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

Dai, Dongjun; Wang, Yanmei; Hu, Xinyang; Jin, Hongchuan; Wang, Xian

doi:10.7717/peerj.8412

Cited by 5 publications

(5 citation statements)

References 32 publications

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“…The higher the LNR stage, the lower the CSS. Dai et al confirmed similarly that a higher LNR was an independent prognostic factor of CSS based on their retrospective study of 1,386 pancreatic cancer (<45 years) (6). LNR has been also regarded as an independent prognostic factor that is strongly associated with the prognosis of various malignancies such as oral cancer, esophageal cancer, breast cancer and medullary thyroid cancer, etc (45)(46)(47)(48).…”

Section: Discussionmentioning

confidence: 85%

“…Currently, there is no international standard definition of early onset pancreatic cancer. In recent years, early onset pancreatic cancer has been defined in literatures as pancreatic cancer diagnosed before the age of 40, 45, 50 years (5)(6)(7)(8). Considering that researchers often use the criterion of age < 50 years for EOPC in literatures and the American Gastrointestinal Association Institute recommended that screening for pancreatic cancer in high-risk groups should begin at age 50, we have defined EOPC as pancreatic cancer diagnosed at an age of less than 50 years in this study (8)(9)(10)(11)(12)(13).…”

Section: Introductionmentioning

confidence: 99%

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Lymph node ratio is a superior predictor in surgically treated early-onset pancreatic cancer

Zheng

Shi

et al. 2022

Front. Oncol.

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BackgroundThe prognostic performance of four lymph node classifications, the 8th American Joint Committee on Cancer (AJCC) Tumor Node Metastasis (TNM) N stage, lymph node ratio (LNR), log odds of positive lymph nodes (LODDS), and examined lymph nodes (ELN) in early-onset pancreatic cancer (EOPC) remains unclear.MethodsThe Surveillance, Epidemiology, and End Results (SEER) database was searched for patients with EOPC from 2004 to 2016. 1048 patients were randomly divided into training (n = 733) and validation sets (n = 315). The predictive abilities of the four lymph node staging systems were compared using the Akaike information criteria (AIC), receiver operating characteristic area under the curve (AUC), and C-index. Multivariate Cox analysis was performed to identify independent risk factors. A nomogram based on lymph node classification with the strongest predictive ability was established. The nomogram’s precision was verified by the C-index, calibration curves, and AUC. Kaplan–Meier analysis and log-rank tests were used to compare differences in survival at each stage of the nomogram.ResultsCompared with the 8th N stage, LODDS, and ELN, LNR had the highest C-index and AUC and the lowest AIC. Multivariate analysis showed that N stage, LODDS, LNR were independent risk factors associated with cancer specific survival (CSS), but not ELN. In the training set, the AUC values for the 1-, 3-, and 5-year CSS of the nomogram were 0.663, 0.728, and 0.760, respectively and similar results were observed in the validation set. In addition, Kaplan–Meier survival analysis showed that the nomogram was also an important factor in the risk stratification of EOPC.ConclusionWe analyzed the predictive power of the four lymph node staging systems and found that LNR had the strongest predictive ability. Furthermore, the novel nomogram prognostic staging mode based on LNR was also an important factor in the risk stratification of EOPC.

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Section: Discussionmentioning

confidence: 85%

Section: Introductionmentioning

confidence: 99%

Lymph node ratio is a superior predictor in surgically treated early-onset pancreatic cancer

Zheng

Shi

et al. 2022

Front. Oncol.

