Evidence map›Paper›PMID 28477149›Full record

ReviewMolecular diagnosis & therapy2017

Current and Emerging Applications of Droplet Digital PCR in Oncology.

Susana Olmedillas-López, Mariano García-Arranz, Damián García-Olmo

Registry-linked trialAbstract readReview
PubMed Publisher
In one paragraph

Review in Molecular diagnosis & therapy, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06105177 (Implementation of Up-front ctDNA Analysis Into Lung Cancer Care and Development of Liquid Biopsy-based Decision Support Models - the Lungmarker² Study), which is not on this map. Cited by 106 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
106citing papers in PubMed, 2 pooled it
6.4field-weighted citation impact, top 2% of its field
1 · What the graph read from 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.

2 · The registry

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.

NCT06105177 recruitingnot on this mapstarted 2023, after this paper: background citation

Implementation of Up-front ctDNA Analysis Into Lung Cancer Care and Development of Liquid Biopsy-based Decision Support Models - the Lungmarker² Study

Typeobservational_patient_registrySponsorCatharina Ziekenhuis EindhovenRan2023 to 2026Enrolled800ConditionsLung Cancer
3 · Its place in the literature

Who cites it

106 citing papers in PubMed, 2 syntheses or guidelines pooled it, 202 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Detection ofBiomolecules · 2021
    Trial
  4. Trial
  5. Trial
  6. Article
  7. Article
  8. Review
  9. Review
  10. Review
  11. Analysis of the Occurrence ofChildren (Basel, Switzerland) · 2025
    Article
  12. Review
  13. Article
  14. [Advances in Diagnosis and Targeted Therapy of KRASG12C Mutant 
Non-small Cell Lung Cancer].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2025
    Review
  15. Can mutation abundance assess the biological behavior of BRAFJournal of translational medicine · 2025
    Article
  16. Article
  17. Review
  18. Article
  19. Review
  20. Review

46 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Susana Olmedillas-LópezNew Therapies Laboratory, Foundation Health Research Institute-Fundación Jiménez Díaz University Hospital (FIIS-FJD), Avda. Reyes Católicos, 2, 28040, Madrid, Spain. susana.olmedillas@fjd.es.
Mariano García-ArranzNew Therapies Laboratory, Foundation Health Research Institute-Fundación Jiménez Díaz University Hospital (FIIS-FJD), Avda. Reyes Católicos, 2, 28040, Madrid, Spain.
Damián García-OlmoNew Therapies Laboratory, Foundation Health Research Institute-Fundación Jiménez Díaz University Hospital (FIIS-FJD), Avda. Reyes Católicos, 2, 28040, Madrid, Spain.
Hospital Universitario Fundación Jiménez Díaz · ESUniversidad Autónoma de Madrid · ES

Funding

Fondo de Investigaciones Sanitarias-FEDER FIS; PI13/01924ISCIII-FEDER RD12/0019/0035
6 · The paper itself

Abstract

The clinical management of cancer has evolved in recent years towards more personalized strategies that require a comprehensive knowledge of the complex molecular features involved in tumor growth and evolution, and the development of drug resistance mechanisms leading to disease progression. Droplet digital PCR (ddPCR) has become one of the most accurate and reliable tools for the examination of genetic alterations in a wide variety of cancers because of its high sensitivity and specificity. ddPCR is currently being applied for absolute allele quantification, rare mutation detection, analysis of copy number variations, DNA methylation, and gene rearrangements in different kinds of clinical samples. This methodology has proven useful for the evaluation of archival tumor tissues, where poor DNA quality and limited sample availability are major obstacles for standard methods, providing less subjective and more automated quantitative results. However, most applications of ddPCR in cancer are focused on liquid biopsies (including cell-free DNA as well as circulating tumor cells) because these represent non-invasive alternatives to tissue biopsies that can more accurately reflect intratumoral heterogeneity and track the dynamic changes in tumor burden that occur in response to treatment at different times during follow-up. A broad spectrum of molecular markers have been interrogated in blood using ddPCR for diagnostic, predictive, and monitoring purposes in various malignancies. Emerging alternative approaches using other body fluids such as cerebrospinal fluid and urine are also currently being developed. This article aims to give a complete overview of ddPCR applications for molecular screening in oncology.

Indexed as

Genetic VariationDrug Resistance, NeoplasmHumansLiquid BiopsyNeoplasmsParaffin EmbeddingPolymerase Chain ReactionPrecision MedicineTissue FixationBRAF V600E MutationKRAS MutationMinimal Residual DiseaseNSCLC PatientPIK3CA Mutation

Identifiers

PMID28477149
OpenAlexW2610953960

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.