ArticleFrontiers in oncology2016
Validation of Claims Algorithms for Progression to Metastatic Cancer in Patients with Breast, Non-small Cell Lung, and Colorectal Cancer.
Article in Frontiers in oncology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
27 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Systematic Review of Estimating Breast Cancer Recurrence at the Population Level With Administrative Data.Journal of the National Cancer Institute · 2020Pooled it
- Axillary Management in Clinically Node-Positive (cN1) Estrogen Receptor-Positive Breast Cancer.Cancers · 2026Article
- Assessing Concordance of Cancer Registry Data and Electronic Health Record Data in Metastatic Cancer: a Cohort Study of Patients with Colorectal Liver Metastasis in a U.S. Integrated Health System.Cancer epidemiology · 2026Article
- Longitudinal Language-Model Reasoning Enables Automated Labeling of Lung Cancer Recurrence from Unstructured Clinical Records.Research square · 2026Article
- Identifying the Initiation of a New Line of Therapy for Metastatic Lung, Breast, and Colorectal Cancer in Real-World Data: A Scoping Review.Pharmacoepidemiology and drug safety · 2026Article
- Emergency cancer diagnosis in Paris: A cross-sectional study using AP-HP data.International journal of cancer · 2025Article
- Assigning cancer stage to patients using administrative claims data: an example for colon and rectal cancers.BMC health services research · 2025Article
- Article
- Real World Evidence on Hormone Receptor Positive and Human Epidermal Growth Factor Receptor 2 Negative Metastatic Breast Cancer in Italy: Insights From 2017 to 2021 Data.ClinicoEconomics and outcomes research : CEOR · 2025Article
- Racial comparisons in treatment of rectal adenocarcinoma and survival in the military health system.JNCI cancer spectrum · 2024Article
- Productivity loss by cancer stage in patients newly diagnosed with hepatocellular carcinoma: A claims database analysis.Journal of managed care & specialty pharmacy · 2024Article
- Biomarker Testing, Targeted Therapy and Clinical Trial Participation by Race Among Patients With Lung Cancer: A Real-World Medicaid Database Study.JTO clinical and research reports · 2024Article
- Development of a Machine Learning Model to Identify Colorectal Cancer Stage in Medicare Claims.JCO clinical cancer informatics · 2023Article
- Novel Algorithm for the Estimation of Cancer Incidence Using Claims Data in Japan: A Feasibility Study.JCO global oncology · 2023Article
- Development and Validation of Coding Algorithms to Identify Patients with Incident Non-Small Cell Lung Cancer in United States Healthcare Claims Data.Clinical epidemiology · 2023Article
- An Automated Line-of-Therapy Algorithm for Adults With Metastatic Non-Small Cell Lung Cancer: Validation Study Using Blinded Manual Chart Review.JMIR medical informatics · 2021Article
- Broad-Spectrum Antibiotic Use and Disease Progression in Early-Stage Melanoma Patients: A Retrospective Cohort Study.Cancers · 2021Article
- Weakly supervised temporal model for prediction of breast cancer distant recurrence.Scientific reports · 2021Article
- A scoping review of core outcome sets and their 'mapping' onto real-world data using prostate cancer as a case study.BMC medical research methodology · 2020Article
- Using natural language processing to construct a metastatic breast cancer cohort from linked cancer registry and electronic medical records data.JAMIA open · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundValidated algorithms for identifying progression to metastatic cancer could permit the use of administrative claims databases for research in this area.
objectiveTo identify simple algorithms that could accurately detect cancer progression to metastatic breast, non-small cell lung, and colorectal cancer (CRC) using medical and pharmacy claims data.
methodsAdults with stage I-III breast, non-small cell lung cancer (NSCLC), or CRC in the Geisinger Health System from 2004 to 2011 were selected. Evidence of progression was extracted via manual chart review as the reference standard. In addition to secondary malignancy diagnosis (ICD-9 code for metastases), diagnoses, procedures, and treatments were selected with clinician input as indicators of cancer progression. Random forests models provided variable importance scores. In addition to codes for secondary malignancy, several more complex algorithms were constructed and performance measures calculated.
resultsAmong those with breast cancer [17/502 (3.4%) progressed], the performance of a secondary malignancy code was suboptimal [sensitivity: 64.7%; specificity: 86.0%; positive predictive value (PPV): 13.9; negative predictive value (NPV): 98.6%]; requiring malignancy at another site or initiation of immunotherapy increased PPV and specificity but decreased sensitivity. For NSCLC [61/236 (25.8%) progressed], codes for secondary malignancy alone (PPV: 47.4%; NPV: 84.8%; sensitivity: 60.7%; specificity: 76.6%) performed similarly or better than more complex algorithms. For CRC [33/276 (12.0%) progressed], secondary malignancy codes had good specificity (92.7%) and NPV (92.3%) but low sensitivity (42.4%) and PPV (43.8%); an algorithm with change in chemotherapy increased sensitivity but decreased other metrics.
conclusionSelected algorithms performed similarly to the presence of a secondary tumor diagnosis code, with low sensitivity/PPV and higher specificity/NPV. Accurate identification of cancer progression likely requires verification through chart review.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.