ReviewClinical & developmental immunology2010
Prognostic and diagnostic value of spontaneous tumor-related antibodies.
Review in Clinical & developmental immunology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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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
10 citing papers in PubMed.
- Anti-ALK autoantibodies in patients with ALK-positive Non-Small Cell Lung Cancer (NSCLC): A monocentric experience.The journal of liquid biopsy · 2024Article
- Tumor diagnosis using carbon-based quantum dots: Detection based on the hallmarks of cancer.Bioactive materials · 2024Review
- The Autoantibodies against Tumor-Associated Antigens as Potential Blood-Based Biomarkers in Thyroid Neoplasia: Rationales, Opportunities and Challenges.Biomedicines · 2022Review
- Circulating Biomarkers of Colorectal Cancer (CRC)-Their Utility in Diagnosis and Prognosis.Journal of clinical medicine · 2021Review
- Early diagnosis of hollow viscus injury using intestinal fatty acid-binding protein in blunt trauma patients.Medicine · 2017Article
- Functional autoantibodies against SSX-2 and NY-ESO-1 in multiple myeloma patients after allogeneic stem cell transplantation.Cancer immunology, immunotherapy : CII · 2014Article
- Manipulation of tumour-infiltrating B cells and tertiary lymphoid structures: a novel anti-cancer treatment avenue?Cancer immunology, immunotherapy : CII · 2014Review
- Colorectal cancer: from prevention to personalized medicine.World journal of gastroenterology · 2014Review
- Tumor-associated autoantibodies as diagnostic and prognostic biomarkers.BMB reports · 2012Review
- Screening for colorectal cancer: established and emerging modalities.Nature reviews. Gastroenterology & hepatology · 2011Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
There is an urgent need for earlier diagnosis of malignancies and more stringent monitoring of relapses after antitumor therapy. In addition, new prognostic markers are needed for risk stratification and design of individualized cancer therapies. New diagnostic and prognostic parameters should overcome the impairments of current standards in a cost-effective manner. Serological approaches measuring spontaneous antibody responses against tumor-associated antigens could be of use as diagnostic and prognostic markers and could also be employed to evaluate response to therapy in cancer patients. Autoantibodies have been suggested to be of frequent and specific occurrence in patients with malignancies and to correlate with clinical parameters. Screening the relevant literature on this topic, we suggest that the analysis of single antibody specificities is unlikely to provide sufficient diagnostic and prognostic accuracy. The combined analysis of autoantibodies targeting different antigens, however, may reach high sensitivity and specificity. In addition, screening cancer patients for autoantibodies might identify subgroups with high relapse risk and a worse prognosis. Larger prospective trials should be initiated to identify sets of tumor-associated autoantibodies suited for the use in diagnostic algorithms for cancer detection and followup.
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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.