PMID- 35730203
OWN - NLM
STAT- MEDLINE
DCOM- 20220623
LR  - 20220815
IS  - 1533-0338 (Electronic)
IS  - 1533-0346 (Print)
IS  - 1533-0338 (Linking)
VI  - 21
DP  - 2022 Jan-Dec
TI  - The Prognosis of Pulmonary Sarcomatoid Carcinoma: Development and Validation of a 
      Nomogram Based on SEER.
PG  - 15330338221109647
LID - 10.1177/15330338221109647 [doi]
LID - 15330338221109647
AB  - Background: The rarity of pulmonary sarcomatoid carcinoma (PSC) and the lack of 
      prospective clinical trials have led to limited knowledge of its clinical 
      characteristics. This study aimed to evaluate the survival and prognostic factors 
      of PSC and to build a nomogram for clinical practice. Methods: Eligible patients 
      diagnosed from 2010 to 2016 were selected from the Surveillance, Epidemiology, 
      and End Results (SEER) database. We compared the clinical characteristics and 
      survival times of PSC patients with those of lung adenocarcinoma (LADC) and lung 
      squamous cell carcinoma (LSCC) patients. We also used univariate and 
      multivariable Cox regression to estimate mortality hazard ratios among patients 
      with PSC, while a visual nomogram was established to judge the prognosis. 
      Discrimination, calibration, clinical utility, and reproducibility were validated 
      by Harrell's concordance index (C-index), the area under the curve (AUC), 
      calibration curves, and decision curve analysis (DCA). Results: A total of 400 
      PSC patients (0.42%) were identified in the SEER database, whereas 58 474 and 
      33 637 patients were diagnosed with LADC and LSCC, respectively. Age, T stage, 
      grade, surgery, and radiation were shown to be significant prognostic factors in 
      the Cox regression analyses and were included in the nomogram as predictors. The 
      C-index of the nomogram in the validation set was 0.759. The AUC also 
      demonstrated the good performance of the nomogram, and DCA demonstrated its good 
      clinical applicability. Conclusion: We established a novel nomogram to predict 
      the prognosis of PSC, which can help clinicians make tailored decisions and 
      adjust follow-up management strategies, and can provide accurate and 
      individualized survival predictions.
FAU - Xie, Yuanyuan
AU  - Xie Y
AD  - 89657The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, P.R. 
      China.
FAU - Lin, Zhiyong
AU  - Lin Z
AD  - The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical 
      University, Wenzhou, P.R. China.
FAU - Shi, Haochun
AU  - Shi H
AD  - The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical 
      University, The Second School of Medicine, 26453Wenzhou Medical University, 
      Wenzhou, P.R. China.
FAU - Sun, Xiang
AU  - Sun X
AD  - 89657The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, P.R. 
      China.
FAU - Gu, Lizhong
AU  - Gu L
AUID- ORCID: 0000-0002-9481-1562
AD  - The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical 
      University, Wenzhou, P.R. China.
LA  - eng
PT  - Journal Article
PL  - United States
TA  - Technol Cancer Res Treat
JT  - Technology in cancer research & treatment
JID - 101140941
SB  - IM
MH  - *Carcinoma, Squamous Cell/pathology
MH  - Humans
MH  - Lung/pathology
MH  - *Nomograms
MH  - Prognosis
MH  - Reproducibility of Results
MH  - SEER Program
PMC - PMC9228655
OTO - NOTNLM
OT  - Pulmonary sarcomatoid carcinoma
OT  - SEER
OT  - nomogram
OT  - overall survival
OT  - prognosis
COIS- Declaration of Conflicting Interests: The author(s) declared no potential 
      conflicts of interest with respect to the research, authorship, and/or 
      publication of this article.
EDAT- 2022/06/23 06:00
MHDA- 2022/06/24 06:00
PMCR- 2022/06/22
CRDT- 2022/06/22 03:26
PHST- 2022/06/22 03:26 [entrez]
PHST- 2022/06/23 06:00 [pubmed]
PHST- 2022/06/24 06:00 [medline]
PHST- 2022/06/22 00:00 [pmc-release]
AID - 10.1177_15330338221109647 [pii]
AID - 10.1177/15330338221109647 [doi]
PST - ppublish
SO  - Technol Cancer Res Treat. 2022 Jan-Dec;21:15330338221109647. doi: 
      10.1177/15330338221109647.