation in other organs, Pituitary Neuroendocrine Tumors (PitNETs) are frequent in the population (16%) and, for unknown reasons, almost exclusively benign. So far, few genes have been identified as drivers for PitNETs, such as GNAS in somatotroph tumors and USP8 in corticotroph tumors. Using whole genome sequencing, we uncover a potential novel driver, the histone methyltransferase KMT2D, in a patient in his 50s suffering from a mixed somato-lactotroph tumor. Coverage ratio between germline and tumor revealed extensive chromosomal alterations. Single-cell RNA sequencing of the tumor shows up-regulation of known tumorigenic pathways compared to a healthy reference, as well as a different immune infiltration profile compared to other PitNETs, more closely resembling the profile of carcinomas than adenomas. Genome-wide DNA methylation analysis identified 792 differentially methylated regions, including notable hypomethylation in the promoter of SPON2, an immune-related gene. Our results show that tumors considered as quiet and non-aggressive can share drivers, features, and epigenetic alterations with metastatic forms of cancer, raising questions about the biological mechanisms controlling their homeostasis.","PeriodicalId":501437,"journal":{"name":"medRxiv - Oncology","volume":"40 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142250429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-18DOI: 10.1101/2024.09.17.24313809
MD Anderson Head and Neck Cancer Symptom Working Group, Natalie A. West, Serageldin Kamel, Zaphanlene Kaffey, Cem Dede, Samuel L. Mulder, Dina M. El-Habashy, Roger Neuberger, Mohamed A Naser, Steven J. Frank, Shitong Mao, Holly McMillan, Brad Smith, David Rosenthal, Stephen Y. Lai, Katherine A. Hutcheson, Amy C Moreno, Clifton David Fuller
Background Radiation-associated lymphedema and fibrosis (LEF) is a significant toxicity following radiation therapy (RT) for head and neck cancer (HNC) patients. Recently, the CT Lymphedema and Fibrosis Assessment Tool (CT-LEFAT) was developed to standardize LEF diagnosis through fat stranding visualized on CT. This study aims to evaluate the inter-observer reliability and diagnostic accuracy of the CT-LEFAT criteria. Materials and Methods This study retrospectively evaluated 26 HNC patients treated with RT that received a minimum of two contrast-enhanced CT scans. Qualitative review was conducted by five physician raters to assess the fat stranding observed on CT according to the CT-LEFAT criteria. Fleiss' kappa analysis was used to assess the inter- and intra-rater reliability, and Receiver Operating Characteristic (ROC) Area Under the Curve (AUC) analysis was used to evaluate diagnostic accuracy. Results The inter-rater reliability across the six CT-LEFAT regions generally indicated a slight to fair agreement across all raters (0.04 ≤ kappa ≤ 0.36). Intra-observer agreement was generally fair to moderate (overall kappa=0.44). The ROC AUC analysis varied based on aggregation method used (0.60 ≤ average AUC ≤ 0.70). Conclusion This specific use-case evaluating CT-LEFAT criteria displays limited performance. This suggests that additional materials, such as further training, refinement of imaging methods, or other processes may be required before achieving clinically-ready diagnostic performance of LEF diagnosis.
{"title":"Evaluating Observer Reliability and Diagnostic Accuracy of CT-LEFAT Criteria for Post-Treatment Head and Neck Lymphedema: A Prospective Blinded Comparative Analysis of Oncologist Human Inter-Rater Performance","authors":"MD Anderson Head and Neck Cancer Symptom Working Group, Natalie A. West, Serageldin Kamel, Zaphanlene Kaffey, Cem Dede, Samuel L. Mulder, Dina M. El-Habashy, Roger Neuberger, Mohamed A Naser, Steven J. Frank, Shitong Mao, Holly McMillan, Brad Smith, David Rosenthal, Stephen Y. Lai, Katherine A. Hutcheson, Amy C Moreno, Clifton David Fuller","doi":"10.1101/2024.09.17.24313809","DOIUrl":"https://doi.org/10.1101/2024.09.17.24313809","url":null,"abstract":"Background\u0000Radiation-associated lymphedema and fibrosis (LEF) is a significant toxicity following radiation therapy (RT) for head and neck cancer (HNC) patients. Recently, the CT Lymphedema and Fibrosis Assessment Tool (CT-LEFAT) was developed to standardize LEF diagnosis through fat stranding visualized on CT. This study aims to evaluate the inter-observer reliability and diagnostic accuracy of the CT-LEFAT criteria.\u0000Materials and Methods\u0000This study retrospectively evaluated 26 HNC patients treated with RT that received a minimum of two contrast-enhanced CT scans. Qualitative review was conducted by five physician raters to assess the fat stranding observed on CT according to the CT-LEFAT criteria. Fleiss' kappa analysis was used to assess the inter- and intra-rater reliability, and Receiver Operating Characteristic (ROC) Area Under the Curve (AUC) analysis was used to evaluate diagnostic accuracy. Results\u0000The inter-rater reliability across the six CT-LEFAT regions generally indicated a slight to fair agreement across all raters (0.04 ≤ kappa ≤ 0.36). Intra-observer agreement was generally fair to moderate (overall kappa=0.44). The ROC AUC analysis varied based on aggregation method used (0.60 ≤ average AUC ≤ 0.70).\u0000Conclusion\u0000This specific use-case evaluating CT-LEFAT criteria displays limited performance. This suggests that additional materials, such as further training, refinement of imaging methods, or other processes may be required before achieving clinically-ready diagnostic performance of LEF diagnosis.","PeriodicalId":501437,"journal":{"name":"medRxiv - Oncology","volume":"95 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142250428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-17DOI: 10.1101/2024.09.16.24313758
