External validation of a nomogram predicting mortality in patients with adrenocortical carcinoma

Validated predictive model for treatment and prognosis of adrenocortical carcinoma

BACKGROUND

Adrenocortical carcinoma has a poor prognosis and multiple clinical, pathological, and treatment variables. Currently, we lack a prognostic and treatment calculator to determine the survival and efficacy of adjuvant chemoradiation. We aimed to validate a calculator to assess prognosis and treatment.

METHODS

We searched the National Cancer Database to identify patients with adrenocortical carcinoma surgically treated from 2004 to 2020 and randomly allocated them into a training (80%) or validation set (20%). We analyzed the variables of age; sex; Charlson Comorbidity Index; insurance status; tumor size; pathologic tumor, node, and metastasis categories; surgical margins; and use of chemotherapy and radiation therapy. We used Cox regression prediction models and bootstrap coefficients to generate a mathematical model to predict 5- and 10-year overall survival. After using the area under the curve analysis to assess the model's performance, we compared overall survival in the training and validation sets.

RESULTS

Multivariable analysis of the 3,480 patients included in the study revealed that all variables were significant except sex (P < .05) and incorporated into a mathematical model. The area under the curve for 5- and 10-year overall survival was 0.68 and 0.70, respectively, for the training set and 0.70 and 0.72, respectively, for the validation set. For the bootstrap coefficients, the 5- and 10-year overall survival was 6.4% and 4.1%, respectively, above the observed mean.

CONCLUSION

Our model predicts the overall survival of patients with adrenocortical carcinoma based on clinical, pathologic, and treatment variables and can assist in individualizing treatment.

S-GRAS score performs better than a model from SEER for patients with adrenocortical carcinoma

PURPOSE

To externally validate the performance of the S-GRAS score and a model from the Surveillance, Epidemiology, and End Results (SEER) database in a Chinese cohort of patients with adrenocortical carcinoma (ACC).

METHODS

We first developed a model using data from the SEER database, after which we retrospectively reviewed 51 ACC patients hospitalized between 2013 and 2018, and we finally validated the model and S-GRAS score in this Chinese cohort.

RESULTS

Patient age at diagnosis, tumor size, TNM stage, and radiotherapy were used to construct the model, and the Harrell's C-index of the model in the training set was 0.725 (95% CI: 0.682-0.768). However, the 5-year area under the curve (AUC) of the model in the validation cohort was 0.598 (95% CI: 0.487-0.708). The 5-year AUC of the ENSAT stage was 0.640 (95% CI: 0.543-0.737), but the Kaplan-Meier curves of stages I and II overlapped in the validation cohort. The resection status (P = 0.066), age (P=0.68), Ki67 (P = 0.69), and symptoms (P = 0.66) did not have a significant impact on cancer-specific survival in the validation cohort. In contrast, the S-GRAS score group showed better discrimination (5-year AUC: 0.683, 95% CI: 0.602-0.764) than the SEER model or the ENSAT stage.

CONCLUSION

The SEER model showed favorable discrimination and calibration ability in the training set, but it failed to distinguish patients with various prognoses in our institution. In contrast, the S-GRAS score could effectively stratify patients with different outcomes.

Nomograms for Individualized Evaluation of Prognosis in Adrenocortical Carcinomas for the Elderly: A Population-Based Analysis

BACKGROUND

Adrenocortical carcinoma (ACC) is extremely rare in elderly patients. Thus, this study aimed to identify the incidence rate and develop nomogram models for predicting survival in elderly ACC patients.

METHODS

Data of ACC patients aged >60 years from 1975 to 2016 were obtained from the Surveillance, Epidemiology, and End Results dataset. The national incidence rate was estimated, and survival was subjected to Kaplan-Meier analysis. A multivariate Cox regression model was used to identify predictors of survival. Nomograms were generated to predict survival, calibrated and internally validated.

