Missed Venous Thromboembolism After Major Cancer Surgery Ryon EL, - - PowerPoint PPT Presentation

Missed Venous Thromboembolism After Major Cancer Surgery

Ryon EL, Parreco JP, Goel N, Eidelson SA, Byers PM, Yeh DD, Namias N, Rattan R.

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No disclosures

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• Venous thromboembolism (VTE) after major cancer

surgery (MCS) is significant

• 1/3 - 30 days post-discharge1
• 2/3 - 90 days post-discharge2
• Risk continues to rise up to 1y3
• Up to 1/3 of postoperative readmissions occur at

different hospital4

• 1. Merkow RP et al, Ann Surg 2011; 254(1). 2. Bouras G et al, PLoS One 2015; 10(12).
• 3. Wun T, White RH, Best Pract Res Clin Haematol 2009; 22(1). 4. Rattan R et al, Surg Inf 2017; 18(8).

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• No national studies tracking different hospital readmission for

postoperative VTE

• True rate of VTE after major cancer surgery unknown

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• 2010-2014 Nationwide Readmissions Database
• Adults after MCS without VTE during index admission

– Colectomy – Cystectomy – Esophagectomy – Gastrectomy

• 1y VTE rates, risk factors, costs

– Hysterectomy – Lung resection – Pancreatectomy – Prostatectomy

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n=1,238,706

• 30d readmission

10.6% (130,774)

• 1y readmission

21.5% (266,861)

• 1y readmission to different hospital

24.8% (66,292)

• 1y readmission with VTE

1.9% (22,746)

• 1y readmission with VTE to different hospital

28.2% (6,413)

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Procedure 1y VTE rate (%) Colectomy 2.0 Cystectomy 5.3 Esophagectomy 2.6 Gastrectomy 2.7 Hysterectomy 1.9 Lung resection 2.0 Pancreatectomy 3.7 Prostatectomy 0.8

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Risk factor Overall Different hospital Hospitalization >7d 1.60 [1.55-1.65] 0.84 [0.78-0.90] Public hospital NS 1.43 [1.31-1.57] For-profit hospital NS 1.26 [1.14-1.41] Urban teaching hospital

• 1.23 [1.14-1.32]

Medicare 1.11 [1.06-1.16] NS Medicaid 1.15 [1.08-1.22] NS Lowest income quartile 1.05 [1.01-1.09] 1.16 [1.07-1.27]

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• 1y VTE readmission cost

$83.5 Million

• 1y VTE readmission to different hospital cost

$21.5 Million

• 1y VTE readmission costs previously hidden

25.7%

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• Nearly 1 in 3 VTEs after MCS are hidden
• Missed VTEs costs $21.5mn annually
• Poorer patients experience more fragmentation of care
• Hospital type affects risk of hidden VTE

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Questions

Missed Venous Thromboembolism After Major Cancer Surgery

Ryon EL, Parreco JP, Goel N, Eidelson SA, Byers PM, Yeh DD, Namias N, Rattan R.

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Development of Malignancy-Risk Gene Signature Assay for Predicting Breast Cancer Risk

James Sun MD, Dung-Tsa Chen PhD, Jiannong Li PhD, Weihong Sun MD, Sean J. Yoder MS, Tania E. Mesa MA, Marek Wloch MS, Richard Roetzheim MD, Christine Laronga MD, M. Catherine Lee MD

March 23, 2019 Florida Chapter American College of Surgeons Annual Meeting Orlando, FL

Disclosures

• No proprietary or commercial interests
• Supported by the NCI (R21CA198762-02)
• Supported by the Tissue Core, Molecular Genomics Core

Facilities, and the Biostatistics and Bioinformatics Shared Resources (P30-CA076292)

• Malignancy-Risk signature patent (#9195796) owned by Moffitt

Cancer Center

Background

• Gail Model most commonly used tool to estimate breast

cancer risk

• Malig

ignan ancy-risk isk (MR) gene s signature re1

– Distinguishes histologically-normal tissue at increased cancer risk – Genes associated with cell cycle/proliferation functions

• Goal

al: compare MR gene signature to Gail Model as predictor

• f breast cancer risk

1Chen D-T, Nasir A, Culhane A, et al. Proliferative genes dominate malignancy-risk gene signature in histologically-normal breast tissue. Breast Cancer Res Treat. 2010;119(2):335-346.

Technical validation

• Materials and Methods

– Paired fresh frozen and FFPE

• malignant tumor and benign breast tissue from same patient

– Standard RNA extraction protocol – Custom NanoString CodeSet for gene expression

• Statistical Analysis

– Principal component analysis

Correlation of FFPE/FF specimens

Materials and Methods

Model MR a alone ne Gail il alone ne Combin ined AUC 0.61 0.68 0.71

Results

Conclusions

• Demonstrated feasibility of FFPE-based assay for breast

cancer risk

– Personalized: benign breast biopsy tissue

• Limit

mitat atio ions

– Low sample size – Scant cellularity of archived tissue

• Combination model (MR score + Gail Model) best predictive

value

– Further investigation required

Thank you!

Is it Wise to Omit Sentinel Node Biopsy in Elderly Patients with Breast Cancer?

