Overall survival and cancer-specific survival in patients with surgically resected pancreatic head adenocarcinoma: A competing risk nomogram analysis

He, Chaobin; Zhang, Yu; Cai, Zhiyuan; Lin, Xiaojun; Li, Shengping

doi:10.7150/jca.25494

Cited by 50 publications

(59 citation statements)

References 32 publications

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“…To be noted, these studies only included with limited samples. A SEER-based study found the risk of cancer-specific death decreases with age in resectable PDAC patients (He et al, 2018). However, we found the age was not an independent prognostic factor for resectable PDAC patients.…”

Section: Discussioncontrasting

confidence: 68%

Prognostic analysis of very early onset pancreatic cancer: a population-based analysis

Dai

Wang

et al. 2020

PeerJ

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Background. We aimed to use competing risk model to assess whether very early onset pancreatic cancer (VEOPC ) (<45 years) had a worse prognosis than older pancreatic cancer (PC) patients, and to build a competing risk nomogram for predicting the risk of death of VEOPC. Methods. We selected pancreatic adenocarcinoma (PDAC) patients as our cohort from the Surveillance, Epidemiology, and End Results (SEER) database. The impact of cancer specific death was estimated by competing risk analysis. Multivariate Fine-Gray regression for proportional hazards modeling of the subdistribution hazard (SH) model based nomogram was constructed, which was internally validated by discrimination and calibration with 1,000 bootstraps. Results. Our cohort included 1,386 VEOPC patients and 53,940 older patients. We observed that in unresectablePDAC patients, VEOPC had better cancer specific survival (CSS) than each older group (45-59 years, 60-69 years, 70-79 years and >79 years). There was no significant prognostic difference between VEOPC and each older group in resectablePDAC. Our competing nomogram showed well discrimination and calibration by internal validation. Conclusion. For unresectable PDAC patients, VEOPC had better CSS than older patients. Our competing risk nomogram might be an easy-to-use tool for the specific death prediction of VEOPC patients with PDAC.How to cite this article Dai D, Wang Y, Hu X, Jin H, Wang X. 2020. Prognostic analysis of very early onset pancreatic cancer: a population-based analysis. PeerJ 8:e8412 http://doi.

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Section: Discussioncontrasting

confidence: 68%

Prognostic analysis of very early onset pancreatic cancer: a population-based analysis

Dai

Wang

et al. 2020

PeerJ

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“…The following classifications were confirmed: the International Classification of Diseases for Oncology, Third Edition (ICD-O-3), the histology code 8140 and the ICD-O-3 site code C23.9. The exclusion criteria have been described in a previous study (21), which mainly included (1) primary multiple tumors, (2) missing or incomplete information of follow-up, (3) pathologically confirmed not adenocarcinoma, (4) in-hospital or 30-day mortality after surgery, (5) American Society of Anesthesiologists (ASA) Physical Status 3 or above levels (14). Patients from the SEER dataset were randomly selected to serve as the training and internal validation cohorts in a ratio of 3:1.…”

Section: Patientsmentioning

confidence: 99%

“…Clinical and pathological variables, including age, gender, tumor size and grade, TNM stage, follow-up information, and cause of death, were collected and analyzed. Lymph node ratio (LNR) was defined and calculated according to our previous study (21). OS and CSS were defined as the duration from the date of diagnosis to the last follow-up or death due to all causes or GBC, respectively.…”

Section: Data Collectionmentioning

confidence: 99%

Prognostic Model to Predict Cancer-Specific Survival for Patients With Gallbladder Carcinoma After Surgery: A Population-Based Analysis

Cai

Zhang

et al. 2019

Front. Oncol.