Roman M. Shapiro, Michal Sheffer, Matthew A. Booker, Michael Y. Tolstorukov, Grace C. Birch, Moshe Sade-Feldman, Jacy Fang, Shuqiang Li, Wesley Lu, Michela Ansuinelli, Remy Dulery, Mubin Tarannum, Joanna Baginska, Nishant Dwivedi, Ashish Kothari, Livius Penter, Yasmin Z. Abdulhamid, Isabel E. Kaplan, Dinh Khanhlinh, Ravindra Uppaluri, Robert A. Redd, Sarah Nikiforow, John Koreth, Jerome Ritz, Catherine J. Wu, Robert J. Soiffer, glenn hanna, Rizwan Romee
Cytokine induced memory-like natural killer (CIML NK) cells combined with an IL-15 super-agonist (N-803) are a novel modality to treat relapsed/refractory head and neck cancer. We report data from a phase I trial of haploidentical CIML NK cells combined with N-803 with or without ipilimumab (IPI) in relapsed/refractory head and neck cancer patients after a median of 6 prior lines of therapy. The primary endpoint was safety, which was established, with dose-limiting toxicity in 1/10 patients. A promising though transient disease control rate of 70% correlated with donor NK cell expansion, the latter occurring irrespective of IPI. High-resolution immunophenotypic and transcriptional profiling characterized the NK cells and their interacting partners in vivo. IPI was associated with contraction of Treg:Tcon, rapid recovery of recipient CD8+ T cells, and accelerated rejection of donor NK cells. These results inform evaluation of CIML NK therapy for advanced malignancies, with considerations for combination with IPI.
细胞因子诱导的记忆样自然杀伤（CIML NK）细胞与IL-15超级拮抗剂（N-803）相结合是治疗复发/难治性头颈癌的一种新方法。我们报告了单倍体CIML NK细胞联合N-803与或不联合伊匹单抗（IPI）治疗复发/难治性头颈癌患者的I期试验数据。研究的主要终点是安全性，1/10的患者出现了剂量限制性毒性。70%的短暂疾病控制率与供体NK细胞扩增有关，后者与IPI无关。高分辨率免疫表型和转录谱分析确定了体内 NK 细胞及其相互作用伙伴的特征。IPI与Treg:Tcon的收缩、受体CD8+ T细胞的快速恢复以及供体NK细胞的加速排斥有关。这些结果为评估晚期恶性肿瘤的CIML NK疗法提供了参考，并考虑了与IPI的结合。
{"title":"First-in-human evaluation of memory-like NK cells with an IL-15 super-agonist and CTLA-4 blockade in advanced head and neck cancer","authors":"Roman M. Shapiro, Michal Sheffer, Matthew A. Booker, Michael Y. Tolstorukov, Grace C. Birch, Moshe Sade-Feldman, Jacy Fang, Shuqiang Li, Wesley Lu, Michela Ansuinelli, Remy Dulery, Mubin Tarannum, Joanna Baginska, Nishant Dwivedi, Ashish Kothari, Livius Penter, Yasmin Z. Abdulhamid, Isabel E. Kaplan, Dinh Khanhlinh, Ravindra Uppaluri, Robert A. Redd, Sarah Nikiforow, John Koreth, Jerome Ritz, Catherine J. Wu, Robert J. Soiffer, glenn hanna, Rizwan Romee","doi":"10.1101/2024.09.16.24313758","DOIUrl":"https://doi.org/10.1101/2024.09.16.24313758","url":null,"abstract":"Cytokine induced memory-like natural killer (CIML NK) cells combined with an IL-15 super-agonist (N-803) are a novel modality to treat relapsed/refractory head and neck cancer. We report data from a phase I trial of haploidentical CIML NK cells combined with N-803 with or without ipilimumab (IPI) in relapsed/refractory head and neck cancer patients after a median of 6 prior lines of therapy. The primary endpoint was safety, which was established, with dose-limiting toxicity in 1/10 patients. A promising though transient disease control rate of 70% correlated with donor NK cell expansion, the latter occurring irrespective of IPI. High-resolution immunophenotypic and transcriptional profiling characterized the NK cells and their interacting partners in vivo. IPI was associated with contraction of Treg:Tcon, rapid recovery of recipient CD8+ T cells, and accelerated rejection of donor NK cells. These results inform evaluation of CIML NK therapy for advanced malignancies, with considerations for combination with IPI.","PeriodicalId":501437,"journal":{"name":"medRxiv - Oncology","volume":"29 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142250430","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-17DOI: 10.1101/2024.09.16.24313563
Anastasia Nikitina, Daria Kiriy, Andrey Tyshevich, Dmitry Tychinin, Zoia Antysheva, Anastasia Sobol, Vladimir Kushnarev, Nara Shin, Jessica H. Brown, James Lewis, Krystle A. Lang Kuhs, Robert Ferris, Lori Wirth, Nikita Kotlov, Daniel L. Faden
Human papillomavirus (HPV)-associated head and neck squamous cell carcinoma (HPV-positive HNSCC) has distinct biological characteristics from HPV-negative HNSCC. Using an AI-based analytical platform on meta cohorts, we profiled expression patterns of viral transcripts and HPV viral genome integration, and classified the tumor microenvironment (TME). Unsupervised clustering analysis revealed 5 distinct and novel TME subtypes across patients (immune-enriched, highly immune and B-cell enriched, fibrotic, immune-desert, and immune-enriched luminal). These TME subtypes were highly correlated with patient prognosis. In order to understand specific factors associated with prognosis, we used unsupervised clustering of a HPV-positive HNSCC cohort from The Cancer Genome Atlas (TCGA) (n = 53) based on HPV transcript expression, and identified 4 HPV-related subtypes (E2/E5, E6/E7, E1/E4 and L1/L2). Utilizing both viral transcript and TME subtypes, we found that the E2/E5 HPV subtype was associated with an immune-enriched TME and had a higher overall survival compared to other subtypes. The E2/E5 subtype was also enriched for samples without HPV-genome integration, suggesting that episomal HPV status and E2/E5 expression pattern may be associated with an inflamed microenvironment and improved prognosis. In contrast, E6/E7 subtype samples were associated with the fibrotic and immune-desert TME subtypes, with lower values of T-cell and B-cell gene expression signatures and lower overall survival. Both E1/E4 and L1/L2 subtypes were associated with the immune-enriched luminal subtype. Our results suggest that HPV-transcript expression patterns may drive modulation of the TME and thereby impact prognosis.
