ReviewMolecular oncology2014
Molecular pathology - the value of an integrative approach.
Review in Molecular oncology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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
17 citing papers in PubMed.
- Metabolic fingerprinting enables rapid, label-free histopathology in gastric cancer diagnosis and prognostic prediction.Cell reports. Medicine · 2025Article
- Deep learning classification of lung cancer histology using CT images.Scientific reports · 2021Article
- Article
- The Role of the Pathologist in the Next-Generation Era of Tumor Molecular Characterization.Diagnostics (Basel, Switzerland) · 2021Review
- NTRK Fusions, from the Diagnostic Algorithm to Innovative Treatment in the Era of Precision Medicine.International journal of molecular sciences · 2020Review
- The leading role of pathology in assessing the somatic molecular alterations of cancer: Position Paper of the European Society of Pathology.Virchows Archiv : an international journal of pathology · 2020Review
- Validated clinico-pathologic nomogram in the prediction of HER2 status in gastro-oesophageal cancer.British journal of cancer · 2019Article
- Time for change: a new training programme for morpho-molecular pathologists?Journal of clinical pathology · 2018Review
- The ins and outs of molecular pathology reporting.Virchows Archiv : an international journal of pathology · 2017Review
- Embracing an integromic approach to tissue biomarker research in cancer: Perspectives and lessons learned.Briefings in bioinformatics · 2017Article
- Tissue-based next generation sequencing: application in a universal healthcare system.British journal of cancer · 2017Review
- The Role of ATRX in Glioma Biology.Frontiers in oncology · 2017Review
- Article
- Article
- PICan: An integromics framework for dynamic cancer biomarker discovery.Molecular oncology · 2015Article
- High mobility group box-1 and its clinical value in breast cancer.OncoTargets and therapy · 2015Article
- Molecular pathology - the value of an integrative approach.Molecular oncology · 2014Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Molecular Pathology (MP) is at the heart of modern diagnostics and translational research, but the controversy on how MP is best developed has not abated. The lack of a proper model or trained pathologists to support the diagnostic and research missions makes MP a rare commodity overall. Here we analyse the scientific and technology areas, in research and diagnostics, which are encompassed by MP of solid tumours; we highlight the broad overlap of technologies and analytical capabilities in tissue research and diagnostics; and we describe an integrated model that rationalizes technical know-how and pathology talent for both. The model is based on a single, accredited laboratory providing a single standard of high-quality for biomarker discovery, biomarker validation and molecular diagnostics.
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.