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Validation of a Resectability Scoring System for Prediction of Pancreatic Adenocarcinoma Surgical Outcomes

  • Pancreatic Tumors
  • Published:
Annals of Surgical Oncology Aims and scope Submit manuscript

Abstract

Background

The most used pancreatic cancer (PC) resectability criteria are descriptive in nature or based solely on dichotomous degree of involvement (< 180° or > 180°) of vessels, which allows for a high degree of subjectivity and inconsistency.

Methods

Radiographic measurements of the circumferential degree and length of tumor contact with major peripancreatic vessels were retrospectively obtained from pre-treatment multi-detector computed tomography (MDCT) images from PC patients treated between 2001 and 2015 at two large academic institutions. Arterial and venous scores were calculated for each patient, then tested for a correlation with tumor resection and R0 resection.

Results

The analysis included 466 patients. Arterial and venous scores were highly predictive of resection and R0 resection in both the training (n = 294) and validation (n = 172) cohorts. A recursive partitioning tree based on arterial and venous score cutoffs developed with the training cohort was able to stratify patients of the validation cohort into discrete groups with distinct resectability probabilities. A refined recursive partitioning tree composed of three resectability groups was generated, with probabilities of resection and R0 resection of respectively 94 and 73% for group A, 61 and 35% for group B, and 4 and 2% for group C. This resectability scoring system (RSS) was highly prognostic, predicting median overall survival times of 27, 18.9, and 13.5 months respectively for patients in RSS groups A, B, and C (p < 0.001).

Conclusions

The proposed RSS was highly predictive of resection, R0 resection, and prognosis for patients with PC when tested against an external dataset.

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Data Availability

A data-sharing agreement was established between the two participating institutions. The data used for this work will not be made publicly available because it is not de-identified and because public sharing of de-identified information was not included in the Institutional Review Board protocol (IRB protocol No. 37339).

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Funding

This research has not been supported by any funds or grants.

Author information

Authors and Affiliations

  1. Department of Radiation Oncology, Mayo Clinic Arizona, Phoenix, AZ, USA

    Diego A. S. Toesca MD

  2. Department of Radiation Oncology, University of California San Francisco, San Francisco, CA, USA

    Matthew Susko MD & Mary Feng MD

  3. Department of Radiation Oncology, Stanford Cancer Institute, 875 Blake Wilbur Drive MC5847, Stanford, CA, 94305, USA

    Rie von Eyben MSc, J. Richelsyn M. Baclay MD, Erqi L. Pollom MD & Daniel T. Chang MD

  4. Department of Radiology, Stanford Cancer Institute, Stanford, CA, USA

    R. Brooke Jeffrey MD & Peter D. Poullos MD

  5. Department of Surgery, Stanford Cancer Institute, Stanford, CA, USA

    George A. Poultsides MD & Brendan C. Visser MD

  6. Department of Medical Oncology, Stanford Cancer Institute, Stanford, CA, USA

    George A. Fisher Jr MD, PhD

  7. Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

    Albert C. Koong MD, PhD

  8. Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA

    Daniel T. Chang MD

Authors
  1. Diego A. S. Toesca MD
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  2. Matthew Susko MD
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  3. Rie von Eyben MSc
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  4. J. Richelsyn M. Baclay MD
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  5. Erqi L. Pollom MD
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  6. R. Brooke Jeffrey MD
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  7. Peter D. Poullos MD
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  8. George A. Poultsides MD
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  10. Brendan C. Visser MD
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  11. Albert C. Koong MD, PhD
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  12. Mary Feng MD
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  13. Daniel T. Chang MD
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Contributions

DAST: conceptualization; investigation; data curation; methodology; formal analysis; investigation; validation; writing—original draft; writing—review and editing. MS: conceptualization; investigation; data curation; validation; writing—original draft; writing—review and editing. RE: data curation; methodology; formal analysis; validation; writing—original draft; writing—review and editing. JRMB: data curation; investigation; validation; writing—review and editing. ELP: conceptualization; methodology; validation; writing—review and editing. RBJ: conceptualization; methodology; validation; writing—review and editing. PDP: conceptualization; methodology; validation; writing—review and editing. GAP: conceptualization; methodology; validation; writing—review and editing. GAF: conceptualization; methodology; validation; writing—review and editing. BCV: conceptualization; methodology; validation; writing—review and editing. ACK: conceptualization; methodology; validation; writing—review and editing. Mary Feng: conceptualization; methodology; validation; writing—review and editing. DTC: conceptualization; methodology; validation; writing—original draft; writing—review and editing.

Corresponding author

Correspondence to Daniel T. Chang MD.

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Toesca, D.A.S., Susko, M., von Eyben, R. et al. Validation of a Resectability Scoring System for Prediction of Pancreatic Adenocarcinoma Surgical Outcomes. Ann Surg Oncol 30, 3479–3488 (2023). https://doi.org/10.1245/s10434-023-13120-3

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  • DOI: https://doi.org/10.1245/s10434-023-13120-3

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