Literature DB >> 30610561

Lessons Learned Regarding Missing Clinical Stage in the National Cancer Database.

Tanya L Hoskin1, Judy C Boughey2, Courtney N Day3, Elizabeth B Habermann3,2,4.   

Abstract

BACKGROUND: The National Cancer Database (NCDB) is a valuable resource for studying national cancer treatment patterns. However, data abstraction rules from 2004 to 2007 resulted in missing clinical stage for a high percentage of cases. We investigated how this missingness can bias results in breast cancer studies including patients treated with neoadjuvant chemotherapy (NAC).
METHODS: The impact of missing clinical stage on the estimated percentage of breast cancers treated with NAC versus adjuvant chemotherapy (AC) was examined from 2004 to 2013. Trends in NAC use were presented, excluding those cases with missing clinical stage, and compared with trends after multiple imputation, performed using the chained equations approach with predictive mean matching.
RESULTS: Clinical stage was missing for 56% of cases in 2004-2007, versus 12% in 2008-2013, and was missing more than twice as often for AC patients versus NAC patients (31% vs. 12% overall), with the largest difference occurring in 2004-2007 (60% vs. 27% missing). Because stage was more frequently missing in AC patients, excluding those missing clinical stage introduced bias when considering NAC versus AC trends. With multiple imputation, significant increases in NAC use were identified between 2004 and 2013 for each stage: use for stage I was 2% in 2004 and 5% in 2013, use for stage II was 11% in 2004 and 24% in 2013, use for stage III was 34% in 2004 and 46% in 2013, in contrast to an analysis excluding those missing stage, which suggested little or no increase within any stage.
CONCLUSION: NCDB data abstraction rules from 2004 to 2007 resulted in missing clinical stage for > 50% of breast cancers, which may introduce substantial bias. Multiple imputation or exclusion of the years 2004-2007 should be considered to mitigate the problem of missing clinical stage in NCDB.

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Year:  2019        PMID: 30610561     DOI: 10.1245/s10434-018-07128-3

Source DB:  PubMed          Journal:  Ann Surg Oncol        ISSN: 1068-9265            Impact factor:   5.344


  4 in total

1.  Expanding the Secondary Use of Prostate Cancer Real World Data: Automated Classifiers for Clinical and Pathological Stage.

Authors:  Selen Bozkurt; Christopher J Magnani; Martin G Seneviratne; James D Brooks; Tina Hernandez-Boussard
Journal:  Front Digit Health       Date:  2022-06-02

2.  Prevalence of Missing Data in the National Cancer Database and Association With Overall Survival.

Authors:  Daniel X Yang; Rohan Khera; Joseph A Miccio; Vikram Jairam; Enoch Chang; James B Yu; Henry S Park; Harlan M Krumholz; Sanjay Aneja
Journal:  JAMA Netw Open       Date:  2021-03-01

3.  Nomogram Models for Predicting Risk and Prognosis of Newly Diagnosed Ovarian Cancer Patients with Liver Metastases - A Large Population-Based Real-World Study.

Authors:  Gui-Min Hou; Chuang Jiang; Jin-Peng Du; Chang Liu; Xiang-Zheng Chen; Ke-Fei Yuan; Hong Wu; Yong Zeng
Journal:  J Cancer       Date:  2021-10-25       Impact factor: 4.207

4.  Is Treatment at a High-volume Center Associated with an Improved Survival for Primary Malignant Bone Tumors?

Authors:  Azeem Tariq Malik; John H Alexander; Safdar N Khan; Thomas J Scharschmidt
Journal:  Clin Orthop Relat Res       Date:  2020-03       Impact factor: 4.755

  4 in total

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