RESULTS

We identified 583 cases. Univariate analysis showed that patients with younger age (≤67 years), female sex, lower tumor grade, surgical treatment performed, and earlier European Network for the Study of Adrenal Tumors (ENSAT) stage had a better survival (P < 0.05). In the Cox regression analysis, no surgery performed (hazard ratio [HR]: 3.544, 95% CI: 1.142-10.995, P = 0.029 for overall survival [OS]; HR: 3.230, 95% CI: 1.040-10.034, P = 0.043 for disease-specific survival [DSS]) and advanced ENSAT stage (HR: 3.328, 95% CI: 1.628-6.801, P = 0.001 for OS; HR: 3.701, 95% CI: 1.682-8.141, P = 0.001 for DSS) were associated with worse outcomes. Age, sex, histologic grade, surgical resection, radiotherapy, and ENSAT stage were included in the nomograms, with a C-index of 0.692 for OS and 0.694 for DSS, demonstrating a good accuracy in predicting survival.

CONCLUSIONS

This study is the largest review of ACC in elderly patients. We present nomograms to predict survival in elderly ACC patients using clinicopathologic data, which could aid in accurate clinical decision-making.

Comparative performances of nomograms and conditional survival after resection of adrenocortical cancer

Background

Adrenocortical carcinomas (ACCs) carry a poor prognosis. This study assessed the comparative performance of existing nomograms in estimating the likelihood of survival, along with the value of conditional survival estimation for patients who had already survived for a given length of time after surgery.

Methods

This was an observational study based on a prospectively developed departmental database that recorded details of patients operated for ACC in a UK tertiary referral centre.

Results

Of 74 patients with ACC managed between 2001 and 2020, data were analysed for 62 patients (32 women and 30 men, mean(s.d.) age 51(17) years) who had primary surgical treatment in this unit. Laparoscopic (9) or open adrenalectomies (53) were performed alone or in association with a multivisceral resection (27). Most of the tumours were left-sided (40) and 18 were cortisol-secreting.

Overall median survival was 33 months, with 1-, 3- and 5-year survival rates of 79, 49, and 41 per cent respectively. Age over 55 years, higher European Network for Study of Adrenal Tumours stage, and cortisol secretion were associated with poorer survival in univariable analyses. Four published nomograms suggested widely variable outcomes that did not correlate with observed overall survival at 1, 3 or 5 years after operation. The 3-year conditional survival at 2 years (probability of surviving to postoperative year 5) was 65 per cent, compared with a 5-year actuarial survival rate of 41 per cent calculated from the time of surgery.

Conclusion

Survival of patients with ACC correlates with clinical parameters but not with published nomograms. Conditional survival might provide a more accurate estimate of survival for patients who have already survived for a certain amount of time after resection.

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

Simple Summary

Adrenocortical carcinoma is a rare and aggressive cancer. Great variability in clinical course is observed, ranging from patients with extreme long survival to aggressive tumors with prompt fatal outcome. This heterogeneity in survival makes it complicated to tailor treatment strategies for an individual patient. Therefore we sought to identify prognostic factors associated with ACC specific mortality. We analyzed the data of 160 ACC patients and developed a clinical prediction model including age, modified European Network for the Study of Adrenal Tumors (mENSAT) stage, and radical resection. This easy-to-use prediction model for ACC-specific mortality has the potential to guide clinical decision making if externally validated.

Abstract

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.

Development and validation of prognostic nomograms in patients with adrenocortical carcinoma: a population-based study

BACKGROUND

Predicting the prognosis of patients with adrenocortical carcinoma (ACC) is difficult, due to its unpredictable behavior. The aim of this study is to develop and validate a nomogram to predict survival outcomes in patients with ACC.

METHODS

Nomograms were established using the data collected from the Surveillance, Epidemiology, and End Results (SEER) database. Based on univariate and multivariate Cox regression analyses, we identified independent risk factors for overall survival (OS) and cancer-specific survival (CSS). Concordance indexes (c-indexes), the area under the receiver operating characteristics curve (AUC) and calibration curve were used to evaluate predictive performance of these models. The clinical use of nomogram was measured by decision curve analysis (DCA) and clinical impact curves.

