Prevalence of Missing Data in the National Cancer Database and Association with Overall Survival

Yang, Daniel X.; Khera, Rohan; Miccio, Joseph A.; Jairam, Vikram; Chang, Enoch; Yu, James B.; Park, Henry S.; Krumholz, Harlan M.; Aneja, Sanjay

doi:10.1001/jamanetworkopen.2021.1793

Cited by 135Global Cancer Incidence and ScreeningMedical Coding and Health InformationElectronic Health Records Systems

Prevalence of Missing Data in the National Cancer Database and Association with Overall Survival

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Yang, Daniel X., Khera, Rohan, Miccio, Joseph A., Jairam, Vikram, Chang, Enoch, Yu, James B., Park, Henry S., Krumholz, Harlan M. +1 more·2021·JAMA Network Open

DOI 10.1001/jamanetworkopen.2021.1793PMC PMC7988369

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Abstract

Importance: Cancer registries are important real-world data sources consisting of data abstraction from the medical record; however, patients with unknown or missing data are underrepresented in studies that use such data sources. Objective: To assess the prevalence of missing data and its association with overall survival among patients with cancer. Design, Setting, and Participants: In this retrospective cohort study, all variables within the National Cancer Database were reviewed for missing or unknown values for patients with the 3 most common cancers in the US who received diagnoses from January 1, 2006, to December 31, 2015. The prevalence of patient records with missing data and the association with overall survival were assessed. Data analysis was performed from February to August 2020. Exposures: Any missing data field within a patient record among 63 variables of interest from more than 130 total variables in the National Cancer Database. Main Outcomes and Measures: Prevalence of missing data in the medical records of patients with cancer and associated 2-year overall survival. Results: A total of 1 198 749 patients with non-small cell lung cancer (mean [SD] age, 68.5 [10.9] years; 628 811 men [52.5%]), 2 120 775 patients with breast cancer (mean [SD] age, 61.0 [13.3] years; 2 101 758 women [99.1%]), and 1 158 635 patients with prostate cancer (mean [SD] age, 65.2 [9.0] years; 100% men) were included in the analysis. Among those with non-small cell lung cancer, 851 295 patients (71.0%) were missing data for variables of interest; 2-year overall survival was 33.2% for patients with missing data and 51.6% for patients with complete data (P < .001). Among those with breast cancer, 1 161 096 patients (54.7%) were missing data for variables of interest; 2-year overall survival was 93.2% for patients with missing data and 93.9% for patients with complete data (P < .001). Among those with prostate cancer, 460 167 patients (39.7%) were missing data for variables of interest; 2-year overall survival was 91.0% for patients with missing data and 95.6% for patients with complete data (P < .001). Conclusions and Relevance: This study found that within a large cancer registry-based real-world data source, there was a high prevalence of missing data that were unable to be ascertained from the medical record. The prevalence of missing data among patients with cancer was associated with heterogeneous differences in overall survival. Improvements in documentation and data quality are necessary to make optimal use of real-world data for clinical advancements.

