Nomograms to predict overall survival and cancer-specific survival in patients with adrenocortical carcinoma

Li, Yan; Bian, Xue; Ouyang, Junyu; Wei, Shuyi; He, Meizhi; Luo, Zelong

doi:10.2147/cmar.s187169

Cited by 19 publications

(23 citation statements)

References 33 publications

(47 reference statements)

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“…No correlation was found with patients' age, sex, ENSAT stage, pathological tumor size or lymph node status, surgical margins status, Weiss classification, steroid secretion. There was a trend toward association with a younger patients' age reported as a good-prognosis feature 58 and with higher MKI67 expression known as a poorprognosis feature. 59 To our knowledge, only one study in literature characterized PDL1 expression in ACC and searched for clinicopathological correlations.…”

Section: Discussionmentioning

confidence: 90%

PDL1 expression is associated with longer postoperative, survival in adrenocortical carcinoma

et al. 2019

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Adrenocortical carcinomas (ACCs) are heterogeneous cancers associated with a very poor prognosis. The improvement of prognostic tools and systemic therapy are urgently needed. Targeting the immune system using checkpoint inhibitors such as PD1/PDL1 inhibitors is an attractive novel therapeutic strategy for poor-prognosis tumors. Multiple clinical trials are ongoing, including in advanced ACC. However, PDL1 expression has been studied in ACC in only one heterogeneous series of 28 clinical samples. Here, we have retrospectively analyzed PDL1 mRNA expression in 146 clinical ACC samples and searched for correlations between expression and biological and clinicopathological data, including post-operative disease-free survival (DFS). PDL1 mRNA expression was heterogeneous across samples. "PDL1-high" tumors were not associated with the classical prognostic variables but were associated with longer DFS in both uni-and multivariate analyses. High PDL1 mRNA expression was associated with biological signs of the cytotoxic local immune response. Supervised analysis between "PDL1-high" and "PDL1-low" tumors identified a robust 370-gene signature whose ontology analysis suggested the existence in "PDL1-high" tumors of a cytotoxic T-cell response, however, associated with some degree of T-cell exhaustion. In conclusion, PDL1 mRNA expression refines the prognostication in ACC and high expression is associated with longer DFS. Clinical validation at the protein level and functional validation are required to fully understand the role of PDL1 in ACC. Reactivation of dormant tumor-infiltrating lymphocytes by PDL1-inhibitors could represent a promising strategy in "PDL1-high" ACCs, supporting the ongoing clinical trials.

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Section: Discussionmentioning

confidence: 90%

PDL1 expression is associated with longer postoperative, survival in adrenocortical carcinoma

et al. 2019

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“…As far as we know, research that specifically focus on risk factors for outcomes of pediatric NB located at adrenal has not been reported [27]. In addition, maybe due to the low incidence of ACC, only a few prognostic prediction models have been reported for ACC patients previously [24,28,29]. However, further studies are warranted due to limitations.…”

Section: Discussionmentioning

confidence: 99%

“…For example, cases with insufficient data were not excluded for analysis, and "unknown" was treated as a category in some variables [24,28]; age at diagnosis was used as a categorical variable rather than continuous variable [24]; a useless variable "year of diagnosis" was even identified as an independent risk factor for survival and incorporated in the final model [24]. More importantly, these models were developed in ACC patients of all ages, which neglected that the prognosis predictors of ACC are different between pediatric and adult patients [24,28,29]. Due to the deficient number of cases, it is hard to develop reliable models for the rare tumors, like the pediatric ACC.…”