{"title":"Viral transcript and tumor immune microenvironment-based transcriptomic profiling of HPV-associated head and neck squamous cell carcinoma identifies subtypes associated with prognosis","authors":"Anastasia Nikitina, Daria Kiriy, Andrey Tyshevich, Dmitry Tychinin, Zoia Antysheva, Anastasia Sobol, Vladimir Kushnarev, Nara Shin, Jessica H. Brown, James Lewis, Krystle A. Lang Kuhs, Robert Ferris, Lori Wirth, Nikita Kotlov, Daniel L. Faden","doi":"10.1101/2024.09.16.24313563","DOIUrl":"https://doi.org/10.1101/2024.09.16.24313563","url":null,"abstract":"Human papillomavirus (HPV)-associated head and neck squamous cell carcinoma (HPV-positive HNSCC) has distinct biological characteristics from HPV-negative HNSCC. Using an AI-based analytical platform on meta cohorts, we profiled expression patterns of viral transcripts and HPV viral genome integration, and classified the tumor microenvironment (TME). Unsupervised clustering analysis revealed 5 distinct and novel TME subtypes across patients (immune-enriched, highly immune and B-cell enriched, fibrotic, immune-desert, and immune-enriched luminal). These TME subtypes were highly correlated with patient prognosis. In order to understand specific factors associated with prognosis, we used unsupervised clustering of a HPV-positive HNSCC cohort from The Cancer Genome Atlas (TCGA) (n = 53) based on HPV transcript expression, and identified 4 HPV-related subtypes (E2/E5, E6/E7, E1/E4 and L1/L2). Utilizing both viral transcript and TME subtypes, we found that the E2/E5 HPV subtype was associated with an immune-enriched TME and had a higher overall survival compared to other subtypes. The E2/E5 subtype was also enriched for samples without HPV-genome integration, suggesting that episomal HPV status and E2/E5 expression pattern may be associated with an inflamed microenvironment and improved prognosis. In contrast, E6/E7 subtype samples were associated with the fibrotic and immune-desert TME subtypes, with lower values of T-cell and B-cell gene expression signatures and lower overall survival. Both E1/E4 and L1/L2 subtypes were associated with the immune-enriched luminal subtype. Our results suggest that HPV-transcript expression patterns may drive modulation of the TME and thereby impact prognosis.","PeriodicalId":501437,"journal":{"name":"medRxiv - Oncology","volume":"15 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142250432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Background: Ovarian cancer is a serious risk to human health and causes a heavy economic burden. Ultrasound is widely used in the diagnosis of ovarian tumors. However, false-positive ultrasound results can lead to false diagnosis, and patients will have to bear unnecessary mental pain, expensive surgery and examination costs, surgical trauma, organ removal, loss of function, and even serious complications in the perioperative period, and other adverse consequences. False-negative ultrasound results lead to delayed treatment, and patients will have to bear the consequences of poor prognosis, high treatment costs, poor quality of life, and poor survival. There is an urgent need to find convenient, cost-effective and non-invasive diagnostic methods to reduce the false-negative and false-positive rates of ovarian ultrasound. The purpose of this study was to evaluate the diagnostic value of YiDiXie™-SS, YiDiXie™-HS and YiDiXie™-D in Ovarian cancer. Patients and methods: The study finally included 79 study subjects (malignant group, n=12; benign group, n=67). Remaining serum samples from the subjects were collected and tested by applying YiDiXie™ all-cancer detection kit to evaluate the sensitivity and specificity of YiDiXie™-SS, YiDiXie™-HS and YiDiXie™-D, respectively. Results: YiDiXie™-SS had a sensitivity of 100% (95% CI: 75.8% - 100%) and a specificity of 61.2% (95% CI: 49.2% - 72.0%). YiDiXie™-HS had a sensitivity of 91.7% (95% CI: 64.6% - 99.6%) and a specificity of 86.6% (95% CI: 76.4% - 92.8%). The sensitivity of YiDiXie™-D was 33.3% (95% CI: 13.8% - 60.0%) and its specificity was 97.0% (95% CI: 89.8% - 99.5%). The sensitivity of YiDiXie™-SS in ultrasound-positive patients was 100% (95% CI: 67.6% - 100%) and its