Evidence map›Paper›PMID 27599138›Full record

Observational studyThe Lancet. Oncology2016

30-day mortality after systemic anticancer treatment for breast and lung cancer in England: a population-based, observational study.

Michael Wallington, Emma B Saxon, Martine Bomb, Rebecca Smittenaar, Matthew Wickenden, Sean McPhail, Jem Rashbass, David Chao, John Dewar, Denis Talbot and 4 more

Erratum issuedOpen access · hybridAbstract readObservational Study
In one paragraph

Observational study in The Lancet. Oncology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 66 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
66citing papers in PubMed, 3 pooled it
9.0field-weighted citation impact, top 1% 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.

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

66 citing papers in PubMed, 3 syntheses or guidelines pooled it, 189 citations in OpenAlex.

  1. Pooled it
  2. Guideline
  3. Pooled it
  4. Search for prognostic markers of mortality in inpatients receiving palliative chemotherapy.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
    Observational
  5. Review
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Drug Delivery Systems for Natural Medicines in Cancer Therapy.Current topics in medicinal chemistry · 2025
    Review
  15. Article
  16. Observational
  17. Engineered CD4 T cells for in vivo delivery of therapeutic proteins.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  18. Article
  19. Optimising oncology drug expenditure in Ireland.Irish journal of medical science · 2024
    Review
  20. Observational

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

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors at 8 institutions in 1 country.

Michael WallingtonPublic Health England, London, UK.
Emma B SaxonCancer Research UK, London, UK.
Martine BombPublic Health England, London, UK.
Rebecca SmittenaarCancer Research UK, London, UK.
Matthew WickendenCancer Research UK, London, UK.
Sean McPhailPublic Health England, London, UK.
Jem RashbassPublic Health England, London, UK.
David ChaoDepartment of Oncology, Royal Free Hospital, London, UK.
John DewarDepartment of Oncology, Ninewells Hospital & Medical School, Dundee, UK.
Denis TalbotUniversity of Oxford, Department of Oncology, Oxford, UK.
Michael PeakePublic Health England, London, UK; University of Leicester, Department of Respiratory Medicine, Glenfield Hospital, Leicester, UK.
Timothy PerrenLeeds Institute of Cancer Research and Pathology, St James's University Hospital, Leeds, UK.
Charles WilsonOncology Centre, Addenbrooke's NHS Trust, Cambridge, UK.
David DodwellInstitute of Oncology, St James's Hospital, Leeds, UK. Electronic address: david.dodwell@nhs.net.
Public Health England · GBCancer Research UK Technology · GBSt James's University Hospital · GBAddenbrooke's Hospital · GBGlenfield Hospital · GBNinewells Hospital · GBThe Royal Free Hospital · GBUniversity of Oxford · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

background30-day mortality might be a useful indicator of avoidable harm to patients from systemic anticancer treatments, but data for this indicator are limited. The Systemic Anti-Cancer Therapy (SACT) dataset collated by Public Health England allows the assessment of factors affecting 30-day mortality in a national patient population. The aim of this first study based on the SACT dataset was to establish national 30-day mortality benchmarks for breast and lung cancer patients receiving SACT in England, and to start to identify where patient care could be improved.

methodsIn this population-based study, we included all women with breast cancer and all men and women with lung cancer residing in England, who were 24 years or older and who started a cycle of SACT in 2014 irrespective of the number of previous treatment cycles or programmes, and irrespective of their position within the disease trajectory. We calculated 30-day mortality after the most recent cycle of SACT for those patients. We did logistic regression analyses, adjusting for relevant factors, to examine whether patient, tumour, or treatment-related factors were associated with the risk of 30-day mortality. For each cancer type and intent, we calculated 30-day mortality rates and patient volume at the hospital trust level, and contrasted these in a funnel plot.

findingsBetween Jan 1, and Dec, 31, 2014, we included 23 228 patients with breast cancer and 9634 patients with non-small cell lung cancer (NSCLC) in our regression and trust-level analyses. 30-day mortality increased with age for both patients with breast cancer and patients with NSCLC treated with curative intent, and decreased with age for patients receiving palliative SACT (breast curative: odds ratio [OR] 1·085, 99% CI 1·040-1·132; p<0·0001; NSCLC curative: 1·045, 1·013-1·079; p=0·00033; breast palliative: 0·987, 0·977-0·996; p=0·00034; NSCLC palliative: 0·987, 0·976-0·998; p=0·0015). 30-day mortality was also significantly higher for patients receiving their first reported curative or palliative SACT versus those who received SACT previously (breast palliative: OR 2·326 99% CI 1·634-3·312; p<0·0001; NSCLC curative: 3·371, 1·554-7·316; p<0·0001; NSCLC palliative: 2·667, 2·109-3·373; p<0·0001), and for patients with worse general wellbeing (performance status 2-4) versus those who were generally well (breast curative: 6·057, 1·333-27·513; p=0·0021; breast palliative: 6·241, 4·180-9·319; p<0·0001; NSCLC palliative: 3·384, 2·276-5·032; p<0·0001). We identified trusts with mortality rates in excess of the 95% control limits; this included seven for curative breast cancer, four for palliative breast cancer, five for curative NSCLC, and seven for palliative NSCLC.

interpretationOur findings show that several factors affect the risk of early mortality of breast and lung cancer patients in England and that some groups are at a substantially increased risk of 30-day mortality. The identification of hospitals with significantly higher 30-day mortality rates should promote review of clinical decision making in these hospitals. Furthermore, our results highlight the importance of collecting routine data beyond clinical trials to better understand the factors placing patients at higher risk of 30-day mortality, and ultimately improve clinical decision making. Our insights into the factors affecting risk of 30-day mortality will help treating clinicians and their patients predict the balance of harms and benefits associated with SACT.

fundingPublic Health England.

Indexed as

AgedAntineoplastic Combined Chemotherapy ProtocolsBreast NeoplasmsCarcinoma, Non-Small-Cell LungEnglandFemaleFollow-Up StudiesHumansLung NeoplasmsMaleMiddle AgedNeoplasm StagingPrognosisSurvival RateTime Factors

Identifiers

PMID27599138
PMCPMC5027226
OpenAlexW2507375366

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.