New Survival Prediction Model for Locally Advanced Pancreatic Cancer

MedicalResearch.com Interview with:

Dr-Dewi-VernereyDewi Vernerey PhD
Epidemiologist / Statistician
Methodology and quality of Life in oncology unit
University Hospital of Besançon

MedicalResearch.com: What is the background for this study?

Response: The management of locally advanced pancreatic cancer (LAPC) patients is still controversial. Better discrimination for the prediction of overall survival (OS) at diagnosis is needed. Currently, there is a lack of a staging system and an absence of a consensus regarding patient-specific risk profile for OS that can lead to confusion about the development of research strategy and to potentially inappropriate management of patients with locally advanced pancreatic cancer.


MedicalResearch.com: What are the main findings?

Response: On the basis of the largest phase III clinical trial of locally advanced pancreatic cancer, we established a novel easy-to-use survival prediction model built on five key parameters (age, albumin, tumour size, CA 19-9 and pain) and provided a prognostic nomogram and score (http://www.umqvc.org/en/tool/prolap.html).

The PROLAP score has the potential to delineate three different prognosis groups with median OS of 15.4, 11.7 and 8.5 months (log-rank P<0.0001). The score ability to discriminate OS was externally confirmed in 106 consecutive locally advanced pancreatic cancer. patients treated in Besancon Hospital, France; median OS of 18.3, 14.1 and 7.6 months for the three groups (log-rank P<0.0001).

MedicalResearch.com: What should readers take away from your report?

Response: In this study, we revealed considerable heterogeneity among locally advanced pancreatic cancer patients regarding their OS-risk profiles with the recognition of clearly different risk groups.

The PROLAP nomogram and score can accurately predict OS before initiation of induction chemotherapy in LAPC untreated patients and may help to optimise clinical trials design and might offer the opportunity to define risk-adapted strategies for LAPC management in the future.

MedicalResearch.com: What recommendations do you have for future research as a result of this study?

Response: It seems therefore reasonable to recommend pre-planned subgroup analyses according to the level of such a score in future trials.

MedicalResearch.com: Is there anything else you would like to add?

Response: It is worth noting that two of the five factors included in our model, pain and albumin are objective surrogates for measurement of Health Related Quality of Life (HRQoL). The importance of these parameters in the model and the recognition of HRQoL as an additional prognostic value for OS in metastatic disease and in other tumour types suggest that HRQoL needs to be evaluated in the future prognostic models for LAPC.

MedicalResearch.com: Thank you for your contribution to the MedicalResearch.com community.

Citation:

Br J Cancer. 2016 Jul 26;115(3):281-289. doi: 10.1038/bjc.2016.212. Epub 2016 Jul 12.
Prognostic nomogram and score to predict overall survival in locally advanced untreated pancreatic cancer (PROLAP).

Vernerey D1, Huguet F2,3, Vienot A4, Goldstein D5,6, Paget-Bailly S1, Van Laethem JL7, Glimelius B8, Artru P2,9, Moore MJ10, André T2,11,Mineur L12, Chibaudel B2,13, Benetkiewicz M2, Louvet C2,14, Hammel P2,15, Bonnetain F1,2.

Note: Content is Not intended as medical advice. Please consult your health care provider regarding your specific medical condition and questions.

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2 thoughts on “New Survival Prediction Model for Locally Advanced Pancreatic Cancer

    • Regional lymph node invasion was included in the model process construction but was not associated with Overall Survival in the univariate Cox modelisation (p=0.6584).
      Please find the complete model process construction in the online publication:

      Br J Cancer. 2016 Jul 26;115(3):281-289. doi: 10.1038/bjc.2016.212. Epub 2016 Jul 12.
      Prognostic nomogram and score to predict overall survival in locally advanced untreated pancreatic cancer (PROLAP).

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