RESULTS

A total of 855 eligible patients, randomly divided into training (n = 600) and validation cohorts (n = 255), were included in this study. Based on the independent predictors, the nomograms were established and demonstrated good discriminative abilities, with C-indexes for OS and CSS were 0.762 and 0.765 in training cohorts and 0.738 and 0.758 in validation cohorts, respectively. The AUC and calibration plots also demonstrated a good performance for both nomograms. DCA indicated that the two nomograms provide clinical net benefits.

CONCLUSION

We unveiled the prognostic factors of ACC and developed novel nomograms that predict OS and CSS more accurately and comprehensively, which can help clinicians improve individual treatment, making proper clinical decisions and adjusting follow-up management strategies.

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

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.

A nomogram for individualized estimation of survival among adult patients with adrenocortical carcinoma after surgery: a retrospective analysis and multicenter validation study

Background

Clinical outcome of adrenocortical carcinoma (ACC) varies because of its heterogeneous nature and reliable prognostic prediction model for adult ACC patients is limited. The objective of this study was to develop and externally validate a nomogram for overall survival (OS) prediction in adult patients with ACC after surgery.

Methods

Based on the data from the Surveillance Epidemiology, and End Results (SEER) database, adults patients diagnosed with ACC between January 1988 and December 2015 were identified and classified into a training set, comprised of 404 patients diagnosed between January 2007 and December 2015, and an internal validation set, comprised of 318 patients diagnosed between January 1988 and December 2006. The endpoint of this study was OS. The nomogram was developed using a multivariate Cox proportional hazards regression algorithm in the training set and its performance was evaluated in terms of its discriminative ability, calibration, and clinical usefulness. The nomogram was then validated using the internal SEER validation, also externally validated using the Cancer Genome Atlas set (TCGA, 82 patients diagnosed between 1998 and 2012) and a Chinese multicenter cohort dataset (82 patients diagnosed between December 2002 and May 2018), respectively.

Results

Age at diagnosis, T stage, N stage, and M stage were identified as independent predictors for OS. A nomogram incorporating these four predictors was constructed using the training set and demonstrated good calibration and discrimination (C-index 95% confidence interval [CI], 0.715 [0.679–0.751]), which was validated in the internal validation set (C-index [95% CI], 0.672 [0.637–0.707]), the TCGA set (C-index [95% CI], 0.810 [0.732–0.888]) and the Chinese multicenter set (C-index [95% CI], 0.726 [0.633–0.819]), respectively. Encouragingly, the nomogram was able to successfully distinguished patients with a high-risk of mortality in all enrolled patients and in the subgroup analyses. Decision curve analysis indicated that the nomogram was clinically useful and applicable.

Conclusions

The study presents a nomogram that incorporates clinicopathological predictors, which can accurately predict the OS of adult ACC patients after surgery. This model and the corresponding risk classification system have the potential to guide therapy decisions after surgery.

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

Purpose

To develop nomogram models to predict individualized estimates of overall survival (OS) and cancer-specific survival (CSS) in patients with adrenocortical carcinoma (ACC).

Patients and methods

A total of 751 patients with ACC were identified within the Surveillance Epidemiology, and End Results (SEER) database between 1973 and 2015. The predictors comprised marital status, sex, age at diagnosis, year of diagnosis, laterality, histologic grade, ethnicity, historic stage, radiation therapy, chemotherapy, and surgery of primary site. Based on the results of the multivariate logistic regression analyses, the nomogram models were used for predicting OS and CSS in patients with ACC. The nomograms were tested using concordance index (C-index) and calibration curves.