specificity was 61.9% (95% CI: 40.9% - 79.2%). This represents a 61.9% (95% CI: 40.9% - 79.2%) reduction in the rate of false-positive ovarian ultrasound with the application of YiDiXie™-SS with essentially no increase in malignant tumor under-diagnosis. The sensitivity of YiDiXie™-HS in ultrasound-negative patients was 75.0% (95% CI: 30.1% - 98.7%) and its specificity was 84.8% (95% CI: 71.8% - 92.4%). This means that the application of YiDiXie™-HS reduces the false negative rate of ultrasound by 75.0% (95% CI: 30.1% - 98.7%). YiDiXie™-D had a sensitivity of 25.0% (95% CI: 4.4% - 59.1%) in ultrasound-positive patients and its specificity was 95.2% (95% CI: 77.3% - 99.8%). This represents a 95.2% (95% CI: 77.3% - 99.8%) reduction in the rate of ultrasound false positives with YiDiXie™-SS. Conclusion: YiDiXie™-SS markedly reduced the false-positive rate of ovarian ultrasound with essentially no increase in delayed treatment of malignant tumors. YiDiXie™-HS substantially reduced the false-negative rate of ovarian ultrasound. YiDiXie™-D substantially reduced the false-positive rate of ovarian ultrasound. The YiDiXie™ test has an excellent diagnostic value in ovarian cancer, and promises to solve the problems of "high false-positive rate o
{"title":"Evaluation of the diagnostic value of YiDiXie™-SS, YiDiXie™-HS, and YiDiXie™-D in Ovarian cancer","authors":"Pengwu Zhang, Chen Sun, Zhenjian Ge, Wenkang Chen, Yingqi Li, Shengjie Lin, Wuping Wang, Siwei Chen, Yutong Wu, Huimei Zhou, Xutai Li, Wei Li, Yongqing Lai","doi":"10.1101/2024.09.15.24313714","DOIUrl":"https://doi.org/10.1101/2024.09.15.24313714","url":null,"abstract":"Background: Ovarian cancer is a serious risk to human health and causes a heavy economic burden. Ultrasound is widely used in the diagnosis of ovarian tumors. However, false-positive ultrasound results can lead to false diagnosis, and patients will have to bear unnecessary mental pain, expensive surgery and examination costs, surgical trauma, organ removal, loss of function, and even serious complications in the perioperative period, and other adverse consequences. False-negative ultrasound results lead to delayed treatment, and patients will have to bear the consequences of poor prognosis, high treatment costs, poor quality of life, and poor survival. There is an urgent need to find convenient, cost-effective and non-invasive diagnostic methods to reduce the false-negative and false-positive rates of ovarian ultrasound. The purpose of this study was to evaluate the diagnostic value of YiDiXie™-SS, YiDiXie™-HS and YiDiXie™-D in Ovarian cancer.\u0000Patients and methods: The study finally included 79 study subjects (malignant group, n=12; benign group, n=67). Remaining serum samples from the subjects were collected and tested by applying YiDiXie™ all-cancer detection kit to evaluate the sensitivity and specificity of YiDiXie™-SS, YiDiXie™-HS and YiDiXie™-D, respectively.\u0000Results: YiDiXie™-SS had a sensitivity of 100% (95% CI: 75.8% - 100%) and a specificity of 61.2% (95% CI: 49.2% - 72.0%). YiDiXie™-HS had a sensitivity of 91.7% (95% CI: 64.6% - 99.6%) and a specificity of 86.6% (95% CI: 76.4% - 92.8%). The sensitivity of YiDiXie™-D was 33.3% (95% CI: 13.8% - 60.0%) and its specificity was 97.0% (95% CI: 89.8% - 99.5%). The sensitivity of YiDiXie™-SS in ultrasound-positive patients was 100% (95% CI: 67.6% - 100%) and its specificity was 61.9% (95% CI: 40.9% - 79.2%). This represents a 61.9% (95% CI: 40.9% - 79.2%) reduction in the rate of false-positive ovarian ultrasound with the application of YiDiXie™-SS with essentially no increase in malignant tumor under-diagnosis. The sensitivity of YiDiXie™-HS in ultrasound-negative patients was 75.0% (95% CI: 30.1% - 98.7%) and its specificity was 84.8% (95% CI: 71.8% - 92.4%). This means that the application of YiDiXie™-HS reduces the false negative rate of ultrasound by 75.0% (95% CI: 30.1% - 98.7%). YiDiXie™-D had a sensitivity of 25.0% (95% CI: 4.4% - 59.1%) in ultrasound-positive patients and its specificity was 95.2% (95% CI: 77.3% - 99.8%). This represents a 95.2% (95% CI: 77.3% - 99.8%) reduction in the rate of ultrasound false positives with YiDiXie™-SS. Conclusion: YiDiXie™-SS