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Mendeley readers
| Title |
Nomograms predict long-term survival for patients with periampullary adenocarcinoma after pancreatoduodenectomy
|
|---|---|
| Published in |
BMC Cancer, March 2018
|
| DOI | 10.1186/s12885-018-4240-x |
| Pubmed ID | |
| Authors |
Chaobin He, Yize Mao, Jun Wang, Fangting Duan, Xiaojun Lin, Shengping Li |
| Abstract |
The prognosis of patients with periampullary adenocarcinoma after pancreatoduodenectomy is diverse and not yet clearly illustrated. The aim of this study was to develop a nomogram to predict individual risk of overall survival (OS) and progression-free survival (PFS) in patients with periampullary adenocarcinoma after pancreatoduodenectomy. A total of 205 patients with periampullary adenocarcinoma after pancreatoduodenectomy were retrospectively included. OS and PFS were evaluated by the Kaplan-Meier method. Two nomograms for predicting OS and PFS were established, and the predictive accuracy was measured by the concordance index (Cindex) and calibration plots. Lymph node ratio (LNR), carbohydrate antigen 19-9 (CA19-9) and anatomical location were incorporated into the nomogram for OS prediction and LNR, CA19-9; anatomical location and tumor differentiation were incorporated into the nomogram for PFS prediction. All calibration plots for the probability of OS and PFS fit well. The Cindexes of the nomograms for OS and PFS prediction were 0.678 and 0.68, respectively. The OS and PFS survival times were stratified significantly using the nomogram-predicted survival probabilities. The present nomograms for OS and PFS prediction can provide valuable information for tailored decision-making for patients with periampullary adenocarcinoma after pancreatoduodenectomy. |
Mendeley readers
The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 23 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 3 | 13% |
| Student > Ph. D. Student | 3 | 13% |
| Professor | 2 | 9% |
| Student > Doctoral Student | 2 | 9% |
| Researcher | 2 | 9% |
| Other | 2 | 9% |
| Unknown | 9 | 39% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 9 | 39% |
| Nursing and Health Professions | 1 | 4% |
| Immunology and Microbiology | 1 | 4% |
| Computer Science | 1 | 4% |
| Unknown | 11 | 48% |