Article
Oncology
Jennifer K. Plichta, Christel N. Rushing, Holly C. Lewis, Marguerite M. Rooney, Dan G. Blazer, Samantha M. Thomas, E. Shelley Hwang, Rachel A. Greenup
Summary: This study evaluated the association between missing data and overall survival in national cancer registries and found that missingness of select variables is not uncommon and is associated with worse overall survival.
BREAST CANCER RESEARCH AND TREATMENT
(2023)
Article
Public, Environmental & Occupational Health
Stephen R. Cole, Paul N. Zivich, Jessie K. Edwards, Bonnie E. Shook-Sa, Michael G. Hudgens
Summary: We describe an approach to sensitivity analysis for missing data, focusing on the relationship between outcomes and missingness. The approach can handle completely random missingness, missingness dependent on observed data, and missingness not dependent on observed data. Examples from HIV are provided to illustrate the sensitivity of estimation under different missingness mechanisms. This approach allows for examination of the impact of missing data bias on the results of epidemiologic studies.
Article
Public, Environmental & Occupational Health
Maya B. Mathur
Summary: We propose sensitivity analyses for complete-case estimates of treatment effects to address biases caused by non-random missing data. These analyses use simple summary data and avoid distributional assumptions. The proposed methods bound the overall treatment effect by considering unobserved treatment effects among nonretained participants and the strengths of confounding associations among retained participants. The introduction of the M-value as an analog to the E-value provides a measure of the strength of confounding associations required to mitigate the treatment effect. These methods can help evaluate the robustness of complete-case analyses to potential biases due to missing data.
AMERICAN JOURNAL OF EPIDEMIOLOGY
(2023)
Article
Medicine, General & Internal
Loukia M. Spineli, Chrysostomos Kalyvas, Katerina Papadimitropoulou
Summary: This study investigates the prevalence of robust conclusions in systematic reviews addressing missing outcome data and compares them with current sensitivity analysis standards. The study found that studies with significant missing outcome data tend to have more frail conclusions. The newly proposed robustness index (RI) indicates that a considerable proportion of analyses fail to demonstrate robustness compared to when using current sensitivity analysis standards.
Article
Oncology
Jianyong Wang, Nan Chen, Jixiang Guo, Xiuyuan Xu, Lunxu Liu, Zhang Yi
Summary: The proposed SurvNet model, trained in a multi-task learning framework, effectively handles missing values and complex features. It outperforms traditional Cox models and Cox-Net models, showing superior performance on real-world datasets.
FRONTIERS IN ONCOLOGY
(2021)
Article
Computer Science, Artificial Intelligence
C. G. Marcelino, G. M. C. Leite, P. Celes, C. E. Pedreira
Summary: This paper investigates the effects and possible solutions to incomplete databases in regression and provides a systematic view of how missing data may affect regression results by analyzing actual publicly available databases. The results indicate that the impact of missing data can be significant, and the K-Nearest Neighbors method performs better in regression with missing data.
APPLIED ARTIFICIAL INTELLIGENCE
(2022)
Article
Oncology
Hung Nguyen, Duc Tran, Bang Tran, Monikrishna Roy, Adam Cassell, Sergiu Dascalu, Sorin Draghici, Tin Nguyen
Summary: Cancer is a complex term with various diseases, and successful treatment relies on accurate subtyping. SMRT, a new method for multi-omics integration and cancer subtyping, offers advantages such as speed, strong data integration capabilities, and user-friendly features.
FRONTIERS IN ONCOLOGY
(2021)
Article
Energy & Fuels
Dongyeon Jeong, Chiwoo Park, Young Myoung Ko
Summary: The study introduces a mixture factor analysis method for estimating missing values in building electric load data. Due to quality issues in building electric load data, a novel data imputation model is proposed to represent patterns and their cyclic rotations, providing better handling of missing data problems and improving efficiency and accuracy in model selection.
Article
Medicine, General & Internal
Lisa Goudman, Geert Molenberghs, Rui Duarte, Maarten Moens
Summary: New waveforms in Spinal Cord Stimulation have led to the development of High-Dose SCS (HD-SCS), with missing data analysis revealing a tipping point sensitivity at a shift parameter of 17 for disability scores, ensuring robust conclusions regarding the therapy's effectiveness over time.
JOURNAL OF CLINICAL MEDICINE
(2021)
Article
Health Care Sciences & Services
Daniela Krepper, Johannes Maria Giesinger, Linda Dirven, Fabio Efficace, Caroline Martini, Anna Margarete Maria Thurner, Imad Al-Naesan, Franziska Gross, Monika Judith Sztankay
Summary: This review examines the statistical handling of missing patient-reported outcome (PRO) data in clinical trials for breast cancer patients. The study found that while most trials reported the extent of missing data, only a small percentage explicitly stated the statistical approach for handling missing data.