markedly reduced the false-positive rate of ovarian ultrasound with essentially no increase in delayed treatment of malignant tumors. YiDiXie™-HS substantially reduced the false-negative rate of ovarian ultrasound. YiDiXie™-D substantially reduced the false-positive rate of ovarian ultrasound. The YiDiXie™ test has an excellent diagnostic value in ovarian cancer, and promises to solve the problems of \"high false-positive rate o","PeriodicalId":501437,"journal":{"name":"medRxiv - Oncology","volume":"19 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142250435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Background: Esophageal cancer is a serious threat to human health and causes a heavy economic burden. upper gastrointestinal imaging(UGI imaging), enhanced CT, Fecal occult blood Tumor markers such as test(FOBT) and CEA, CA125 and CA19-9 are widely used in the screening or preliminary diagnosis of esophageal cancer. However, false positive results such as UGI imaging will bring unnecessary mental pain, expensive examination costs, examination injuries and other adverse consequences. However, false negative results such as UGI imaging lead to delayed treatment, and patients will have to bear the adverse consequences of poor prognosis, high treatment costs, poor quality of life, and short survival time. It is urgent to find a convenient, economical and non-invasive diagnostic method to reduce the false negative rate and false positive rate of UGI imaging. The objective of this study was to evaluate the diagnostic value of YiDiXie™-SS and YiDiXie™-HS in esophageal cancer. Patients and methods: This study included 164 subjects (malignant group, n=105; Benign group, n=59 cases). The remaining serum samples of the subjects were collected and the sensitivity and specificity of the YiDiXie™-SS and YiDiXie™-HS were evaluated using the YiDiXie™all-cancer detection kit. Results: The sensitivity of YiDiXie™-SS was 99.0% (95% CI: 94.8% - 100%) and its specificity was 62.7% (95% CI: 50.0% - 73.9%). The sensitivity of YiDiXie™-HS was 92.3% (95% CI: 85.7% - 96.1%) and its specificity was 86.4% (95% CI: 75.5% - 93.0%). The sensitivity of YiDiXie™-SS in UGI imaging, enhanced CT, FOBT, CEA, CA125 and CA19-9 positive patients was 96.6% (95% CI: 82.8-99.8%) and 98.7% (95% CI: 93.1% - 99.9%), 100% (95% CI: 17.8% 100%), 100% (95% CI: 81.6% 100%), 100% (95% CI: 61.0% 100%), 100% (95%CI: 56.6%-100%); The specific degrees were 60.0% (95% CI: 23.1% 92.9%), 75.0% (95% CI: 30.1% 98.7%), 100% (95% CI: 5.1% 100%), 100% (95% CI: 43.9% - 100%), 100% (95% CI: 5.1% 100%), 50.0% (95% CI: 2.6% 97.4%). This means that the application of YiDiXie™-SS, without basically increasing the missed diagnosis of malignant tumors, reduced the false positive range of UGI imaging, enhanced CT, FOBT, CEA, CA125 and CA19-9 by 60.0% (95% CI: 23.1% - 92.9%), 75.0% (95% CI: 30.1% 98.7%), 100% (95% CI: 5.1% 100%), 100% (95% CI: 43.9% 100%), 100% (95% CI: 5.1% - 100%), 50.0% (95% CI: 2.6% 97.4%). The sensitivity of YiDiXie™-HS in UGI imaging, enhanced CT, FOBT, CEA, CA125 and CA19-9 negative patients was 88.9% (95% CI: 56.5% - 99.4%), 92.6% (95% CI: 84.8% - 96.6%), 96.9% (95% CI: 84.3% - 99.8%), 92.6% (95% CI: 84.8% - 96.6%), 92.0% (95% CI: 84.5% - 96.1%), 91.3% (95% CI: 83.8% - 95.5%), respectively; The specific degrees were 60.0% (95% CI: 23.1% 92.9%), 87.3% (95% CI: 76.0% 93.7%), 80.0% (95% CI: 37.6% 99.0%), 89.1% (95% CI: 78.2% - 94.9%), 79.3% (95% CI: 61.6% 90.2%), 87.0% (95% CI: 75.6% 93.6%). This means that YiDiXie™-HS reduced false negatives for UGI imaging, enhanced CT, FOBT, CEA, CA125 and CA19