Results

In univariate and multivariate analyses of OS, OS was significantly associated with age at diagnosis, year of diagnosis, histologic grade, historic stage, and chemotherapy. In univariate and multivariate analyses of CSS, age at diagnosis, year of diagnosis, historic stage, and chemotherapy were the independent risk factors with CSS. These characteristics were included in the nomograms predicting OS and CSS. The nomograms demonstrated good accuracy in predicting OS and CSS, with the C-index of 0.677 and 0.672.

Conclusion

These clinically useful tools predicted OS and CSS in patients with ACC using readily available clinicopathologic factors and could aid individualized clinical decision making.

European Society of Endocrinology Clinical Practice Guidelines on the management of adrenocortical carcinoma in adults, in collaboration with the European Network for the Study of Adrenal Tumors

Adrenocortical carcinoma (ACC) is a rare and in most cases steroid hormone-producing tumor with variable prognosis. The purpose of these guidelines is to provide clinicians with best possible evidence-based recommendations for clinical management of patients with ACC based on the GRADE (Grading of Recommendations Assessment, Development and Evaluation) system. We predefined four main clinical questions, which we judged as particularly important for the management of ACC patients and performed systematic literature searches: (A) What is needed to diagnose an ACC by histopathology? (B) Which are the best prognostic markers in ACC? (C) Is adjuvant therapy able to prevent recurrent disease or reduce mortality after radical resection? (D) What is the best treatment option for macroscopically incompletely resected, recurrent or metastatic disease? Other relevant questions were discussed within the group. Selected Recommendations: (i) We recommend that all patients with suspected and proven ACC are discussed in a multidisciplinary expert team meeting. (ii) We recommend that every patient with (suspected) ACC should undergo careful clinical assessment, detailed endocrine work-up to identify autonomous hormone excess and adrenal-focused imaging. (iii) We recommend that adrenal surgery for (suspected) ACC should be performed only by surgeons experienced in adrenal and oncological surgery aiming at a complete en bloc resection (including resection of oligo-metastatic disease). (iv) We suggest that all suspected ACC should be reviewed by an expert adrenal pathologist using the Weiss score and providing Ki67 index. (v) We suggest adjuvant mitotane treatment in patients after radical surgery that have a perceived high risk of recurrence (ENSAT stage III, or R1 resection, or Ki67 >10%). (vi) For advanced ACC not amenable to complete surgical resection, local therapeutic measures (e.g. radiation therapy, radiofrequency ablation, chemoembolization) are of particular value. However, we suggest against the routine use of adrenal surgery in case of widespread metastatic disease. In these patients, we recommend either mitotane monotherapy or mitotane, etoposide, doxorubicin and cisplatin depending on prognostic parameters. In selected patients with a good response, surgery may be subsequently considered. (vii) In patients with recurrent disease and a disease-free interval of at least 12 months, in whom a complete resection/ablation seems feasible, we recommend surgery or alternatively other local therapies. Furthermore, we offer detailed recommendations about the management of mitotane treatment and other supportive therapies. Finally, we suggest directions for future research.

MANAGEMENT OF ENDOCRINE DISEASE: Adrenocortical carcinoma: differentiating the good from the poor prognosis tumors

Adrenocortical carcinoma (ACC) is a rare malignancy with a poor prognosis, the five-years overall survival being below 40%. However, there is great variability of outcomes and we have now a better view of the heterogeneity of tumor aggressiveness. The extent of the disease at the time of diagnosis, best assayed by the European Network for the Study of Adrenal Tumors (ENSAT) Staging Score, is a major determinant of survival. The tumor grade, including the mitotic count and the Ki67 proliferation index, also appears as a strong prognostic factor. The assessment of tumor grade, even by expert pathologists, still suffers from inter-observer reproducibility. The emergence of genomics in the last decade has revolutionized the knowledge of molecular biology and genetics of cancers. In ACC, genomic approaches - including pan-genomic studies of gene expression (transcriptome), recurrent mutations (exome or whole-genome sequencing), chromosome alterations, DNA methylation (methylome), miRNA expression (miRnome) - converge in a new classification of ACC, characterized by distinct molecular profiles and very different outcomes. Targeted measurements of a few discriminant molecular alterations have been developed in the perspective of clinical routine, and thus, may help defining therapeutic strategy. By individualizing patients' prognosis and tumor biology, these recent progresses appear as an important step forward towards precision medicine.

