Dataset Information

Accuracy of The Cancer Genome Atlas Classification vs American Joint Committee on Cancer Classification for Prediction of Metastasis in Patients With Uveal Melanoma.

ABSTRACT:

Importance

The Cancer Genome Atlas (TCGA) classification is a newly emerging method for prediction of uveal melanoma (UM)-related metastasis and death. Limited information is available regarding the accuracy of the TCGA classification for prediction of metastasis in patients with UM.

Objective

To investigate the accuracy of the TCGA classification for predicting UM-related metastasis compared with the American Joint Committee on Cancer (AJCC) classification.

Design, setting, and participants

In this retrospective cohort study, patients with UM treated with plaque radiotherapy at a tertiary referral center from October 1, 2008, to December 31, 2018, were evaluated. All patients with tumors classified according to the American Joint Committee on Cancer Staging Manual, 8th Edition, and who completed pretreatment fine-needle aspiration biopsy sampling for genetic analysis of chromosomes 3 and 8 for TCGA classification were included. Tumors were classified into 4 categories, 17 subcategories, and 4 stages using AJCC classification and further grouped into 4 classes using TCGA classification.

Main outcomes and measures

Value of TCGA classification vs AJCC classification for predicting UM-related metastasis.

Results

Of 642 included patients, 331 (51.6%) were women, and the mean (SD) age was 58.0 (13.8) years. There were 642 tumors from 642 patients classified according to both AJCC and TCGA classifications. The mean (range) follow-up time for the entire cohort was 43.7 (1.4-159.2) months. At 5 years, TCGA classification showed higher value for prediction of metastasis (4 TCGA classes: Wald statistic, 94.8; hazard ratio [HR], 2.8; 95% CI, 2.3-3.5; P?Conclusions and relevanceThese results suggest that TCGA classification provides accuracy that is superior to AJCC categories, subcategories, and stages for predicting metastasis from UM. When genetic testing is available, TCGA classification can provide a more accurate way to identify patients at high risk of metastasis who might benefit from adjuvant therapy.

SUBMITTER: Mazloumi M

PROVIDER: S-EPMC6990957 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Accuracy of The Cancer Genome Atlas Classification vs American Joint Committee on Cancer Classification for Prediction of Metastasis in Patients With Uveal Melanoma.

Mazloumi Mehdi M Vichitvejpaisal Pornpattana P Dalvin Lauren A LA Yaghy Antonio A Ewens Kathryn G KG Ganguly Arupa A Shields Carol L CL

JAMA ophthalmology 20200301 3

<h4>Importance</h4>The Cancer Genome Atlas (TCGA) classification is a newly emerging method for prediction of uveal melanoma (UM)-related metastasis and death. Limited information is available regarding the accuracy of the TCGA classification for prediction of metastasis in patients with UM.<h4>Objective</h4>To investigate the accuracy of the TCGA classification for predicting UM-related metastasis compared with the American Joint Committee on Cancer (AJCC) classification.<h4>Design, setting, an ...[more]

PMID: 31944225

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Project description:BackgroundThe American Joint Committee on Cancer (AJCC) maintains that the eighth edition of its Staging Manual (AJCC8) has improved accuracy compared with the seventh (AJCC7). However, there are concerns that implementation may disrupt analysis of active clinical trials for stage III patients. We used an independent cohort of melanoma patients to test the extent to which AJCC8 has improved prognostic accuracy compared with AJCC7.MethodsWe analyzed a cohort of 1315 prospectively enrolled patients. We assessed primary tumor and nodal classification of stage I-III patients using AJCC7 and AJCC8 to assign disease stages at diagnosis. We compared recurrence-free (RFS) and overall survival (OS) using Kaplan-Meier curves and log-rank tests. We then compared concordance indices of discriminatory prognostic ability and area under the curve of 5-year survival to predict RFS and OS. All statistical tests were two-sided.ResultsStage IIC patients continued to have worse outcomes than stage IIIA patients, with a 5-year RFS of 26.5% (95% confidence interval [CI] = 12.8% to 55.1%) vs 56.0% (95% CI = 37.0% to 84.7%) by AJCC8 (P = .002). For stage I, removing mitotic index as a T classification factor decreased its prognostic value, although not statistically significantly (RFS concordance index [C-index] = 0.63, 95% CI = 0.56 to 0.69; to 0.56, 95% CI = 0.49 to 0.63, P = .07; OS C-index = 0.48, 95% CI = 0.38 to 0.58; to 0.48, 95% CI = 0.41 to 0.56, P = .90). For stage II, prognostication remained constant (RFS C-index = 0.65, 95% CI = 0.57 to 0.72; OS C-index = 0.61, 95% CI = 0.50 to 0.72), and for stage III, AJCC8 yielded statistically significantly enhanced prognostication for RFS (C-index = 0.65, 95% CI = 0.60 to 0.70; to 0.70, 95% CI = 0.66 to 0.75, P = .01).ConclusionsCompared with AJCC7, we demonstrate that AJCC8 enables more accurate prognosis for patients with stage III melanoma. Restaging a large cohort of patients can enhance the analysis of active clinical trials.