{"title":"Evaluation of the diagnostic value of YiDiXie™-SS and YiDiXie™-HS in esophageal cancer","authors":"Xutai Li, Zhenjian Ge, Peng Liao, Chen Sun, Wenkang Chen, Yingqi Li, Shengjie Lin, Pengwu Zhang, Wuping Wang, Siwei Chen, Yutong Wu, Huimei Zhou, Wei Li, Jing Du, Fangting Zhang, Yongqing Lai","doi":"10.1101/2024.09.15.24313696","DOIUrl":"https://doi.org/10.1101/2024.09.15.24313696","url":null,"abstract":"Background: Esophageal cancer is a serious threat to human health and causes a heavy economic burden. upper gastrointestinal imaging(UGI imaging), enhanced CT, Fecal occult blood Tumor markers such as test(FOBT) and CEA, CA125 and CA19-9 are widely used in the screening or preliminary diagnosis of esophageal cancer. However, false positive results such as UGI imaging will bring unnecessary mental pain, expensive examination costs, examination injuries and other adverse consequences. However, false negative results such as UGI imaging lead to delayed treatment, and patients will have to bear the adverse consequences of poor prognosis, high treatment costs, poor quality of life, and short survival time. It is urgent to find a convenient, economical and non-invasive diagnostic method to reduce the false negative rate and false positive rate of UGI imaging. The objective of this study was to evaluate the diagnostic value of YiDiXie™-SS and YiDiXie™-HS in esophageal cancer.\u0000Patients and methods: This study included 164 subjects (malignant group, n=105; Benign group, n=59 cases). The remaining serum samples of the subjects were collected and the sensitivity and specificity of the YiDiXie™-SS and YiDiXie™-HS were evaluated using the YiDiXie™all-cancer detection kit.\u0000Results: The sensitivity of YiDiXie™-SS was 99.0% (95% CI: 94.8% - 100%) and its specificity was 62.7% (95% CI: 50.0% - 73.9%). The sensitivity of YiDiXie™-HS was 92.3% (95% CI: 85.7% - 96.1%) and its specificity was 86.4% (95% CI: 75.5% - 93.0%). The sensitivity of YiDiXie™-SS in UGI imaging, enhanced CT, FOBT, CEA, CA125 and CA19-9 positive patients was 96.6% (95% CI: 82.8-99.8%) and 98.7% (95% CI: 93.1% - 99.9%), 100% (95% CI: 17.8% 100%), 100% (95% CI: 81.6% 100%), 100% (95% CI: 61.0% 100%), 100% (95%CI: 56.6%-100%); The specific degrees were 60.0% (95% CI: 23.1% 92.9%), 75.0% (95% CI: 30.1% 98.7%), 100% (95% CI: 5.1% 100%), 100% (95% CI: 43.9% - 100%), 100% (95% CI: 5.1% 100%), 50.0% (95% CI: 2.6% 97.4%). This means that the application of YiDiXie™-SS, without basically increasing the missed diagnosis of malignant tumors, reduced the false positive range of UGI imaging, enhanced CT, FOBT, CEA, CA125 and CA19-9 by 60.0% (95% CI: 23.1% - 92.9%), 75.0% (95% CI: 30.1% 98.7%), 100% (95% CI: 5.1% 100%), 100% (95% CI: 43.9% 100%), 100% (95% CI: 5.1% - 100%), 50.0% (95% CI: 2.6% 97.4%).\tThe sensitivity of YiDiXie™-HS in UGI imaging, enhanced CT, FOBT, CEA, CA125 and CA19-9 negative patients was 88.9% (95% CI: 56.5% - 99.4%), 92.6% (95% CI: 84.8% - 96.6%), 96.9% (95% CI: 84.3% - 99.8%), 92.6% (95% CI: 84.8% - 96.6%), 92.0% (95% CI: 84.5% - 96.1%), 91.3% (95% CI: 83.8% - 95.5%), respectively; The specific degrees were 60.0% (95% CI: 23.1% 92.9%), 87.3% (95% CI: 76.0% 93.7%), 80.0% (95% CI: 37.6% 99.0%), 89.1% (95% CI: 78.2% - 94.9%), 79.3% (95% CI: 61.6% 90.2%), 87.0% (95% CI: 75.6% 93.6%). This means that YiDiXie™-HS reduced false negatives for UGI imaging, enhanced CT, FOBT, CEA, CA125 and CA19","PeriodicalId":501437,"journal":{"name":"medRxiv - Oncology","volume":"65 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142250434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-16DOI: 10.1101/2024.09.16.24313343
Anne Van Arsdale, Olga Meshcheryakova, Sonia Gallego, Elaine Maggi, Bryan Harmon, Koenraad Van Doorslaer, Dennis YS Kuo, Mark H Einstein, Brian Haas, Cristina Montagna, Jack Lenz
Almost all cervical cancers are caused by human papillomaviruses (HPVs). In most cases, HPV DNA is integrated into the human genome. We found that tumor-specific, HPV-human DNA junctions are detectable in serum cell-free DNA of cervical cancer patients at initial treatment. Retrospective analysis revealed these junctions were more frequently detectable in women in whom the cancer later recurred. We also found that cervical cancers caused by HPV types outside of phylogenetic clade α9 had a higher recurrence frequency than those caused by α9 types in both our study and The Cancer Genome Atlas cervical cancer database, despite the higher prevalence of non-α9 types including HPV16 in cervical cancer. Thus, HPV-human DNA junction detection in serum cell-free DNA and HPV type determination in tumor tissue may help predict recurrence risk. Screening serum cell-free DNA for junctions may also offer an unambiguous, non-invasive means to monitor absence of recurrence following treatment.