Curative Surgical Resection of Adrenocortical Carcinoma: Determining Long-term Outcome Based on Conditional Disease-free Probability

OBJECTIVE

To evaluate conditional disease-free survival (CDFS) for patients who underwent curative intent surgery for adrenocortical carcinoma (ACC).

BACKGROUND

ACC is a rare but aggressive tumor. Survival estimates are usually reported as survival from the time of surgery. CDFS estimates may be more clinically relevant by accounting for the changing likelihood of disease-free survival (DFS) according to time elapsed after surgery.

METHODS

CDFS was assessed using a multi-institutional cohort of patients. Cox proportional hazards models were used to evaluate factors associated with DFS. Three-year CDFS (CDFS3) estimates at "x" year after surgery were calculated as follows: CDFS3 = DFS(x+3)/DFS(x).

RESULTS

One hundred ninety-two patients were included in the study cohort; median patient age was 52 years. On presentation, 36% of patients had a functional tumor and median size was 11.5 cm. Most patients underwent R0 resection (75%) and 9% had N1 disease. Overall 1-, 3-, and 5-year DFS was 59%, 34%, and 22%, respectively. Using CDFS estimates, the probability of remaining disease free for an additional 3 years given that the patient had survived without disease at 1, 3, and 5 years, was 43%, 53%, and 70%, respectively. Patients with less favorable prognosis at baseline demonstrated the greatest increase in CDFS3 over time (eg, capsular invasion: 28%-88%, Δ60% vs no capsular invasion: 51%-87%, Δ36%).

CONCLUSIONS

DFS estimates for patients with ACC improved dramatically over time, in particular among patients with initial worse prognoses. CDFS estimates may provide more clinically relevant information about the changing likelihood of DFS over time.

Nomograms to Predict Recurrence-Free and Overall Survival After Curative Resection of Adrenocortical Carcinoma

IMPORTANCE

Adrenocortical carcinoma (ACC) is a rare but aggressive endocrine tumor, and the prognostic factors associated with long-term outcomes after surgical resection remain poorly defined.

OBJECTIVES

To define clinicopathological variables associated with recurrence-free survival (RFS) and overall survival (OS) after curative surgical resection of ACC and to propose nomograms for individual risk prediction.

DESIGN, SETTING, AND PARTICIPANTS

Nomograms to predict RFS and OS after surgical resection of ACC were proposed using a multi-institutional cohort of patients who underwent curative-intent surgery for ACC at 13 major institutions in the United States between March 17, 1994, and December 22, 2014. The dates of our study analysis were April 15, 2015, to May 12, 2015.

MAIN OUTCOMES AND MEASURES

The discriminative ability and calibration of the nomograms to predict RFS and OS were tested using C statistics, calibration plots, and Kaplan-Meier curves.

RESULTS

In total, 148 patients who underwent surgery for ACC were included in the study. The median patient age was 53 years, and 65.5% (97 of 148) of the patients were female. One-third of the patients (35.1% [52 of 148]) had a functional tumor, and the median tumor size was 11.2 cm. Most patients (77.7% [115 of 148]) underwent R0 resection, and 8.8% (13 of 148) of the patients had N1 disease. Using backward stepwise selection of clinically important variables with the Akaike information criterion, the following variables were incorporated in the prediction of RFS: tumor size of at least 12 cm (hazard ratio [HR], 3.00; 95% CI, 1.63-5.70; P < .001), positive nodal status (HR, 4.78; 95% CI, 1.47-15.50; P = .01), stage III/IV (HR, 1.80; 95% CI, 0.95-3.39; P = .07), cortisol-secreting tumor (HR, 2.38; 95% CI, 1.27-4.48; P = .01), and capsular invasion (HR, 1.96; 95% CI, 1.02-3.74; P = .04). Factors selected as predicting OS were tumor size of at least 12 cm (HR, 1.78; 95% CI, 1.00-3.17; P = .05), positive nodal status (HR, 5.89; 95% CI, 2.05-16.87; P = .001), and R1 margin (HR, 2.83; 95% CI, 1.51-5.30; P = .001). The discriminative ability and calibration of the nomograms revealed good predictive ability as indicated by the C statistics (0.74 for RFS and 0.70 for OS).