James Sun MD, Brittany J. Mathias MD, Weihong Sun MD, William J. Fulp MS, Jun-Min Zhou PhD, Christine Laronga MD, Loretta S. Loftus MD, M. Catherine Lee MD

March 23, 2019 Florida Chapter American College of Surgeons Annual Meeting Orlando, FL

Disclosures

• No relevant financial disclosures
• Supported by the Biostatistics and Bioinformatics Shared

Resources (P30-CA076292)

Background

• SSO’s Choosing Wisely Recommendations (July 2016)
• Identified common practices that may not be necessary

– Routine SLNB is not recommended in cN0 patients ≥70 years old with hormone receptor (HR) positive breast cancer

• Referenced sources:

– CALGB 93431 – Martelli 20112

• 1. Hughes, Kevin S., et al. "Lumpectomy plus tamoxifen with or without irradiation in women age 70 years or older with early breast cancer:

long-term follow-up of CALGB 9343." Journal of Clinical Oncology 31.19 (2013): 2382.

• 2. Martelli, Gabriele, et al. "Axillary dissection versus no axillary dissection in elderly patients with breast cancer and no palpable axillary

nodes: results after 15 years of follow-up." Annals of surgical oncology18.1 (2011): 125-133.

Objectives

• The recommendation to omit SLNB in elderly patients is

poorly supported

• Is there a benefit of SLNB in elderly patients?
• Evaluated patients by SLN-status

– How does this affect management? – Does this change outcomes?

Methods

• Single-institution retrospective review
• Patients treated 1998-2016
• Age 70 years, unilateral breast cancer with resection,

positive SLNB

• Subset of hormone receptor-positive patients analyzed
• Compared by SLN status to assess differences in

treatment

Results: Comparison by SLNB status (n=500)

Va Variable Negative n = 345 n = 345 (69% (69%) Po Positive ve n = 155 n = 155 (3 (31% 1%) P- P-value Ag Age a at diagnosis diagnosis (IQR) (IQR) 74 yrs (72-78) 75 yrs (72-79) 0.27 Tu Tumor s size: median median (IQR) (IQR) 1.3 cm (0.8-2) 2 cm (1.4-2.5) <0.000 <0.0001 Tu Tumor grade 1 2 3 85 (28%) 154 (50%) 68 (22%) 25 (18%) 65 (46%) 51 (36%) 0. 0.003 003 T s T stage 1 2 3 278 (81%) 62 (18%) 5 (1%) 80 (52%) 68 (44%) 7 (4%) 0. 0.0005 0005 Ov Overa erall ll Sta Stage 1 2 3 281 (81%) 64 (19%) 0 (0%) 26 (17%) 97 (63%) 32 (20%) <0.000 <0.0001 ER ER Nega Negative Po Positive ve 40 (12%) 301 (88%) 17 (11%) 138 (89%) 0.92 PR PR Nega Negative Po Positive ve 87 (26%) 253 (74%) 34 (22%) 121 (78%) 0.44 Her2 Her2 Po Positive ve Nega Negative 27 (8%) 306 (92%) 19 (12%) 133 (88%) 0.17 XRT XRT Ye Yes No No 242 (78%) 69 (22%) 93 (62%) 56 (38%) 0. 0.0008 0008 Chemo. Chemo. Ye Yes No No 23 (7%) 290 (93%) 51 (34%) 99 (66%) <0.000 <0.0001 Hormone Hormone Ye Yes No No 229 (73%) 85 (27%) 125 (82%) 27 (18%) 0.04 0.04

Recurrence: 38/500 Locoregional: 11/500 (2.2%) Distant: 27/500 (5.4%)

Results: Comparison by SLNB status, HR+ patients (n=371)

Va Variable Negative n = 25 n = 251 1 (68% (68%) Po Positive ve n = 1 n = 120 0 (32%) 2%) P- P-value Ag Age a at diagnosis diagnosis (IQR) (IQR) 74 yrs (72-78) 75 yrs (72-79.2) 0.18 Tu Tumor s size: median median (IQR) (IQR) 1.2 cm (0.7-1.9) 2 cm (1.45-2.5) <0.000 <0.0001 Tu Tumor grade 1 2 3 70 (32%) 124 (56%) 28 (12%) 22 (20%) 56 (51%) 31 (29%) 0.27 T s T stage 1 2 3 205 (82%) 43 (17%) 3 (1%) 62 (52%) 54 (45%) 4 (3%) 0. 0.0005 0005 Ov Overall all Sta Stage 1 2 3 206 (82%) 45 (18%) 0 (0%) 20 (17%) 77 (64%) 23 (19%) <0.000 <0.0001 Her2 Her2 Ye Yes No No 11 (5%) 233 (95%) 7 (6%) 110 (94%) 0.73 XRT XRT Ye Yes No No 174 (76%) 54 (24%) 75 (66%) 39 (34%) 0.05 Chemo. Chemo. Ye Yes No No 8 (3%) 222 (97%) 31 (27%) 84 (73%) <0.000 <0.0001 Hormone Hormone Ye Yes No No 190 (83%) 40 (17%) 107 (92%) 10 (7%) 0.04 0.04

Recurrence: 18/371 Locoregional: 4/371 (1.1%) Distant: 14/370 (3.8%)

Discussion

• Subset of HR+ patients resembles overall cohort
• SLN status affected use of adjuvant chemotherapy
• No difference in locoregional recurrence by SLN status;

decreased distant recurrence in SLNB-negative patients

• Competing argument:

– Elderly patients undertreated with negative outcomes1 – Adjuvant therapy driven by tumor biology (eg; TNBC, her2

• verexpression)
• 1. Sun, S.X., Hollenbeak, C.S. and Leung, A.M., 2015. Deviation from the standard of care for early breast cancer in the elderly: what are the

consequences?. Annals of surgical oncology, 22(8), pp.2492-2499.

Conclusions

• SLNB can be safely omitted in elderly patients with IDC

tumors with T1, HR+ disease

• SLNB provides information that affects treatment

recommendations

• Candidates for adjuvant systemic chemotherapy

(performance status, tumor biology) should be considered for SLNB