几乎所有宫颈癌都是由人类乳头瘤病毒（HPV）引起的。在大多数情况下，HPV DNA 会整合到人类基因组中。我们发现，在宫颈癌患者接受初次治疗时，其血清无细胞 DNA 中可检测到肿瘤特异性 HPV 与人类 DNA 连接。回顾性分析表明，在癌症后来复发的妇女中更经常检测到这些连接。我们还发现，在我们的研究和癌症基因组图谱（The Cancer Genome Atlas）宫颈癌数据库中，尽管包括 HPV16 在内的非 α9 型 HPV 在宫颈癌中的发病率较高，但由系统发育支系 α9 以外的 HPV 所导致的宫颈癌的复发率高于由 α9 型 HPV 所导致的宫颈癌。因此，检测血清无细胞DNA中的HPV-人类DNA接合点和确定肿瘤组织中的HPV类型可能有助于预测复发风险。筛查血清无细胞 DNA 中的接合点还可以提供一种明确、无创的方法来监测治疗后是否复发。
{"title":"Serum, Cell-Free HPV-Human DNA Junction Detection and HPV Typing for Predicting and Monitoring Cervical Cancer Recurrence","authors":"Anne Van Arsdale, Olga Meshcheryakova, Sonia Gallego, Elaine Maggi, Bryan Harmon, Koenraad Van Doorslaer, Dennis YS Kuo, Mark H Einstein, Brian Haas, Cristina Montagna, Jack Lenz","doi":"10.1101/2024.09.16.24313343","DOIUrl":"https://doi.org/10.1101/2024.09.16.24313343","url":null,"abstract":"Almost all cervical cancers are caused by human papillomaviruses (HPVs). In most cases, HPV DNA is integrated into the human genome. We found that tumor-specific, HPV-human DNA junctions are detectable in serum cell-free DNA of cervical cancer patients at initial treatment. Retrospective analysis revealed these junctions were more frequently detectable in women in whom the cancer later recurred. We also found that cervical cancers caused by HPV types outside of phylogenetic clade α9 had a higher recurrence frequency than those caused by α9 types in both our study and The Cancer Genome Atlas cervical cancer database, despite the higher prevalence of non-α9 types including HPV16 in cervical cancer. Thus, HPV-human DNA junction detection in serum cell-free DNA and HPV type determination in tumor tissue may help predict recurrence risk. Screening serum cell-free DNA for junctions may also offer an unambiguous, non-invasive means to monitor absence of recurrence following treatment.","PeriodicalId":501437,"journal":{"name":"medRxiv - Oncology","volume":"16 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142250433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-16DOI: 10.1101/2024.09.14.24313680
Jack R Andrews, Yohan Kim, Edlira Horjeti, Ali Arafa, Heather Gunn, Aurelie De Bruycker, Ryan Phillips, Daniel Song, Daniel S Childs, Oliver A Sartor, Jacob J Orme, Aadel A Chaudhuri, Phuoc Tran, Ana Kiess, Philip Sutera, Carole Mercier, Piet Ost, Sean S Park, Fabrice Lucien
Purpose: Two randomized clinical trials (STOMP and ORIOLE) demonstrated that stereotactic ablative radiotherapy (SABR) can prolong ADT-free survival or progression-free survival (PFS) in patients with metachronous oligometastatic prostate cancer (omCSPC) patients. While most omCSPC patients have a more modest delay in progression, a small subset achieves a durable response following SABR. We investigated the prognostic and predictive value of circulating PSMA-positive extracellular vesicles (PSMA+EV) and prostate specific antigen (PSA) in a biomarker correlative study using blood samples from three independent patient cohorts. Methods: Plasma samples from 46 patients on the ORIOLE trial and 127 patietns on the STOMP trial protocol with omCSPC patients treated with SABR. Pre-SABR PSMA+EV levels (EVs/ml) were measured by nanoscale flow cytometry. Kaplan-Meier curves and logistic regression models were used to determine the association of PSMA+EV and PSA levels with clinical outcomes. Results: In the pooled cohorts, median bPFS were 26.1 and 15.0 months (p=0.005) and median rPFS were 36.0 and 25.0 months (p=0.003) for PSMA+EV low and high groups, respectively. The combination of pre-SABR low levels of both PSMA+EV and PSA was associated with lower risk of radiographic progression (HR=0.34, 95% CI: 0.18-0.58, p=0.0002). In the ORIOLE cohort, which included both a SABR arm and an observation arm, low PSMA+EV was predictive of benefit from SABR (p=0.012). Conclusions: PSMA+EV is a novel prognostic and predictive biomarker of radiographically occult tumor burden in omCSPC. PSMA+EV may inform clinical decisions regarding which patients achieve a durable benefit from consolidative SABR alone.