JOURNAL OF CLINICAL EPIDEMIOLOGY
(2023)
Review
Mathematical & Computational Biology
James R. Carpenter, Melanie Smuk
Summary: This article addresses the issue of missing data in medical research, discussing methods such as multiple imputation and sensitivity analysis. It provides practical approaches for practitioners to tackle issues arising from missing data and gives an overview of the relationships between various methods in the literature.
BIOMETRICAL JOURNAL
(2021)
Article
Health Care Sciences & Services
Zhiping Qiu, Huijuan Ma, Jianwei Chen, Gregg E. Dinse
Summary: The paper discusses the quantile regression model for survival data with missing censoring indicators, proposes two weighted estimating equations based on the augmented inverse probability weighting technique, and establishes asymptotic properties of the resultant estimators and resampling-based inference procedures. The performance of the proposed approaches is investigated in simulation studies and a real data application.
STATISTICAL METHODS IN MEDICAL RESEARCH
(2021)
Article
Biology
Yunwei Zhang, Germaine Wong, Graham Mann, Samuel Muller, Jean Y. H. Yang
Summary: This article introduces the importance of survival analysis and proposes a new benchmarking design, SurvBenchmark, for evaluating the performance of various survival models on clinical and omics datasets. Through a systematic comparison of 320 comparisons, it demonstrates the variations of survival models in real-world applications and highlights the importance of using multiple performance metrics for evaluation.
Article
Public, Environmental & Occupational Health
Hongsheng Lu, Lu Li, Yongran Cheng, Zhaohui Yang, Xuequan Cao, Hui Zhang, Dongju Qiao, Liangyou Wang, Tianhui Chen
Summary: This study aimed to assess the long-term survival of cervical cancer patients in eastern China, using cancer registry data from Taizhou. The 5-year relative survival rate for patients with cervical cancer during 2014-2018 was 90.9%, with variations based on age at diagnosis and region. The projected 5-year relative survival rate for the period 2019-2023 is expected to reach 94.2%.
FRONTIERS IN PUBLIC HEALTH
(2022)
Article
Public, Environmental & Occupational Health
Katherine J. Lee, John B. Carlin, Julie A. Simpson, Margarita Moreno-Betancur
Summary: Researchers are advised to classify their missing data as MCAR, MAR, or MNAR when analyzing the data. However, the original classification by Rubin in the 1970s has two major problems. First, it is difficult to assess the plausibility of the MAR assumption when there are missing data in multiple variables. Second, MCAR and MAR are not necessary conditions for consistent estimation, so the classification does not determine the best approach for handling missing data.
INTERNATIONAL JOURNAL OF EPIDEMIOLOGY
(2023)
Article
Surgery
Nicholas A. Elmer, Sthefano Araya, Juliet Panichella, Brian Egleston, Mengying Deng, Sameer A. Patel
Summary: This study aimed to understand the temporal pattern and risk factors associated with lower extremity free flap failure. It found a reoperation rate of 14.5% within the first 30 postoperative days, with patients with vascular indications having the highest rate. The rate of reoperation was highest during the first 2 days postoperative and significantly decreased afterwards. African American race, malignant tumors, prosthetic/implant complications, and wound/infectious indications were significant predictors for reoperation.
ANNALS OF PLASTIC SURGERY
(2023)
Letter
Oncology
Benjamin G. Carlisle, Donna L. Coffman, Brian L. Egleston, Maia Salholz-Hillel
ANNALS OF SURGICAL ONCOLOGY
(2023)
Article
Psychology, Clinical
Bradley N. Collins, Stephen J. Lepore, Brian L. Egleston
Summary: This study aimed to examine the effectiveness of the BLiSS multilevel intervention in promoting smoking cessation among low-income maternal smokers and its impact on smoking relapse rates over a 12-month period. The results showed that mothers who received the intervention were more likely to eliminate their children's tobacco smoke exposure within three months, which was significantly associated with long-term smoking abstinence.
JOURNAL OF BEHAVIORAL MEDICINE
(2023)
Article
Oncology
Brian L. Egleston, Richard J. Bleicher, Carolyn Y. Fang, Thomas J. Galloway, Slobodan Vucetic
Summary: Additional evaluations and second opinions before breast cancer surgery may improve care, but could cause detrimental delays. This study investigates the timing of surgical delays associated with survival benefits and potential harm. It found that quick new patient visits have a protective association with breast cancer mortality, but substantial delays may increase mortality in older patients. Similarly, delays in medical oncologist and surgeon visits can also have negative impacts on outcomes.
Article
Surgery
Sthefano Araya, Theresa K. K. Webster, Brian Egleston, Grace M. M. Amadio, Juliet C. C. Panichella, Nicholas A. A. Elmer, Sameer A. A. Patel
Summary: This study reviewed the impact of ERAS implementation on the length of stay (LOS) in patients undergoing DIEP free-flap breast reconstruction. The results showed that the implementation of ERAS protocols led to a significant decrease in LOS and supported safe discharge on postoperative days 2-3.
