Evidence map›Paper›PMID 31673516›Full record

ReviewTranslational lung cancer research2019

Pathologic response after modern radiotherapy for non-small cell lung cancer.

Simon F Roy, Alexander V Louie, Moishe Liberman, Philip Wong, Houda Bahig

Abstract readReview
In one paragraph

Review in Translational lung cancer research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–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. Article
  2. No disease left behind.Oncotarget · 2025
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. SABR-BRIDGE:Frontiers in oncology · 2020
    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

5 authors.

Simon F RoyDepartment of Pathology, University of Montreal, Montreal, QC, Canada.
Alexander V LouieDepartment of Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.
Moishe LibermanDivision of Thoracic Surgery, Department of Surgery, Centre Hospitalier de l'Université de Montréal, Montreal, QC, Canada.
Philip WongDepartment of Radiation Oncology, Centre Hospitalier de l'Université de Montréal, Montreal, QC, Canada.
Houda BahigDepartment of Radiation Oncology, Centre Hospitalier de l'Université de Montréal, Montreal, QC, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In non-small cell lung cancer (NSCLC), pathologic complete response (pCR) following radiotherapy treatment has been shown to be an independent prognostic factor for long-term survival, progression-free survival and locoregional control. PCR is considered a surrogate to therapeutic efficacy, years before survival data are available, and therefore can be used to guide treatment plans and additional therapeutic interventions post-surgical resection. Given the extensive fibrotic changes induced by radiotherapy in the lung, radiological assessment of response can potentially misrepresent pathologic response. The optimal timing for assessment of pathologic response after conventionally fractionated radiotherapy and stereotactic ablative radiotherapy (SABR) remains poorly understood. In this review, we summarize recent literature on pathologic response after radiotherapy for early stage and locally advanced NSCLC, we discuss current controversies around radiobiological considerations, and we present upcoming trials that will provide insight into current knowledge gaps.

Indexed as

non-small cell lung cancer (NSCLC)pathologic complete response (pCR)Stereotactic ablative radiotherapy (SABR)

Identifiers

PMID31673516
PMCPMC6795577

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.