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Predicting the prognosis of gallbladder carcinoma (GBC) has always been important for improving survival. The objective of this study was to determine the risk factors of survival for patients with GBC after surgery and to develop predictive nomograms for overall survival (OS) and cancer-specific survival (CSS) using a large population-based cohort. We identified 2,762 patients with primary resectable GBC in the Surveillance, Epidemiology, and End Results (SEER) database for the period of 2004 to 2014 and another 152 patients with GBC after surgery from Sun Yat-sen University Cancer Center (SYSUCC) for the period of 1997 to 2017. The 1-, 2-, and 3-year cancer-specific mortalities were 37.2, 52.9, and 59.9%, while the competing mortalities were 5.8, 7.8, and 9.0%, respectively. Nomograms were developed to estimate OS and CSS, and these were validated by concordance indexes (C-indexes) and evaluated using receiver operating characteristic (ROC) curves. The C-indexes of the nomograms for OS and CSS prediction were 0.704 and 0.732, respectively. In addition, compared with the 8th Tumor-Node-Metastasis staging system, the newly established nomograms displayed higher areas under the ROC curves for OS and PFS prediction. The nomograms are well-validated and could thus aid individual clinical practice.

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“…10 They demonstrated that both primary tumor location and diameter were significantly associated with the risk of synchronous liver metastasis. Tumor size, a powerful and reliable predictor of both distant metastasis and prognosis, 5,27 was found to have an intimate association with the infiltration of the pancreatic cancer cells into the liver. Larger size tumors were more invasive and infiltrated to the peripheral organs or vessels; which may also signify greater tumor burden for patients with PDAC.…”

Section: Discussionmentioning

confidence: 99%

“…3 Distant metastasis is a major indicator of poor prognosis. 4,5 PDAC predisposes the liver to secondary tumors and liver metastasis is the most common form of distant metastasis in these patients. 6 Also, it was shown that patients with liver metastasis had worse prognoses than those with lung metastasis or other distant metastases.…”

Section: Introductionmentioning

confidence: 99%

Development and Validation of a Nomogram to Predict Liver Metastasis in Patients with Pancreatic Ductal Adenocarcinoma: A Large Cohort Study

He¹,

Zhong

Cai³

et al. 2018

SSRN Journal

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These authors contributed equally to this workBackground: Few studies have explored the relationship between clinicopathological factors of patients with pancreatic ductal adenocarcinoma (PDAC) and liver metastasis. The aim of this study was to develop and validate a nomogram to predict liver metastasis in patients with PDAC. Patients and methods: Patients diagnosed with PDAC between 2004 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database were retrospectively collected. The nomogram was established based on a logistic regression model. The precision of the nomogram was evaluated and compared using concordance index (C-index), and the area under receiver operating characteristic curve (AUC). The clinical use of nomogram was evaluated by making use of a decision curve analysis (DCA). Results: A total of 12,644 eligible patients, which were randomly divided into training (n=9,483) and validation cohorts (n=3,161), were included in this study. The nomograms, which were established on the basis of independent predictors, were well calibrated, and demonstrated good discriminative ability, with C-indexes of 0.784 for the training cohort and 0.790 for validation cohort. The values of AUC for training and validation cohort were 0.792 and 0.800, respectively. When other sites of distant metastases were included into this predictive system, the new predictive model demonstrated a better discriminative ability and greater net benefit in predicting liver metastasis in patients with PDAC in both the training and validation cohorts. Conclusion: Nomograms were constructed to predict liver metastasis in patients with PDAC. Validation revealed excellent discrimination and calibration of the nomograms, suggesting that the nomograms were well calibrated and could serve to improve the prediction of the risks of liver metastasis which can be used to guide the management of patients with PDAC.

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Overall survival and cancer-specific survival in patients with surgically resected pancreatic head adenocarcinoma: A competing risk nomogram analysis

Cited by 50 publications

References 32 publications

Prognostic analysis of very early onset pancreatic cancer: a population-based analysis

Prognostic analysis of very early onset pancreatic cancer: a population-based analysis

Prognostic Model to Predict Cancer-Specific Survival for Patients With Gallbladder Carcinoma After Surgery: A Population-Based Analysis

Development and Validation of a Nomogram to Predict Liver Metastasis in Patients with Pancreatic Ductal Adenocarcinoma: A Large Cohort Study

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