Project description:Answer questions and earn CME/CNE To update the melanoma staging system of the American Joint Committee on Cancer (AJCC) a large database was assembled comprising >46,000 patients from 10 centers worldwide with stages I, II, and III melanoma diagnosed since 1998. Based on analyses of this new database, the existing seventh edition AJCC stage IV database, and contemporary clinical trial data, the AJCC Melanoma Expert Panel introduced several important changes to the Tumor, Nodes, Metastasis (TNM) classification and stage grouping criteria. Key changes in the eighth edition AJCC Cancer Staging Manual include: 1) tumor thickness measurements to be recorded to the nearest 0.1 mm, not 0.01 mm; 2) definitions of T1a and T1b are revised (T1a, <0.8 mm without ulceration; T1b, 0.8-1.0 mm with or without ulceration or <0.8 mm with ulceration), with mitotic rate no longer a T category criterion; 3) pathological (but not clinical) stage IA is revised to include T1b N0 M0 (formerly pathologic stage IB); 4) the N category descriptors "microscopic" and "macroscopic" for regional node metastasis are redefined as "clinically occult" and "clinically apparent"; 5) prognostic stage III groupings are based on N category criteria and T category criteria (ie, primary tumor thickness and ulceration) and increased from 3 to 4 subgroups (stages IIIA-IIID); 6) definitions of N subcategories are revised, with the presence of microsatellites, satellites, or in-transit metastases now categorized as N1c, N2c, or N3c based on the number of tumor-involved regional lymph nodes, if any; 7) descriptors are added to each M1 subcategory designation for lactate dehydrogenase (LDH) level (LDH elevation no longer upstages to M1c); and 8) a new M1d designation is added for central nervous system metastases. This evidence-based revision of the AJCC melanoma staging system will guide patient treatment, provide better prognostic estimates, and refine stratification of patients entering clinical trials. CA Cancer J Clin 2017;67:472-492. © 2017 American Cancer Society.

Project description:BACKGROUND:The American Joint Committee on Cancer (AJCC) breast cancer staging system provides important prognostic information. The recently published eighth edition incorporates biological markers and recommends the use of a complex "prognostic stage." In this study, we assessed the relationship between stage, breast cancer subtype, grade, and outcome in a large population-based cohort and evaluated a risk score system incorporating tumor characteristic to the AJCC anatomic staging system. MATERIALS AND METHODS:Patients diagnosed with primary breast cancer stage I-IV between 2005-2008 were identified in the California Cancer Registry. For patients with stage I-III disease, pathologic stage was recorded. For patients with stage IV disease, clinical stage was utilized. Five-year breast cancer specific survival (BCSS) and overall survival (OS) rates were determined for each potential tumor size-node involvement-metastases (TNM) combination according to breast cancer subtype. A risk score point-based system using grade, estrogen receptor, and human epidermal growth factor receptor 2 (HER2) status was designed to complement the anatomic AJCC staging system. Survival probabilities between groups were compared using log-rank test. Cox proportional hazards models were used. RESULTS:Among 43,938 patients, we observed differences in 5-year BCSS and OS for each TNM combination according to breast cancer subtype. The most favorable outcomes were seen for hormone receptor-positive tumors followed closely by HER2-positive tumors, with the worst outcomes observed for triple negative breast cancer. Our risk score system separated patients into four risk groups within each stage category (all p?<?.05). CONCLUSION:Our simple risk score system incorporates biological factors into the AJCC anatomic staging system, providing accurate prognostic information. IMPLICATIONS FOR PRACTICE:This study demonstrates that stage, but also breast cancer subtype and grade, define prognosis in a large population of breast cancer patients. It shows that a point-based risk score system that incorporates these biological factors provides refined stratification and information on prognosis, improving the anatomic American Joint Committee on Cancer (AJCC) staging system. In addition, the overall mortality and breast cancer specific mortality rates detailed here provide much-needed information about prognosis in the current era, refining the current AJCC staging.