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“…Our prediction model comprehensively considers all stages of ovarian cancer and suggests three "early" death periods (1, 3, and 6 months) as references. The prognosis of malignant tumors of the digestive tract is mostly related to race, marital status, and tumor location, which has been shown using nomograms [11][12][13][14]. Unlike most human cancers that spread through blood-borne metastasis, traditionally, EOC tumor cells were considered to metastasize directly by migrating through the peritoneal fluid to the omentum of the peritoneal cavity, highlighting its unique metastasis compared with that in lung cancer [15], breast cancer [16] and other cancers.…”

Section: Discussionmentioning

confidence: 99%

Nomogram for predicting postoperative cancer-specific early death in patients with epithelial ovarian cancer based on the SEER database: a large cohort study

Zhang

Zhu

2021

Arch Gynecol Obstet

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Purpose Ovarian cancer is a common gynecological malignant tumor. Poor prognosis is strongly associated with early death, but there is no effective tool to predict this. This study aimed to construct a nomogram for predicting cancer-specific early death in patients with ovarian cancer. Methods We used data from the Surveillance, Epidemiology, and End Results database of patients with ovarian cancer registered from 1988 to 2016. Important independent prognostic factors were determined by univariate and multivariate logistic regression and LASSO Cox regression. Several risk factors were considered in constructing the nomogram. Nomogram discrimination and calibration were evaluated using C-index, internal validation, and receiver operating characteristic (ROC) curves. Results A total of 4769 patients were included. Patients were assigned to the training set (n = 3340; 70%) and validation set (n = 1429; 30%). Based on the training set, eight variables were shown to be significant factors for early death and were incorporated in the nomogram: American Joint Committee on Cancer (AJCC) stage, residual lesion size, chemotherapy, serum CA125 level, tumor size, number of lymph nodes examined, surgery of primary site, and age. The concordance indices and ROC curves showed that the nomogram had better predictive ability than the AJCC staging system and good clinical practicability. Internal validation based on validation set showed good consistency between predicted and observed values for early death. Conclusion Compared with predictions made based on AJCC stage or residual lesion size, the nomogram could provide more robust predictions for early death in patients with ovarian cancer.

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“…Backward stepwise regression based on Bayesian information criteria was conducted to select independent risk factors and avoid overfitting. A competing risk model was then constructed using the Fine and Gray proportional sub-distribution hazards regression model for different types of CMM ( 21 , 22 ). Nomograms were established based on the independent risk factors to estimate the 3-, 5-, and 10-year probability of death resulting from CMM, other cancers, and noncancerous diseases.…”

Section: Methodsmentioning

confidence: 99%

Characteristics, Prognosis, and Competing Risk Nomograms of Cutaneous Malignant Melanoma: Evidence for Pigmentary Disorders

et al. 2022

Front. Oncol.

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PurposeCutaneous malignant melanoma (CMM) always presents as a complex disease process with poor prognosis. The objective of the present study was to explore the influence of solitary or multiple cancers on the prognosis of patients with CMM to better understand the landscape of CMM.MethodsWe reviewed the records of CMM patients between 2004 and 2015 from the Surveillance, Epidemiology, and End Results Program. The cumulative incidence function was used to represent the probabilities of death. A novel causal inference method was leveraged to explore the risk difference to death between different types of CMM, and nomograms were built based on competing risk models.ResultsThe analysis cohort contained 165,043 patients with CMM as the first primary malignancy. Patients with recurrent CMM and multiple primary tumors had similar overall survival status (p = 0.064), while their demographics and cause-specific death demonstrated different characteristics than those of patients with solitary CMM (p < 0.001), whose mean survival times are 75.4 and 77.3 months and 66.2 months, respectively. Causal inference was further applied to unveil the risk difference of solitary and multiple tumors in subgroups, which was significantly different from the total population (p < 0.05), and vulnerable groups with high risk of death were identified. The established competing risk nomograms had a concordance index >0.6 on predicting the probabilities of death of CMM or other cancers individually across types of CMM.ConclusionPatients with different types of CMM had different prognostic characteristics and different risk of cause-specific death. The results of this study are of great significance in identifying the high risk of cause-specific death, enabling targeted intervention in the early period at both the population and individual levels.

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

Cited by 5 publications

References 32 publications

Lymph node ratio is a superior predictor in surgically treated early-onset pancreatic cancer

Lymph node ratio is a superior predictor in surgically treated early-onset pancreatic cancer

Nomogram for predicting postoperative cancer-specific early death in patients with epithelial ovarian cancer based on the SEER database: a large cohort study

Characteristics, Prognosis, and Competing Risk Nomograms of Cutaneous Malignant Melanoma: Evidence for Pigmentary Disorders

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