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Studies on cancer registries reveal frequent missing data due to inadequate documentation, such as absent cancer stage or test results, which affects the diagnosis and evaluation process and lowers survival rates.
“For example, studies on cancer registries reveal frequent missing data due to inadequate documentation, such as absent cancer stage or test results, which affects the diagnosis and evaluation process and lowers survival rates [178].”
From Toward Safer Diagnoses: A SEIPS-Based Narrative Review of Diagnostic Errors (2026) · cites this paper as [178]
The Introduction and Discussion report frequent missing registry data linked to incomplete medical-record documentation, including cancer stage, and say such gaps may affect treatment decisions. The Discussion reports an association with worse overall survival in some groups but explicitly cautions that missing data itself may not be the reason; it does not establish that missing test results impair diagnosis or evaluation and thereby lower survival. (LLM, conf=0.88)
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Real-World Data: Applications and Relevance to Cancer Clinical Trials
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Cervical cancer disparities in stage at presentation for disaggregated Asian Americans, Native Hawaiians, and Pacific Islanders
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A systematic review of methods to estimate colorectal cancer incidence using population-based cancer registries
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Liver oligometastatic disease in synchronous metastatic gastric cancer patients: a nationwide population-based cohort study
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Validation of algorithms to select patients with multiple myeloma and patients initiating myeloma treatment in the national Veterans Affairs Healthcare System
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Inclusive Digital Health
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Insurance-Based Disparities in Guideline-Concordant Thyroid Cancer Care in the Era of De-escalation
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Analysis identifying minimal governing parameters for clinically accurate in silico fractional flow reserve
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Data From a One-Stop-Shop Comprehensive Cancer Screening Center
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A patient-driven clinicogenomic partnership for metastatic prostate cancer
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Medicaid expansion and 2-year survival in women with gynecologic cancer: a difference-in-difference analysis
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Particle Swarm Optimized Gaussian Process Classifier for Treatment Discontinuation Prediction in Multicohort Metastatic Castration-Resistant Prostate Cancer Patients
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FACILITATE: A real-world, multicenter, prospective study investigating the utility of a rapid, fully automated real-time PCR assay versus local reference methods for detecting epidermal growth factor receptor variants in NSCLC
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The yield of diagnostic laparoscopy with peritoneal lavage in gastric adenocarcinoma: A retrospective cohort study
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Factors Associated with Missing Sociodemographic Data in the IRIS® (Intelligent Research in Sight) Registry
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Real world data in mechanical thrombectomy: who are we losing to follow-up?
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Disparities in Presentation, Treatment, and Survival in Anaplastic Thyroid Cancer
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Preserving Informative Presence: How Missing Data and Imputation Strategies Affect the Performance of an AI-Based Early Warning Score
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Health Disparities among Patients with Cancer Who Received Molecular Testing for Biomarker-Directed Therapy
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A Clinical Decision Tool to Calculate Pretest Probability of Sentinel Lymph Node Metastasis in Primary Cutaneous Melanoma
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Toward Safer Diagnoses: A SEIPS-Based Narrative Review of Diagnostic Errors
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Adjusting for Population Differences in the National Cancer Database to Better Represent United States Cancer Cases: A Reference Tool for Researchers
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Five‐Year Survival Prognosis of Early‐Onset and Later‐Onset Colorectal Cancer by Clinical and Lifestyle Characteristics
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The 17-Gene Genomic Prostate Score Assay Is Prognostic for Biochemical Failure in Men With Localized Prostate Cancer After Radiation Therapy at a Community Cancer Center
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Multiagent Chemotherapy Followed by Stereotactic Body Radiotherapy Versus Conventional Radiotherapy for Resected Pancreas Cancer
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Is cancer stage data missing completely at random? A report from a large population-based cohort of non-small cell lung cancer
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Survival benefits of Cytoreductive Nephrectomy in patients with metastatic renal cell carcinoma: evidence from a SEER-based retrospective cohort study
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Prognostic Impact of Primary Tumor Size in Thymic Epithelial Tumor: An NCDB-Based Study
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Treatment Interruptions During Stereotactic Body Radiotherapy for Prostate Cancer
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Body mass index and cancer mortality in patients with incident type 2 diabetes: A population‐based study of adults in England
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Medicaid Expansion and Postoperative Mortality in Women with Gynecologic Cancer: A Difference-in-Difference Analysis
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Enhancing the National Cancer Database content using natural language processing and electronic health record data
