Evidence map›Paper›PMID 40122129›Full record

SynthesisThe Cochrane database of systematic reviews2025

Next-generation sequencing for guiding matched targeted therapies in people with relapsed or metastatic cancer.

Farasat Kazmi, Nipun Shrestha, Tik Fung Dave Liu, Thomas Foord, Philip Heesen, Stephen Booth, David Dodwell, Simon Lord, Kheng-Wei Yeoh, Sarah P Blagden

Abstract readSystematic ReviewMeta-Analysis
In one paragraph

Synthesis in The Cochrane database of systematic reviews, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. A novel inflammatory-nutritional nomogram for predicting survival after minimally invasive surgery for spinal metastases: a comparison with the Katagiri and SORG systems.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 · 2026
    Article
  4. Article
  5. Observational
  6. Article
  7. Review
  8. Article
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

10 authors.

Farasat KazmiDepartment of Oncology, University of Oxford, Oxford, UK.
Nipun ShresthaHealth Evidence Synthesis, Recommendations and Impact (HESRI), School of Public Health, University of Adelaide, Adelaide, South Australia, Australia.
Tik Fung Dave LiuDepartment of Oncology, Norfolk and Norwich University Hospital, Norwich, UK.
Thomas FoordUniversity of Oxford, Oxford, UK.
Philip HeesenUniversity of Zurich, Zurich, Switzerland.
Stephen BoothDepartment of Haematology, Royal Berkshire Hospital, Reading, UK.
David DodwellNuffield Department of Population Health, University of Oxford, Oxford, UK.
Simon LordDepartment of Oncology, University of Oxford, Oxford, UK.
Kheng-Wei YeohRadiation Oncology, National Cancer Centre, Singapore, Singapore.
Sarah P BlagdenDepartment of Oncology, University of Oxford, Oxford, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMatched targeted therapies (MTT) given alone or in combination with systemic anti-cancer therapies have delivered proven survival benefit for many people with newly diagnosed cancer. However, there is little evidence of their effectiveness in the recurrent or late-stage setting. With this uncertainty, alongside the perception that late-stage cancers are too genetically heterogenous or too mutationally diverse to benefit from matched targeted therapies, next-generation sequencing (NGS) of tumours in people with refractory cancer remains a low priority. As a result, next-generation sequencing testing of recurrent or late-stage disease is discouraged. We lack evidence to support the utility of next generation sequencing in guiding matched targeted therapies in this setting.

objectivesTo evaluate the benefits and harms of matched targeted therapies in people with advanced cancers in randomised controlled trials. SEARCH

methodsWe searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, ClinicalTrials.gov, and the World Health Organisation International Clinical Trials Registry Platform (WHO-ICTRP) search portal up to 30th October 2024. We also screened reference lists of included studies and also the publications that cited these studies. SELECTION CRITERIA: We included randomised controlled trials (RCTs) that had enroled participants with advanced/refractory solid or haematological cancers who had progressed through at least one line of standard anti-cancer systemic therapy. To be eligible, all participants should have received matched targeted therapy based on next-generation sequencing carried out on their tumour (tumour tissue, blood or bone marrow). DATA COLLECTION AND ANALYSIS: We systematically searched medical databases (e.g. MEDLINE, Embase) and trial registers for randomised controlled trials (RCTs). Outcomes of interest were progression-free survival (PFS), overall survival (OS), overall response rates (ORR), serious (grade 3 or 4) adverse events (AEs) and quality of life (QOL). We used a random-effects model to pool outcomes across studies and compared predefined subgroups using interaction tests. Grading of Recommendations Assessment, Development and Evaluation (GRADE) assessment of certainty was used to evaluate the quality of evidence. MAIN

resultsWe identified a total of 37 studies, out of which 35 studies (including 9819 participants) were included in the meta-analysis. All included studies compared a matched targeted therapy intervention to standard-of-care treatment, non-matched targeted therapies or no treatment (best supportive care): Matched targeted therapy versus standard-of-care treatment Matched targeted therapy (MTT) compared with standard systematic therapy probably reduces the risk of disease progression by 34% (hazard ratio (HR) = 0.66, 95% confidence interval (CI) 0.59 to 0.74; 14 studies, 3848 participants; moderate-certainty evidence). However, MTT might have little to no difference in risk of death (HR = 0.85, 95% CI 0.75 to 0.97; 14 studies, 3848 participants; low-certainty evidence) and may increase overall response rates (low-certainty evidence). There was no clear evidence of a difference in severe (grade 3/4) adverse events between matched targeted therapy and standard-of-care treatment (low-certainty evidence). There was limited evidence of a difference in quality of life between groups (very low-certainty of evidence). Matched targeted therapy in combination with standard-of-care treatment versus standard-of-care treatment alone Matched targeted therapy in combination with standard-of-care treatment compared with standard-of-care treatment alone probably reduces the risk of disease progression by 39% (HR = 0.61, 95% CI 0.53-0.70, 14 studies, 2,637 participants; moderate-certainty evidence) and risk of death by 21% (HR = 0.79, 95% CI 0.70 to 0.89; 11 studies, 2575 participants, moderate-certainty evidence). The combination of MTT and standard-of-care treatment may also increase overall response rates (low-certainty evidence). There was limited evidence of a difference in the incidence of severe adverse events (very low-certainty evidence) and quality of life between the groups (very low-certainty of evidence). Matched targeted therapy versus non-matched targeted therapy Matched targeted therapy compared with non-matched targeted therapy probably reduces the risk of disease progression by 24% (HR = 0.76, 95% CI 0.64 to 0.89; 3 studies, 1568 participants; moderate-certainty evidence) and may reduce the risk of death by 25% (HR = 0.75, 95% CI 0.65 to 0.86, 1307 participants; low-certainty evidence). There was little to no effect on overall response rates between MTT and non-MTT. There was no clear evidence of a difference in overall response rates (low-certainty evidence) and severe adverse events between MTT and non-MTT (low-certainty evidence). None of the studies comparing MTT and non-MTT reported quality of life. Matched targeted therapy versus best supportive care Matched targeted therapy compared with the best supportive care (BSC) i.e. no active treatment probably reduces the risk of disease progression by 63% (HR 0.37, 95% CI 0.28 to 0.50; 4 studies, 858 participants; moderate-certainty evidence). There was no clear evidence of a difference in overall survival between groups (HR = 0.88, 95% CI 0.73 to 1.06, 3 studies, 783 participants; low-certainty evidence). There was no clear evidence of a difference in overall response rates (very low-certainty of evidence) and incidence of severe adverse events (very low-certainty of evidence) between the groups. Quality of life was reported in a single study but did not provide composite scores. Risk of bias The overall risk of bias was judged low for eight studies, unclear for two studies, and the remaining 27 studies were high risk. AUTHORS'

conclusionsMatched targeted therapies guided by next-generation sequencing in people with advanced cancer prolongs the time before cancer progresses compared to standard therapies. However, there is limited evidence to suggest that it prolongs overall survival, improves the quality of life or increases adverse events. Importantly, this review supports equitable access to next-generation sequencing technology for all people with advanced cancer and offers them the opportunity to access genotype-matched targeted therapies.

Indexed as

High-Throughput Nucleotide SequencingMolecular Targeted TherapyNeoplasm Recurrence, LocalNeoplasmsBiasHumansNeoplasm MetastasisProgression-Free SurvivalQuality of LifeRandomized Controlled Trials as Topic

Identifiers

PMID40122129
PMCPMC11930395

What OpenQuestion holds

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Registered trials

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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.