ANNALS OF PLASTIC SURGERY
(2023)
Article
Oncology
Madison Kilbride, Brian L. Egleston, Wendy K. Chung, Olufunmilayo Olopade, Kara N. Maxwell, Payal Shah, Jane E. Churpek, Linda Fleisher, Mary Beth Terry, Dominique Fetzer, Jill Bennett Gaieski, Jessica Bulafka, Aileen Espinal, Kelsey Karpink, Sarah Walser, Davone Singleton, Monica Palese, Ilona Siljander, Amanda Brandt, Dana Clark, Carrie Koval, Julia Wynn, Jessica M. Long, Danielle Mckenna, Jacquelyn Powers, Sarah Nielsen, Susan M. Domchek, Katherine L. Nathanson, Angela R. Bradbury
Summary: The study showed high interest in web-based predisclosure education for returning genetic research results, but it did not increase the uptake of results. There were no negative patient-reported outcomes with web education, indicating that it is a viable alternative delivery model for reducing burdens and costs of returning genetic research results.
JOURNAL OF CLINICAL ONCOLOGY
(2023)
Article
Public, Environmental & Occupational Health
Amy H. Auchincloss, Francesca Mucciaccio, Carolyn Y. Fang, Dominic A. Ruggiero, Jana A. Hirsch, Julia Zhong, Minzi Li, Brian L. Egleston, Marilyn Tseng
Summary: This study examined the relationship between neighborhood social composition, gentrification, and acculturation stress among first-generation Chinese immigrants. The findings showed that Chinese immigrants living in neighborhoods with a higher proportion of Chinese immigrants and higher wealth experienced lower acculturation stress, while gentrification had no impact.
SSM-POPULATION HEALTH
(2023)
Article
Health Care Sciences & Services
Margaret L. Longacre, Marcin Chwistek, Cynthia Keleher, Mark Siemon, Brian L. Egleston, Molly Collins, Carolyn Y. Fang
Summary: The study demonstrates the usability and satisfaction of a patient-caregiver portal system in engaging caregivers systematically. The system allows patients to specify their caregiver and communication preferences, connects caregivers to a unique portal page, and provides electronic notifications to the care team. The findings highlight the need for further research on caregivers of patients with different illnesses.
JMIR HUMAN FACTORS
(2023)
Meeting Abstract
Oncology
Mary Daly, Brian Egleston, Kaitlyn Lew, Lisa Bealin, Alexander Husband, Jill Stopfe, Pawel Przybysz, Olga Tchuvatkina, Yu-Ning Wong, Judy Garber, Timothy Rebbeck
Meeting Abstract
Oncology
Brian Egleston, Mary Daly, Kaitlyn Lew, Lisa Bealin, Alexander Husband, Jill Stopfer, Pawel Przybysz, Olga Tchuvatkina, Yu-Ning Wong, Judy Garber, Timothy Rebbeck
Article
Social Sciences, Mathematical Methods
Brian L. Egleston, Ashis Kumar Chanda, Tian Bai, Carolyn Y. Fang, Richard J. Bleicher, Slobodan Vucetic
Summary: Identification of procedures using medical codes for medical claims research is challenging. Pointwise Mutual Information can be used to find associated codes. In a study on racial differences in breast cancer outcomes, treatment definitions were identified using the Pointwise Mutual Information statistic. The study found that survival disparities between Black and White women were completely eliminated with augmented treatment definitions.
METHODOLOGY-EUROPEAN JOURNAL OF RESEARCH METHODS FOR THE BEHAVIORAL AND SOCIAL SCIENCES
(2023)
Meeting Abstract
Oncology
Marilyn Tseng, Brian Egleston, Julia Zhong, Minzi Li, Carolyn Fang
CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION
(2023)
Meeting Abstract
Oncology
Ella Batterson, Marilyn Tseng, Emily C. Walton, Brian Egleston, Julia Zhong, Minzi Li, Carolyn Fang
CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION
(2023)
Article
Computer Science, Interdisciplinary Applications
Joanna Woersching, Janet H. Van Cleave, Brian Egleston, Chenjuan Ma, Judith Haber, Deborah Chyun
Summary: This study analyzed the data quality of automated comorbidity lists in electronic health records and found deficiencies in documentation. The automatic comorbidity lists were found to be less accurate in identifying comorbidities compared to provider narrative notes. This may have implications for healthcare delivery and clinical research.
CIN-COMPUTERS INFORMATICS NURSING
(2022)
Meeting Abstract
Oncology
Janet H. Van Cleave, Catherine Concert, Kenneth S. Hu, Eva Liang, Brian L. Egleston
ONCOLOGY NURSING FORUM
(2022)