Project description:ImportanceControversy exists around the American Joint Committee on Cancer (AJCC) TNM staging system for medullary thyroid cancer (MTC). Because of the rarity of the disease and limited available data, the staging system for MTC has been largely extrapolated from staging for differentiated thyroid cancer.ObjectivesTo evaluate how well the current (seventh and eighth editions) AJCC TNM staging system correlates with survival for patients with MTC and to suggest a possible revision.Design, setting, and participantsThis population-based retrospective cohort analysis used the National Cancer Database to select patients aged 18 years or older diagnosed with MTC in the United States between 1998 and 2012. Patient demographic and tumor characteristics were assessed, and pathologic tumor stages were provided as T, N, and M categories. Recursive partitioning with bootstrapping was used to divide patients by TNM stages into groups with similar survival. The newly identified groupings were validated in a Surveillance, Epidemiology, and End Results (SEER) cohort. Data analysis was conducted between July 17, 2016, and November 11, 2016.Main outcomes and measuresOverall survival and disease-specific survival.ResultsOf the 3315 patients with MTC included in the analysis, 1941 (58.6%) were women. The median (interquartile range) age was 54 (42-65) years, and 2839 (85.6%) self-reported their race/ethnicity as white. The current AJCC TNM staging system classified 941 of these patients (28.4%) as stage I, 907 (27.4%) as stage II, 424 (12.9%) as stage III, and 1043 (31.5%) as stage IV. Recursive partitioning analysis yielded 4 TNM groups: stage I (T1N0-1aM0, T2N0M0), stage II (T1N1bM0, T2N1a-bM0, and T3N0M0), stage III (T3N1a-bM0, T4N0-1bM0), and stage IV (T1-4N0-1bM1). Based on these proposed TNM groupings, 1797 of the 3315 patients (54.2%) were classified as stage I, 684 (20.6%) as stage II, 669 (20.2%) as stage III, and 165 (5.0%) as stage IV. Under the proposed TNM groupings, survival differences across TNM groups were more distinct than under the current AJCC TNM staging system. With stage I as the reference, the hazard ratios of the proposed TNM groupings and the current AJCC TNM staging system were 2.19 (95% CI, 1.37-3.12) vs 1.45 (95% CI, 1.09-1.92) for stage II, 4.20 (95% CI, 2.75-5.75) vs 2.17 (95% CI, 1.59-2.89) for stage III, and 10.97 (95% CI, 5.52-18.57) vs 5.33 (95% CI, 4.13-6.86) for stage IV. In a SEER cohort, the proposed TNM groupings were better at discriminating survival than was the current AJCC TNM staging system.Conclusions and relevanceThe current AJCC TNM staging system for MTC appears to be less than optimal in distinguishing risk of mortality among stage groups, upstaging a significant number of patients to stage IV. The current AJCC TNM staging system could be improved with the new TNM groupings proposed here for more accurate risk stratification and potential treatment selection.

