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Local Recurrence Growth Rate Predicts Outcome In Locally Recurrent Retroperitoneal Liposarcoma. James Park, MD, Li-Xuan Qin, PhD, Francesco Prete, MD Murray Brennan, MD, Samuel Singer, MD. Background: Retroperitoneal Liposarcoma Retroperitoneal sarcoma (RPS) 15% of soft tissue sarcomas (STS) 1

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Local Recurrence Growth Rate Predicts OutcomeIn Locally Recurrent Retroperitoneal Liposarcoma

James Park, MD, Li-Xuan Qin, PhD, Francesco Prete, MDMurray Brennan, MD, Samuel Singer, MD


  • Background: Retroperitoneal Liposarcoma

  • Retroperitoneal sarcoma (RPS) 15% of soft tissue sarcomas (STS)1

  • Liposarcoma (LS) most common; 20% of all STS, up to 50% of RPS2

  • Complete resection feasible in 80% of primary RPLS3

  • Local recurrence 40~80%; local effects cause of death in 75%1,2

1. Stoeckle. Cancer 2001 2. Lewis. Ann Surg 1998 3. Singer. Ann Surg 2003


  • Background: Retroperitoneal Liposarcoma

  • Gross margin, grade, and histologic subtype predict survival1,2

  • Subtype and contiguous organ resection, predict local recurrence1

  • No objective consensus to guide re-resection of local recurrence following complete resection

1. Singer. Ann Surg 2003 2. van Dalen. EJSO 2006


1. Singer. Ann Surg 2003


  • Purpose

  • Determine prognostic factors for survival and recurrence in patients with locally recurrent retroperitoneal liposarcoma

  • Use these factors to guide therapy and define subset of patients with locally recurrent retroperitoneal liposarcoma most likely to benefit from surgical resection


  • Prospective sarcoma database reviewed 7/82~10/05

All STS treated N=6682

All RPS treated N=607

All RPLS treated N=355

Primary RPLS treated N=207

Complete resection N=180 (180/207 87%)

Local recurrence (LR) N=105 (105/180 58%)

Complete resection of LR N=61 (61/105 58%)


Endpoints:

Disease-specific survival (from time of first local recurrence) for all 105 patients

Local recurrence-free survival for 61 patients re-resected

Statistics:Univariate analysis- Kaplan Meier curve and Log-rank test

Multivariate analysis- Cox’s PH model and Score test

Cut-point finding- Minimum P value method




Tumor size (sum of max dimensions on imaging)

Time from primary resection to LR

  • Univariate Analysis of Disease-Specific Survival

  • for First LR (N=105)

Start time: First LR End point: Dead of disease

LR Growth Rate =



Tumor size (sum of max dimensions on pathology)

Time from primary resection to LR

  • Univariate Analysis of Disease-Specific Survival

  • for Complete Resection of First LR (N=61)

Start time: LR resection End point: Dead of disease

Second recurrence

LR Growth Rate =





0.9

1. Mazumdar. Statist Med 2003


All 105 Patients 61 Re-resected



  • LR growth rate and primary grade are independent predictors of disease-specific survival in locally recurrent RPLS

     Patients with LR growth rate ≥ 0.9 cm/month had significantly worse disease-specific survival

  • Re-resection of the recurrence did not alter the poor outcome for patients with LR growth rate ≥ 0.9 cm/month


LR growth rate predicts disease-specific survival and local control following complete resection of locally recurrent RPLS

 Patients with LR growth rate ≥ 0.9cm/month did not benefit from aggressive operative management and should be considered for trials of novel targeted therapies


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