1. Factors Influencing Sarcoma Referral and Treatment William G. Ward, Matthew T. Cline, Fred J. Dorey* Wake Forest University Health Sciences, Winston-Salem, NC, *Department of Pediatrics, USC Keck School of Medicine, Los Angeles, CA

2. What Is An Unplanned Resection? Lack of … Lack of … Preoperative imaging modalities Preoperative imaging modalities True wide resection True wide resection

3. Unplanned Resections Difficult reresection for oncologic surgeon Difficult reresection for oncologic surgeon Increased morbidity for sarcoma patients Increased morbidity for sarcoma patients Reresection Reresection Additional hospital stay Additional hospital stay Higher rate of local recurrence Higher rate of local recurrence

4. Primary Question What factors influence treatment prior to referral? Insurance status Insurance status Race Race Age Age Tumor size Tumor size Bone vs. Soft-tissue Bone vs. Soft-tissue

5. Hypothesis Patients with insurance would be more likely to have undergone an unplanned resection prior to referral Patients with insurance would be more likely to have undergone an unplanned resection prior to referral

6. Demographic Information 401 Sarcoma Patients 401 Sarcoma Patients 172 Bone and 229 Soft Tissue Sarcomas 172 Bone and 229 Soft Tissue Sarcomas 183 Females, 218 Males 183 Females, 218 Males Average age 48 (1 to 95) Average age 48 (1 to 95)Results Local recurrence-free survivorship = 91.9% ± 1.65% Local recurrence-free survivorship = 91.9% ± 1.65% Overall survivorship = 67% ± 2.4% at 5 years. Overall survivorship = 67% ± 2.4% at 5 years.

7. Diagnostic Information SarcomaNumber Osteosarcoma74 Malignant Fibrous Histiocytoma56 Liposarcoma52 Chondrosarcoma41 Myxofibrosarcoma31 Synovial cell Sarcoma24 Ewing's Sarcoma22 Other20 Leiomyosarcoma17 Malignant Peripheral Nerve Sheath Tumor14 Pleomorphic Sarcoma14 Sarcoma (unspecified)14 Fibrosarcoma12 Rhabdomyosarcoma6 Epithelioid Sarcoma4

8. Results

9. Insurance Status and Unplanned Resection Patients on Medicaid were less likely have an unplanned resection (p=0.14) Patients on Medicaid were less likely have an unplanned resection (p=0.14)

10. Insurance and Unplanned Resections Prior to Referral Insurance Type Patients Patients with unplanned resections, N (%) p = 0.14 Medicaid18 1 (5%) Commercial313 76 (24%) Uninsured38 10 (26%) Medicare32 11 (34%)

11. Race and Unplanned Resection African Americans were less likely to have an unplanned resection (p=0.05) African Americans were less likely to have an unplanned resection (p=0.05) African Americans were not more likely to be uninsured or on Medicaid African Americans were not more likely to be uninsured or on Medicaid

12. Race and Treatment RacePatients Patients with unplanned resections, N (%) p = 0.05 African Americans 42 5 (12%) Caucasian351 90 (26%) Other8 3 (37%)

13. Age and Unplanned Resection Patients under the age of 18 were less likely to have an unplanned resection. (p=0.004) Patients under the age of 18 were less likely to have an unplanned resection. (p=0.004)

14. Age and Treatment Age, years Number of patients Patients with unplanned resections, N (%) p = 0.004 <1859 5 (8%)  18 342 93 (27%)

15. Tumor Size and Unplanned Resection Patients with tumors  5cm at initial resection were more likely to have an unplanned resection (p < 0.001) Patients with tumors  5cm at initial resection were more likely to have an unplanned resection (p < 0.001)

16. Unplanned Resections Based on Tumor Size Resection Tumor size,  5cm N Tumor size,  >5cm N Unplanned3730 No Unplanned 32118 p < 0.001

17. Soft Tissue or Bone Tumor and Unplanned Resection Patient with bone tumors were less likely to have an unplanned resection ( Patient with bone tumors were less likely to have an unplanned resection ( p < 0.01)

18. Soft Tissue or Bone Tumor and Unplanned Resection Tumor Location Unplanned Resection Soft Tissue 68/229 (30%) Bone 30/172 (17%) p < 0.01

19. Logistic Regression Analysis of Local Recurrence Following Reresection *Multi-variant analysis taking into account tumor size. Dependent variable = local recurrence Independent variable = plan vs unplanned resection Odds ratio = 3.027* Resection Local recurrence N (%) p = 0.012 Unplanned 14/68 (21%) No Unplanned 15/161 (9%)

20. Discussion Our impression is that most unplanned resection were performed in situations where the diagnosis of malignancy was not included in the differential diagnosis. Our impression is that most unplanned resection were performed in situations where the diagnosis of malignancy was not included in the differential diagnosis. Evidence…unplanned resections less likely to occur with larger tumors, patients under the age of 18, and bone tumors. Evidence…unplanned resections less likely to occur with larger tumors, patients under the age of 18, and bone tumors.

21. Teaching Point Whenever treating a “suspicious” mass always include malignancy in the differential diagnosis. Whenever treating a “suspicious” mass always include malignancy in the differential diagnosis. Avoid unplanned resections – consider early referral to oncologic surgeon and/or appropriate preoperative imaging. Avoid unplanned resections – consider early referral to oncologic surgeon and/or appropriate preoperative imaging. Consider preoperative biopsy Consider preoperative biopsy FNA/aspiration FNA/aspiration Transilluminate all suspected ganglions Transilluminate all suspected ganglions

22. Conclusion - Summary Those less likely to undergo an unplanned resection... Those less likely to undergo an unplanned resection... Patients with larger lesions, p<0.001 Patients with larger lesions, p<0.001 Patients under the age of 18, p=0.004 Patients under the age of 18, p=0.004 Patients with bone tumors, p<0.01 Patients with bone tumors, p<0.01 African Americans, p=0.05 African Americans, p=0.05 Patients on Medicaid, p=0.14 Patients on Medicaid, p=0.14 Patients subjected to unplanned resections are three times more likely to have a local recurrence following definitive re-resection. Patients subjected to unplanned resections are three times more likely to have a local recurrence following definitive re-resection.

23. Thank you Thank you