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Failure patterns in resected pancreas adenocarcinoma: lack of predicted benefit to SMAD4 expression.

Publication ,  Journal Article
Winter, JM; Tang, LH; Klimstra, DS; Liu, W; Linkov, I; Brennan, MF; DʼAngelica, MI; DeMatteo, RP; Fong, Y; Jarnagin, WR; Oʼreilly, EM; Allen, PJ
Published in: Ann Surg
August 2013

OBJECTIVE: To determine whether SMAD4 expression is associated with recurrence pattern after resection for pancreatic ductal adenocarcinoma (PDA). BACKGROUND: SMAD4 expression status has been reported to be associated with patterns of failure in PDA, but studies have not examined recurrence patterns after resection. METHODS: A tissue microarray was constructed including 127 patients with resected PDA and either short-term (<12 months) or long-term (>30 months) survival. SMAD4 expression was evaluated by immunohistochemistry and categorized as present or lost in tumor cells. Conventional pathologic features (lymph node metastases, positive resection margin, poor grade, and tumor size) were recorded, and disease-specific outcomes (eg, recurrence pattern and early cancer-specific mortality) were determined. RESULTS: Loss of SMAD4 expression in pancreatic adenocarcinoma was identified in 40 of 127 patients (32%). SMAD4 loss occurred in 27% of patients who experienced isolated local recurrence, 33% of patients with a distant recurrence, 33% of patients who experienced local and distant site recurrences, and 25% of patients who were without evidence of recurrence (Fisher exact, P = 0.9). In a multivariate analysis, the presence of regional lymph node metastases was the only factor associated with the development of distant metastases (odds ratio = 4.7, P = 0.02). SMAD4 was neither associated with recurrence pattern (odds ratio = 0.9, P = 0.9) nor associated with early death (odds ratio = 0.5, P = 0.15). CONCLUSIONS: Primary tumor SMAD4 expression status was not a predictor of recurrence pattern in a large cohort of patients with resected PDA.

Duke Scholars

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Published In

Ann Surg

DOI

EISSN

1528-1140

Publication Date

August 2013

Volume

258

Issue

2

Start / End Page

331 / 335

Location

United States

Related Subject Headings

  • Treatment Outcome
  • Tissue Array Analysis
  • Survival Rate
  • Surgery
  • Smad4 Protein
  • Pancreaticoduodenectomy
  • Pancreatic Neoplasms
  • Pancreatectomy
  • Neoplasm Recurrence, Local
  • Multivariate Analysis
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Winter, J. M., Tang, L. H., Klimstra, D. S., Liu, W., Linkov, I., Brennan, M. F., … Allen, P. J. (2013). Failure patterns in resected pancreas adenocarcinoma: lack of predicted benefit to SMAD4 expression. Ann Surg, 258(2), 331–335. https://doi.org/10.1097/SLA.0b013e31827fe9ce
Winter, Jordan M., Laura H. Tang, David S. Klimstra, Weiguo Liu, Irena Linkov, Murray F. Brennan, Michael I. DʼAngelica, et al. “Failure patterns in resected pancreas adenocarcinoma: lack of predicted benefit to SMAD4 expression.Ann Surg 258, no. 2 (August 2013): 331–35. https://doi.org/10.1097/SLA.0b013e31827fe9ce.
Winter JM, Tang LH, Klimstra DS, Liu W, Linkov I, Brennan MF, et al. Failure patterns in resected pancreas adenocarcinoma: lack of predicted benefit to SMAD4 expression. Ann Surg. 2013 Aug;258(2):331–5.
Winter, Jordan M., et al. “Failure patterns in resected pancreas adenocarcinoma: lack of predicted benefit to SMAD4 expression.Ann Surg, vol. 258, no. 2, Aug. 2013, pp. 331–35. Pubmed, doi:10.1097/SLA.0b013e31827fe9ce.
Winter JM, Tang LH, Klimstra DS, Liu W, Linkov I, Brennan MF, DʼAngelica MI, DeMatteo RP, Fong Y, Jarnagin WR, Oʼreilly EM, Allen PJ. Failure patterns in resected pancreas adenocarcinoma: lack of predicted benefit to SMAD4 expression. Ann Surg. 2013 Aug;258(2):331–335.

Published In

Ann Surg

DOI

EISSN

1528-1140

Publication Date

August 2013

Volume

258

Issue

2

Start / End Page

331 / 335

Location

United States

Related Subject Headings

  • Treatment Outcome
  • Tissue Array Analysis
  • Survival Rate
  • Surgery
  • Smad4 Protein
  • Pancreaticoduodenectomy
  • Pancreatic Neoplasms
  • Pancreatectomy
  • Neoplasm Recurrence, Local
  • Multivariate Analysis