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Validation of RUBY for Breast Cancer Knowledge Extraction From a Large French Electronic Medical Record System
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High-dimensional multiple imputation for partially observed confounders including natural language processing–derived auxiliary covariates
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Declining use of inguinofemoral lymphadenectomy in the treatment of clinically negative, pathologic node positive vulvar cancer
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Patterns of Care and Data Quality in a National Registry of Black and White Patients with Merkel Cell Carcinoma
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Socioeconomic and Survival Analysis of Radioembolization in Patients with Intrahepatic Cholangiocarcinoma: A Propensity Score–Adjusted Study
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Better tools for better estimates: improving approaches to handling missing data in Swiss cancer registries
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Colon Cancer Survival Among South Asian Americans: A Cross-Sectional Analysis of a National Dataset
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Liver Oligometastatic Disease in Synchronous Metastatic Gastric Cancer Patients: A Nationwide Population-Based Cohort StudyPreprint
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The ICGC ARGO data dictionary for standardizing global cancer clinical data
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Revolutionizing Lung Cancer Detection: A High‐Accuracy Machine Learning Framework for Early Diagnosis
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Multiple imputation for missing values in ordinal variables from cancer registry data when performing Cox proportional hazards regression
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Variation in opioid filling after same-day breast surgery in Ontario, Canada: a population-based cohort study
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Quality and Location of the Surgical Episode Mediate a Large Proportion of Socioeconomic-Based Survival Disparities in Patients with Resected Stage I–III Colon Cancer
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Antibiotic Prophylaxis in Breast Cancer Surgery: A Multicontinental Survey Study
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Breast cancer survival and mortality among women with type 2 diabetes: a retrospective cohort study
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Modernizing data and data science infrastructure as a strategic asset for cancer center
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Efficacy of Adjuvant Chemoimmunotherapy versus Chemotherapy and the Impact of Lymph Node Dissection on Survival
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Cancers of unknown primary: Survival by histologic type, demographic features, and treatment in the U.S. Military Health System
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Discriminatory Ability and Clinical Utility of the AJCC7 and AJCC8 Staging Systems for Breast Cancer in a Middle-Income Setting
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Pancreatic Cancer Classification Using Missing Data Imputation And Cluster-Based Undersampling Methods: A Comparative Analysis With Multiple Machine Learning Algorithms
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Use of the National Cancer Database in Identifying Disparities in Cancer Treatment
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Assessing data completeness in the international society for the study of pleura and peritoneum (ISSPP) PIPAC database: a multicenter evaluation from 2020–2024
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Real‐world Big‐data: Strengths and weaknesses of ASCO 's CancerLinQ ® discovery multiple myeloma dataset
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Nationwide changes in radiation oncology travel and location of care before and during the COVID-19 pandemic
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High variability in what is considered important to report following instability surgery: a Delphi study among Dutch shoulder specialists
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Personalized Medicine in Localized Prostate Cancer: Are We There Yet?
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Inter-hospital variation in data collection, radiotherapy treatment, and survival in patients with head and neck cancer: A multisite study
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Authors: Yang, D. X., Khera, R., Miccio, J. A., Jairam, V., Chang, E., Yu, J. B., Park, H. S., Krumholz, H. M., & Aneja, S.
Affiliations: Yale University (US)
Corresponding author: Aneja, Sanjay
ORCID: Yang, Daniel X.
Khera, Rohan
Jairam, Vikram
Chang, Enoch
Yu, James B.
Park, Henry S.
Krumholz, Harlan M.
Aneja, Sanjay
Venue: JAMA Network Open
Publisher: American Medical Association (AMA)
Published: 2021-03-23
Volume: 4
Issue: 3
Pages: e211793
ISSN: 2574-3805 (ISSN-L)
DOI: 10.1001/jamanetworkopen.2021.1793
PMC: PMC7988369
OpenAlex: W3135917060
Cited by: 135
References: 55
Citations by year: 2026: 28 · 2025: 22 · 2024: 23 · 2023: 33 · 2022: 26 · 2021: 3
FWCI: 7.74
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
Locations: JAMA Network Open (publishedVersion, cc-by)
medRxiv (acceptedVersion)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
Funders: Conquer Cancer Foundation
Yale University
Yale SPORE in Lung Cancer
Topics: Health Sciences › Medicine › Oncology › Global Cancer Incidence and Screening
Health Sciences › Health Professions › Health Information Management › Medical Coding and Health Information
Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
Keywords: missing data, data quality, cancer registry, National Cancer Database, overall survival, non-small cell lung cancer, breast cancer, prostate cancer, data abstraction, real-world data, data sharing restrictions, data access restrictions
MeSH terms: Data Management, Aged, Female, Follow-Up Studies, Humans, Male, Middle Aged, Neoplasms, Registries, Retrospective Studies, United States, Prevalence, Survival Rate, Databases, Factual

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Prevalence of Missing Data in the National Cancer Database and Association with Overall Survival

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