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1.
Cancer ; 123(4): 697-703, 2017 02 15.
Artigo em Inglês | MEDLINE | ID: mdl-27783399

RESUMO

BACKGROUND: Researchers have used prostate-specific antigen (PSA) values collected by central cancer registries to evaluate tumors for potential aggressive clinical disease. An independent study collecting PSA values suggested a high error rate (18%) related to implied decimal points. To evaluate the error rate in the Surveillance, Epidemiology, and End Results (SEER) program, a comprehensive review of PSA values recorded across all SEER registries was performed. METHODS: Consolidated PSA values for eligible prostate cancer cases in SEER registries were reviewed and compared with text documentation from abstracted records. Four types of classification errors were identified: implied decimal point errors, abstraction or coding implementation errors, nonsignificant errors, and changes related to "unknown" values. RESULTS: A total of 50,277 prostate cancer cases diagnosed in 2012 were reviewed. Approximately 94.15% of cases did not have meaningful changes (85.85% correct, 5.58% with a nonsignificant change of <1 ng/mL, and 2.80% with no clinical change). Approximately 5.70% of cases had meaningful changes (1.93% due to implied decimal point errors, 1.54% due to abstract or coding errors, and 2.23% due to errors related to unknown categories). Only 419 of the original 50,277 cases (0.83%) resulted in a change in disease stage due to a corrected PSA value. CONCLUSIONS: The implied decimal error rate was only 1.93% of all cases in the current validation study, with a meaningful error rate of 5.81%. The reasons for the lower error rate in SEER are likely due to ongoing and rigorous quality control and visual editing processes by the central registries. The SEER program currently is reviewing and correcting PSA values back to 2004 and will re-release these data in the public use research file. Cancer 2017;123:697-703. © 2016 American Cancer Society.


Assuntos
Valor Preditivo dos Testes , Antígeno Prostático Específico/sangue , Neoplasias da Próstata/epidemiologia , Programa de SEER , Humanos , Masculino , Estadiamento de Neoplasias , Neoplasias da Próstata/sangue , Neoplasias da Próstata/patologia
2.
Cancer ; 120 Suppl 23: 3815-25, 2014 Dec 01.
Artigo em Inglês | MEDLINE | ID: mdl-25412393

RESUMO

BACKGROUND: Several changes were made to bladder cancer staging guidelines between the 6th and 7th editions of the American Joint Committee on Cancer (AJCC) Staging Manual. Also, Collaborative Stage (CS) Data Collection System version 2 (CSv2) implemented for 2010 Surveillance, Epidemiology, and End Results (SEER) cases involved collection of 3 new site-specific factors (SSFs): World Health Organization/International Society of Urological pathology grade (SSF1), size of metastasis in regional lymph nodes (SSF2), and extranodal extension (SSF3). Our objective was to evaluate these new SSFs to assist researchers in their use/interpretation and to describe data quality issues to be addressed moving forward. METHODS: Staging trends were assessed for invasive and noninvasive bladder cancer cases from 2004 to 2010. Among 2010 cases, staging was compared using the AJCC 6th and 7th edition guidelines, and evaluation of completeness/quality of the SSFs was performed in relevant subgroups. RESULTS: Age-adjusted incidence rates and proportions of cases by stage remained steady from 2004 to 2010. Changes from the AJCC 6th to 7th editions caused no substantial movement between stages. SSF1 had a known value in 82% of cases, which was higher than the traditional SEER grade/differentiation variable. SSF2 and SSF3 were less complete, with 41% and 37% having known values, respectively, among cases with lymph node involvement (according to CS lymph node variable). CONCLUSIONS: SSF1 was more complete and straightforward to interpret than the traditional grade/differentiation variable. SSF2 and SSF3 were less complete, may be associated with data quality issues, and should only be used among cases with known lymph node involvement.


Assuntos
Carcinoma de Células Escamosas/patologia , Carcinoma de Células de Transição/patologia , Linfonodos/patologia , Neoplasias da Bexiga Urinária/patologia , Estudos de Coortes , Feminino , Humanos , Masculino , Estadiamento de Neoplasias/tendências , Neoplasias Epiteliais e Glandulares/patologia , Prognóstico , Estudos Retrospectivos , Programa de SEER
3.
J Registry Manag ; 48(4): 161-167, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-37260866

RESUMO

Background: The National Cancer Institute's Surveillance Research Program (SRP) received reports from cancer registries in the Surveillance, Epidemiology, and End Results (SEER) Program concerning the coding of melanoma tumor depth. To address these concerns, SRP developed an algorithm to identify melanoma depth measurement values and conducted a nonmatch analysis. Methods: A nonmatch analysis was conducted on 1,117 cases diagnosed between 2010 and 2017. With the help of Information Management Services, a natural language processing algorithm was developed to identify melanoma tumor depth values along with a gold standard for comparison. A randomly sampled data set was created to compare the algorithm-generated and gold standard values to the originally reported values; these were analyzed using SAS software version 9.4. Analyses were conducted to determine the distribution of nonmatches by demographics and estimate the distribution of nonmatches by the derived T variable according to the 7th edition of the American Joint Committee on Cancer (AJCC)'s AJCC Cancer Staging Manual. Results: Of the 1,117 cases, 849 cases (76%) were a match between the originally reported values and the gold standard. The majority of cases were found to be in male patients (60%) and non-Hispanic White patients (93%). When comparing derived AJCC-7 T based on the originally reported value to the gold standard, 16% of the original derived AJCC-7 T values were incorrect, with most of the nonmatches resulting in incorrectly coding a case as TX instead of T1. Conclusion: In total, 24% of cases were found to have a discrepancy in the originally recorded values. Decimal errors made up 3% of all cases in this nonmatch analysis. This algorithm may prove to be an essential tool in optimizing registry resources by flagging inconsistencies via automated text review to be adjudicated by registrars, improving their quality of data as needed.

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