{"title":"PSMA+ Extracellular Vesicles are a Biomarker for SABR in Oligorecurrent Prostate Cancer Analysis from the STOMP-like and ORIOLE trial cohorts","authors":"Jack R Andrews, Yohan Kim, Edlira Horjeti, Ali Arafa, Heather Gunn, Aurelie De Bruycker, Ryan Phillips, Daniel Song, Daniel S Childs, Oliver A Sartor, Jacob J Orme, Aadel A Chaudhuri, Phuoc Tran, Ana Kiess, Philip Sutera, Carole Mercier, Piet Ost, Sean S Park, Fabrice Lucien","doi":"10.1101/2024.09.14.24313680","DOIUrl":"https://doi.org/10.1101/2024.09.14.24313680","url":null,"abstract":"Purpose: Two randomized clinical trials (STOMP and ORIOLE) demonstrated that stereotactic ablative radiotherapy (SABR) can prolong ADT-free survival or progression-free survival (PFS) in patients with metachronous oligometastatic prostate cancer (omCSPC) patients. While most omCSPC patients have a more modest delay in progression, a small subset achieves a durable response following SABR. We investigated the prognostic and predictive value of circulating PSMA-positive extracellular vesicles (PSMA+EV) and prostate specific antigen (PSA) in a biomarker correlative study using blood samples from three independent patient cohorts. Methods: Plasma samples from 46 patients on the ORIOLE trial and 127 patietns on the STOMP trial protocol with omCSPC patients treated with SABR. Pre-SABR PSMA+EV levels (EVs/ml) were measured by nanoscale flow cytometry. Kaplan-Meier curves and logistic regression models were used to determine the association of PSMA+EV and PSA levels with clinical outcomes. Results: In the pooled cohorts, median bPFS were 26.1 and 15.0 months (p=0.005) and median rPFS were 36.0 and 25.0 months (p=0.003) for PSMA+EV low and high groups, respectively. The combination of pre-SABR low levels of both PSMA+EV and PSA was associated with lower risk of radiographic progression (HR=0.34, 95% CI: 0.18-0.58, p=0.0002). In the ORIOLE cohort, which included both a SABR arm and an observation arm, low PSMA+EV was predictive of benefit from SABR (p=0.012). Conclusions: PSMA+EV is a novel prognostic and predictive biomarker of radiographically occult tumor burden in omCSPC. PSMA+EV may inform clinical decisions regarding which patients achieve a durable benefit from consolidative SABR alone.","PeriodicalId":501437,"journal":{"name":"medRxiv - Oncology","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142250436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-14DOI: 10.1101/2024.09.13.24313658
Kendall Kiser, Ashish Vaidyanathan, Matthew Schuelke, Joshua Denzer, Trudy Landreth, Christopher Abraham, Adam Wilcox
Background Radiation and medical oncologists evaluate patients' risk of imminent mortality with scales like Karnofsky Performance Status (KPS) and predicate treatment decisions on these evaluations. However, we hypothesized that statistical models derived from structured electronic health record (EHR) data could predict patient deaths within 30 days of radiotherapy consultation better than models developed only with patient age and physician-reported KPS. Methods Clinical data from patients who consulted in a radiotherapy department from June 2018 - February 2024 were abstracted from EHR databases, including patient demographics, laboratory results, medications, comorbidities, KPS, cancer stages, oncologic treatment histories, oncologist notes, radiologist reports, and pathologist narratives. A subset of structured features known or believed to be associated with mortality were curated and used to train and test logistic regression, random forest, and gradient-boosted decision classifiers. Results Of 38,262 patients, 951 (2.5%) died within 30 days of radiotherapy consultation. From 34.5 gigabytes of tabular data, 2,977 clinical features were chosen or derived by a radiation oncologist, then reduced to 1,000 features using ANOVA F values. Using an event probability classification threshold of 0.2, optimized logistic regression, random forest, and gradient-boosted decision classifiers tested with high accuracy (0.97, 0.98, and 0.98, respectively) and F1 scores (0.50, 0.54, and 0.52). The areas under receiver operating and precision-recall curves for the random forest model were respectively 0.94 and 0.55, which outperformed a model trained only with patient age and KPS (0.61 and 0.06). Models prominently weighed features that were rationally associated with mortality. Conclusion Statistical models developed from a physician-curated feature space of structured EHR data predicted patient deaths within 30 days of radiotherapy consultation better than a model developed only with a patient's age and physician-assessed KPS. With clinically explicable feature weights, these models could influence treatment decisions such as the length of palliative radiotherapy courses.
{"title":"Predicting cancer patient mortality within 30 days of radiotherapy consultation to inform palliative radiotherapy fractionation decisions","authors":"Kendall Kiser, Ashish Vaidyanathan, Matthew Schuelke, Joshua Denzer, Trudy Landreth, Christopher Abraham, Adam Wilcox","doi":"10.1101/2024.09.13.24313658","DOIUrl":"https://doi.org/10.1101/2024.09.13.24313658","url":null,"abstract":"Background\u0000Radiation and medical oncologists evaluate patients' risk of imminent mortality with scales like Karnofsky Performance Status (KPS) and predicate treatment decisions on these evaluations. However, we hypothesized that statistical models derived from structured electronic health record (EHR) data could predict patient deaths within 30 days of radiotherapy consultation better than models developed only with patient age and physician-reported KPS. Methods\u0000Clinical data from patients who consulted in a radiotherapy department from June 2018 - February 2024 were abstracted from EHR databases, including patient demographics, laboratory results, medications, comorbidities, KPS, cancer stages, oncologic treatment histories, oncologist notes, radiologist reports, and pathologist narratives. A subset of structured features known or believed to be associated with mortality were curated and used to train and test logistic regression, random forest, and gradient-boosted decision classifiers.\u0000Results\u0000Of 38,262 patients, 951 (2.5%) died within 30 days of radiotherapy consultation. From 34.5 gigabytes of tabular data, 2,977 clinical features were chosen or derived by a radiation oncologist, then reduced to 1,000 features using ANOVA F values. Using an event probability classification threshold of 0.2, optimized logistic regression, random forest, and gradient-boosted decision classifiers tested with high accuracy (0.97, 0.98, and 0.98, respectively) and F1 scores (0.50, 0.54, and 0.52). The areas under receiver operating and precision-recall curves for the random forest model were respectively 0.94 and 0.55, which outperformed a model trained only with patient age and KPS (0.61 and 0.06). Models prominently weighed features that were rationally associated with mortality.\u0000Conclusion\u0000Statistical models developed from a physician-curated feature space of structured EHR data predicted patient deaths within 30 days of radiotherapy consultation better than a model developed only with a patient's age and physician-assessed KPS. With clinically explicable feature weights, these models could influence treatment decisions such as the length of palliative radiotherapy courses.","PeriodicalId":501437,"journal":{"name":"medRxiv - Oncology","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142268343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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