ReviewCancer2019
The opportunities and shortcomings of using big data and national databases for sarcoma research.
Review in Cancer, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 2 of them syntheses 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
38 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Impact of Sex and Deprivation on Neuroendocrine Tumour Survival: Challenges of Heterogeneous Data.Neuroendocrinology · 2025Pooled it
- Evaluation of reporting quality of cohort studies using real-world data based on RECORD: systematic review.BMC medical research methodology · 2023Pooled it
- Twelve-Month Metastatic State as a Landmark-Based Prognostic Stratifier in Metastatic Sarcoma.Cancers · 2026Article
- Locked-Window EQ-5D-5L (Index and VAS) Benchmarking in Sarcoma Care: Rule-Based Traffic-Light Classification Across Two Institutions.Diseases (Basel, Switzerland) · 2026Article
- A comparison of organ preservation in older adults with stage I rectal cancer.International journal of colorectal disease · 2025Article
- Revolutionising osseous biopsy: the impact of artificial intelligence in the era of personalized medicine.The British journal of radiology · 2025Review
- Article
- Adjuvant Chemotherapy for High-Risk Stage II Colon Cancer: A Population-Based Study.Journal of gastrointestinal cancer · 2025Article
- De Novo Natural Language Processing Algorithm Accurately Identifies Myxofibrosarcoma From Pathology Reports.Clinical orthopaedics and related research · 2025Article
- Epidemiology and survival outcomes for liposarcoma patients in England: An observational cohort study using real world data.Rare tumors · 2025Article
- Machine learning-based radiomics prognostic model for patients with proximal esophageal cancer after definitive chemoradiotherapy.Insights into imaging · 2024Article
- The Multi-Institutional Medullary Thyroid Cancer Collaborative Registry: Can a Rare Tumor Registry Accurately Represent the Real-World Patient Population?Thyroid : official journal of the American Thyroid Association · 2024Article
- Article
- Neoadjuvant Intra-arterial Cytoreductive Chemotherapy Improves Outcomes in Lacrimal Gland Adenoid Cystic Carcinoma.The oncologist · 2024Article
- Explainable Model Using Shapley Additive Explanations Approach on Wound Infection after Wide Soft Tissue Sarcoma Resection: "Big Data" Analysis Based on Health Insurance Review and Assessment Service Hub.Medicina (Kaunas, Lithuania) · 2024Article
- Article
- Does primary tumor resection improve survival for patients with sarcomas of pelvic bones, sacrum, and coccyx who have metastasis at diagnosis ?European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2023Article
- Predicting survival and prognosis in early-onset locally advanced colon cancer: a retrospective observational study.International journal of colorectal disease · 2023Observational
- Association of Rural Residence and Receipt of Guideline-Concordant Care for Locoregional Colon Cancer.Annals of surgical oncology · 2023Article
- The Midwest Sarcoma Trials Partnership: Bridging Academic and Community Networks in a Collaborative Approach to Sarcoma.Journal of clinical medicine · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
The rarity and heterogeneity of sarcomas make performing appropriately powered studies challenging and magnify the significance of large databases in sarcoma research. Established large tumor registries and population-based databases have become increasingly relevant for answering clinical questions regarding sarcoma incidence, treatment patterns, and outcomes. However, the validity of large databases has been questioned and scrutinized because of the inaccuracy and wide variability of coding practices and the absence of clinically relevant variables. In addition, the utilization of large databases for the study of rare cancers such as sarcoma may be particularly challenging because of the known limitations of administrative data and poor overall data quality. Currently, there are several large national cancer databases, including the Surveillance, Epidemiology, and End Results database, the National Cancer Data Base of the American College of Surgeons and the American Cancer Society, and the National Program of Cancer Registries of the Centers for Disease Control and Prevention. These databases are often used for sarcoma research, but they are limited by their dependence on administrative or billing data, the lack of agreement between chart abstractors on diagnosis codes, and the use of preexisting documented hospital diagnosis codes for tumor registries, which lead to a significant underestimation of sarcomas in large data sets. Current and future initiatives to improve databases and big data applications for sarcoma research include increasing the utilization of sarcoma-specific registries and encouraging national initiatives to expand on real-world, evidence-based data sets.
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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.