Project description:ImportanceImmune checkpoint inhibitors (ICIs) have transformed the survival of patients with metastatic melanoma. Patient prognosis is reflected by the American Joint Committee on Cancer (AJCC) staging system; however, it is unknown whether the metastatic (M) stage categories for cutaneous melanoma remain informative of prognosis in patients who have received ICIs.ObjectivesTo evaluate the outcomes of patients with metastatic cutaneous melanoma based on the M stage category from the AJCC eighth edition and to determine whether these designations continue to inform the prognosis of patients who have received ICIs.Design, setting, and participantsThis cohort study included patients with metastatic cutaneous melanoma who were treated between August 2006 and August 2019 at the University of Michigan. The estimated median follow-up time was 35.5 months. Patient data were collected via the electronic medical record system. Critical findings were externally validated in a multicenter nationwide cohort of patients treated within the Veterans Affairs health care system. Data analysis was conducted from February 2020 to January 2021.ExposuresAll patients were treated with dual-agent concurrent ipilimumab and nivolumab followed by maintenance nivolumab or single-agent ipilimumab, nivolumab, or pembrolizumab therapy. Patients were staged using the AJCC eighth edition.Main outcomes and measuresUnivariable and multivariable analyses were used to assess the prognostic value of predefined clinicopathologic baseline factors on survival.ResultsIn a discovery cohort of 357 patients (mean [SD] age, 62.6 [14.2] years; 254 [71.1%] men) with metastatic cutaneous melanoma treated with ICIs, the M category in the AJCC eighth edition showed limited prognostic stratification by both univariable and multivariable analyses. The presence of liver metastases and elevated levels of serum lactate dehydrogenase (LDH) offered superior prognostic separation compared with the M category (liver metastases: hazard ratio, 2.22; 95% CI, 1.48-3.33; P < .001; elevated serum LDH: hazard ratio, 1.73; 95% CI, 1.16-2.58; P = .007). An updated staging system based on these factors was externally validated in a cohort of 652 patients (mean [SD] age, 67.9 [11.6] years; 630 [96.6%] men), with patients without liver metastases or elevated LDH levels having the longest survival (median overall survival, 30.7 months).Conclusions and relevanceThis study found that the AJCC eighth edition M category was poorly reflective of prognosis in patients receiving ICIs. Future staging systems could consider emphasizing the presence of liver metastases and elevated LDH levels. Additional studies are needed to confirm the importance of these and other prognostic biomarkers.

Project description:This study compared the prognostic significance of staging between the American Joint Committee on Cancer 8th edition Tumor, Node, Metastasis (TNM) staging system and the Barcelona Clinic Liver Cancer (BCLC) classification in patients with hepatocellular carcinoma (HCC). The study population comprised patients with liver cancer registered in the Taiwan Cancer Database from 2007 to 2013 and was followed up until December 31, 2016. The study included patients with HCC, with known staging in both TNM and BCLC systems, and with follow-up >1 month. Primary endpoint was overall survival. Univariate and multivariate Cox proportional hazards model were constructed to investigate the significance of staging by two systems. Goodness-of-fit of model was evaluated via Akaike's information criterion (AIC), the lower the better. Among 73,136 patients with newly diagnosed liver cancer, a total of 37,062 patients with HCC (25.6% underwent surgery) were eligible. The mean age and overall survival of this cohort were 63.9 years and 27.2%, respectively. Overall survivals for stages I, II, III, and IV (the TNM system) were 54.5%, 34.9%, 10.3%, and 6.4%, respectively. Overall survivals for stages A, B, C, and D (the BCLC classification) were 54.5%, 29.2%, 9.8%, and 4.0%, respectively. The median follow-up time was 59.4 months. Multivariate Cox proportional hazards model revealed that both systems predicted overall survival, cancer-specific survival, disease-free survival, and local recurrence-free rate well. Values of ΔAIC of the BCLC classification and the TNM system were lower for the surgery group and nonsurgery group, respectively. The TNM system (8th edition) predicted long-term outcome better than the BCLC classification in patients with HCC. But in patients treated initially with surgery, the BCLC classification outperformed the 8th edition of the TNM system. IMPLICATIONS FOR PRACTICE: This work demonstrates that the Tumor, Node, Metastasis (TNM) system (8th edition) and the Barcelona Clinic Liver Cancer (BCLC) classification both predict long-term outcome significantly in patients with hepatocellular carcinoma but that the TNM system (8th edition) predicts long-term outcome better than the BCLC classification. For patients treated initially with surgery, BCLC classification outperforms in 8th edition TNM system in predicting long-term outcome.

Dataset Information

Accuracy of The Cancer Genome Atlas Classification vs American Joint Committee on Cancer Classification for Prediction of Metastasis in Patients With Uveal Melanoma.

Importance

Objective

Design, setting, and participants

Main outcomes and measures

Results

Publications

Accuracy of The Cancer Genome Atlas Classification vs American Joint Committee on Cancer Classification for Prediction of Metastasis in Patients With Uveal Melanoma.

Similar Datasets

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