CONCLUSIONS AND RELEVANCE

Independent predictors of survival and recurrence risk after curative-intent surgery for ACC were selected to create nomograms predicting RFS and OS. The nomograms were able to stratify patients into prognostic groups and performed well on internal validation.

Diagnosis, treatment and outcome of adrenocortical cancer

BACKGROUND

Adrenocortical cancer (ACC) is a rare disease with a dismal prognosis. The majority of patients are diagnosed with advanced disease and raise difficult management challenges.

METHODS

All references identified in PubMed, published between 2004 and 2014, using the keywords 'adrenocortical cancer' or 'adrenal surgery' or both, were uploaded into a database. The database was interrogated using keywords specific for each field studied.

RESULTS

In all, 2049 publications were identified. There is ongoing debate about the feasibility and oncological outcomes of laparoscopic adrenalectomy for small ACCs, and data derived from institutional case series have failed to provide an evidence level above expert opinion. The use of mitotane (1-(2-chlorophenyl)-1-(4-chlorophenyl)-2,2-dichloroethane) in combination with chemotherapy in the treatment of metastatic disease has been assessed in an international randomized trial (FIRM-ACT trial) involving patients with ACC. Based on this trial, mitotane plus etoposide, doxorubicin and cisplatin is now the established first-line cytotoxic therapy owing to a higher response rate and longer median progression-free survival than achieved with streptozocin-mitotane. For patients with tumours smaller than 5 cm and with no signs of lymph node or distant metastases, survival is favourable with a median exceeding 10 years. However, the overall 5-year survival rate for all patients with ACC is only 30 per cent.

CONCLUSION

Open and potentially laparoscopic adrenalectomy for selected patients is the main treatment for non-metastatic ACC, but the overall 5-year survival rate remains low.

Diagnostic and prognostic features in adrenocortical carcinoma: a single institution case series and review of the literature

Background

Adrenocortical carcinoma is a rare cancer, with an incidence in the literature of 0.5 to 2 cases per million population per year. Adult adrenocortical carcinoma has a poor prognosis, underscoring the importance of identifying diagnostic and prognostic markers.

Methods

We searched our laboratory database for all cases in the past 15 years with a diagnosis of adrenocortical carcinoma. The original slides were then reviewed for their histopathological features. A representative paraffin block was subjected to further immunohistochemical staining for Ki-67, inhibin, steroidogenic factor-1 (SF-1), p53, and Β-catenin. These slides were scored by the study pathologist who was blinded to all clinicopathological data. In addition, a comprehensive review of the relevant English literature in the past 15 years was conducted.

Results

Eight cases were identified, including two adrenal sarcomatoid carcinomas. Seven of the eight cases had a disrupted reticulin network. Six of the eight tumors had >10% Ki-67 expression. Five of the eight tumors had >10% p53 expression. Positive inhibin immunohistochemical staining was seen in three of the eight tumors, and positive SF-1 staining was seen in five of the seven stained tumors. Abnormal Β-catenin intracellular accumulation was noted in four of the eight tumors. The two tumors in our series with sarcomatoid histology did not stain positively for SF-1 or inhibin.

