Observational studyBMC palliative care2018
Indicators for early assessment of palliative care in lung cancer patients: a population study using linked health data.
Observational study in BMC palliative care, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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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
4 citing papers in PubMed, 11 citations in OpenAlex.
- Palliative care and psychosocial care in metastatic non-small cell lung cancer: factors affecting utilisation of services and impact on patient survival.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2019Trial
- Combining data to perform population-based observational studies: know your sources. The case of thyroid cancer in Belgium.Archives of public health = Archives belges de sante publique · 2022Article
- Using administrative health data for palliative and end of life care research in Ireland: potential and challenges.HRB open research · 2021Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAnalysing linked, routinely collected data may be useful to identify characteristics of patients with suspected lung cancer who could benefit from early assessment for palliative care. The aim of this study was to compare characteristics of newly diagnosed lung cancer patients dying within 30 days of diagnosis (short term survivors) with those surviving more than 30 days. To identify indicators for early palliative care assessment we distinguished between characteristics available at diagnosis (age, gender, smoking status, marital status, comorbid disease, admission type, tumour stage and histology) from those available post diagnosis. A second aim was to examine the association between receiving any tumour-directed treatment, place of death and survival time.
methodsA retrospective observational population based study comparing lung cancer patients who died within 30 days of diagnosis (short term survivors) with those who survived longer using Chi-squared tests and logistic regression. Incident lung cancer (ICD-03:C34) patients diagnosed 2005-2012 inclusive who died before 01-01-2014 (n = 14,228) were identified from the National Cancer Registry of Ireland linked to death certificate data and acute hospital episode data.
resultsOne in five newly diagnosed lung cancer patients died within 30 days of diagnosis. After adjusting for stage and histology, death within 30 days was higher in patients who were aged 80 years or older (adjusted OR 2.46; 95%CI 2.05-3.96; p < 0.001), patients with emergency admissions at diagnosis (adjusted OR 2.96; 95%CI 2.61-3.37; p < 0.001) and patients with any comorbidities at diagnosis (adjusted OR 1.32 95%CI 1.15-1.52; p < 0.001). Overall, 75% of those who died within 30 days died in hospital compared to 43% of longer term survivors.
conclusionsWe have shown a high proportion of lung cancer patients who die within 30 days of diagnosis are older, have comorbidities and are admitted through the emergency department. These characteristics, available at diagnosis, may be useful prognostic factors to guide decisions on early assessment for palliative care for lung cancer patients. Patients who die shortly after diagnosis are more likely to die in hospital so reporting place of death by survival time may be useful to evaluate interventions to reduce deaths in acute hospitals.
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