ArticleAmerican journal of cancer research2015
Disparate survival trends in histologic subtypes of metastatic non-small cell lung cancer: a population-based analysis.
Article in American journal of cancer research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed, 20 citations in OpenAlex.
- Trial
- Inhibitory effect and mechanism of hirsuteine on NCI‑H1299 lung cancer cell lines.Oncology letters · 2023Article
- Article
- Observational
- A Proposal to Reflect Survival Difference and Modify the Staging System for Lung Adenocarcinoma and Squamous Cell Carcinoma: Based on the Machine Learning.Frontiers in oncology · 2019Article
- Article
- The results with the addition of metronomic cyclophosphamide to palliative radiotherapy for the treatment of non-small cell lung carcinoma.Annals of translational medicine · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Erlotinib, bevacizumab, and pemetrexed improved survival of metastatic non-small cell lung cancer (mNSCLC) in clinical trials, but their benefits are restricted to non-squamous histology. We studied recent survival trends in mNSCLC subpopulations defined by histology and associated clinical factors correlating with adenocarcinoma or endothelial growth factor receptor mutations. Using the Surveillance, Epidemiology and End Results database, we calculated relative survival at 1 year from diagnosis for mNSCLC cases diagnosed in 2000-2011. Trends by histology, age, sex, race, prevalence of smoking or poverty, expressed as annual percent change (APC) using joinpoint regression, were compared by test of slope parallelism (Ppar ). Among 226,446 cases, 47% had adenocarcinoma, 20% squamous carcinoma, 6% other, and 27% unspecified histology. The proportion of cases designated as adenocarcinoma significantly increased after 2005. One-year survival increased from 23.5% in 2000 to 30.5% in 2010, significantly more for adenocarcinoma (APC, 3.3%) than squamous carcinoma (APC, 2.1%, Ppar =0.0018). For patients with adenocarcinoma, these trends were significantly better for Asians than Whites (Ppar =0.012) and for areas with fewer smokers (Ppar =0.014). Such differences were not observed for squamous carcinoma (Ppar =0.87 and 0.14, respectively). The absolute disparity in one-year survival between adenocarcinoma and squamous carcinoma increased from 1.6% in 2000 to 5.5% in 2010. The disparity between Asians and Whites increased from 5.2% to 13.1%, respectively. These data demonstrate that improvement in survival of mNSCLC since 2000 is now evident on a population scale. The superior increment for patients with adenocarcinoma, particularly among Asians and in communities with fewer smokers, suggests impact of the newly introduced, histology-specific agents, rather than better supportive care alone. Growing disparities between adenocarcinoma and squamous carcinoma highlight the needs to intensify research on treatment for subgroups that did not benefit from recent advances.
Indexed as
Identifiers
26328253PMC4548334W1412922529What OpenQuestion holds
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.