Conclusions

Eight cases of adrenocortical carcinoma, including two with sarcomatoid features are presented. The two sarcomatoid adrenocortical carcinomas in our series did not stain for SF-1 which suggests a possible de novo pathway of tumorigenesis for this rare variant. The reticulin staining method was a useful tool for rapid differentiation of adrenocortical adenomas and carcinomas. Diffuse p53 staining showed a trend for positive correlation with increased Ki-67 expression. Inhibin staining was inconsistently expressed in our cases of adrenocortical carcinoma. In conclusion, as adrenocortical carcinoma is a rare disease, we recommend future multicenter studies with appropriate sample sizes to further evaluate the efficacy of these diagnostic and prognostic markers.

Contemporary management of adrenocortical carcinoma

CONTEXT

Adrenocortical carcinoma (ACC) is a rare and typically aggressive malignancy. Available recommendations are based primarily on retrospective series or expert opinions, and only few prospective clinical studies have yet been published.

OBJECTIVE

To combine the available evidence for diagnostic work-up and treatment of ACC to a contemporary recommendation on the management of this disease.

EVIDENCE ACQUISITION

We conducted a systematic literature search for studies conducted on humans and published in English using the Medline/PubMed database up to 31 January 2011. In addition, we screened published abstracts at meetings and several Web sites for recommendations on ACC management.

EVIDENCE SYNTHESIS

In patients with suspected localised ACC, a thorough endocrine and imaging work-up is followed by complete (R0) resection of the tumour by an expert surgeon. In experienced hands, laparoscopic adrenalectomy is probably as effective and safe for localised and noninvasive ACC as open surgery. Most clinicians agree that mitotane should be used as adjuvant therapy in the majority of patients, as they have a high risk for recurrence. An international panel has suggested using tumour stage, resection status, and the proliferation marker Ki67 as guidance for or against adjuvant therapy. In patients with advanced disease at presentation or recurrence not amenable to complete resection, a surgical approach is frequently inadequate. In these cases, mitotane alone or in combination with cytotoxic drugs is the treatment of choice. The most promising regimens (etoposide, doxorubicin, cisplatin plus mitotane, and streptozotocin plus mitotane) are currently compared in an international phase 3 trial, and results should be available by the end of 2011. Several targeted therapies are under investigation and may lead to new treatment options. Management of endocrine manifestations with steroidogenesis inhibitors is required in patients suffering uncontrolled hormone excess.

CONCLUSIONS

Detailed recommendations are provided to guide the management of patients with ACC.

Effects of increased cross-sectional imaging on the diagnosis and prognosis of adrenocortical carcinoma: analysis of the National Cancer Database

PURPOSE

We assessed whether incidental screening due to imaging performed for other purposes has resulted in earlier detection or better outcomes in patients with adrenocortical carcinoma.

MATERIALS AND METHODS

We used the National Cancer Database to assemble a cohort diagnosed with adrenocortical carcinoma from 1985 to 2007. Trends in the distribution of grouped tumor sizes were assessed with the Cochran-Armitage chi-square test. Relative 5-year survival rates were calculated for cases diagnosed through 2002.

RESULTS

Median survival in the full cohort of 4,275 patients was 24 months. Localized adrenocortical carcinoma accounted for 43.9% of cases. No stage migration was noted with time. No statistical trends were noted in tumor size changes during the years in patients who underwent surgery for localized disease (p=0.32). No improvement was observed in 5-year survival during the period (p>0.1).

CONCLUSIONS

In this cohort of patients with adrenocortical carcinoma, which is to our knowledge the largest cohort reported to date, 43.9% presented with localized disease. No shift was noted toward lower stage or smaller tumor size in a 22-year period despite the advent of abdominal imaging and its resulting incidental screening of the adrenal gland. These data contrast with the well documented stage and size migration of tumors of the kidney, a neighboring retroperitoneal organ. Furthermore, no improvement in survival was noted. As such, better risk stratification of patients with adrenal incidentaloma, while improving treatment efficacy for those with proven adrenocortical carcinoma, is an essential clinical and epidemiological task.