Section: Discussionmentioning

confidence: 99%

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Nomograms for the Prediction of Survival for Patients with Pediatric Adrenal Cancer after Surgery

et al. 2020

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Purpose: To develop and validate a nomogram to postoperatively evaluate overall survival (OS) and cancer-specific survival (CSS) in patients with pediatric adrenal cancer. Methods: In total, 847 eligible patients diagnosed between 1988 and 2015 form the Surveillance Epidemiology, and End Results (SEER) database were enrolled in this study according to the specified inclusion and exclusion criteria. They were divided into a training set (n = 661) and a validation set (n = 186). Multivariate Cox proportional hazards regression algorithm was used to identify the independent predictors of OS and CSS in the training set, and develop the predicting models, which were presented two nomograms. The performance of the nomograms (discrimination, calibration and clinical usefulness) was assessed in the training set and validated in the validation set. Results: Based on the multivariate Cox proportional hazards regression analyses, three independent predictors including age at diagnosis, tumor size and M stage were identified for both OS and CSS. Then, an OS nomogram and a CSS nomogram were developed incorporating these three predictors, respectively. The OS nomogram showed good calibration and discrimination in the training set (C-index [95% CI], 0.744 [0.711-0.777]), which was confirmed in the validation set (C-index [95% CI], 0.746 [0.656-0.836]). Favorable calibration and discrimination of the CSS nomogram were also observed in the training set (C-index [95% CI], 0.749 [0.715-0.783]) and validation set (C-index [95% CI], 0.789 [0.710-0.868]). Moreover, the nomograms successfully distinguished patients with high risk of all-cause and cancer-specific mortality in all patients and in the stratified analyses. Decision curve analysis demonstrated the usefulness of the nomograms. Conclusion: The presented nomograms show favorable predictive accuracy for OS and CSS in patients with pediatric adrenal cancer after surgery. Further validation is warranted prior to clinical implementation.

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“…A clinical prediction model can inform patients and their physicians of the patients’ probability of a specified outcome and help them with associated decision making. Previous prediction models were developed for specific subgroups of ACC patients: recurrence-free (RFS) and overall survival (OS) after curative resection of ACC [ 15 ], OS of ACC patients after surgery [ 16 ], or lacking essential (histologic) predictors in the model development [ 17 , 18 , 19 ]. Therefore, the aim of this study is to develop and internally validate a multivariable, generally applicable clinical prediction model for ACC-specific mortality.…”

Section: Introductionmentioning

confidence: 99%

Development and Internal Validation of a Multivariable Prediction Model for Adrenocortical-Carcinoma-Specific Mortality

Ettaieb

Kuijk

Wit-Pastoors

et al. 2020

Cancers

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Adrenocortical carcinoma (ACC) has an incidence of about 1.0 per million per year. In general, survival of patients with ACC is limited. Predicting survival outcome at time of diagnosis is a clinical challenge. The aim of this study was to develop and internally validate a clinical prediction model for ACC-specific mortality. Data for this retrospective cohort study were obtained from the nine centers of the Dutch Adrenal Network (DAN). Patients who presented with ACC between 1 January 2004 and 31 October 2013 were included. We used multivariable Cox proportional hazards regression to compute the coefficients for the prediction model. Backward stepwise elimination was performed to derive a more parsimonious model. The performance of the initial prediction model was quantified by measures of model fit, discriminative ability, and calibration. We undertook an internal validation step to counteract the possible overfitting of our model. A total of 160 patients were included in the cohort. The median survival time was 35 months, and interquartile range (IQR) 50.7 months. The multivariable modeling yielded a prediction model that included age, modified European Network for the Study of Adrenal Tumors (mENSAT) stage, and radical resection. The c-statistic was 0.77 (95% Confidence Interval: 0.72, 0.81), indicating good predictive performance. We developed a clinical prediction model for ACC-specific mortality. ACC mortality can be estimated using a relatively simple clinical prediction model with good discriminative ability and calibration.

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Nomograms to predict overall survival and cancer-specific survival in patients with adrenocortical carcinoma

Cited by 19 publications

References 33 publications

PDL1 expression is associated with longer postoperative, survival in adrenocortical carcinoma

PDL1 expression is associated with longer postoperative, survival in adrenocortical carcinoma

Nomograms for the Prediction of Survival for Patients with Pediatric Adrenal Cancer after Surgery

Development and Internal Validation of a Multivariable Prediction Model for Adrenocortical-Carcinoma-Specific Mortality

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