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Poster Display session

214P - Development of a nomogram to predict the progression-free survival in lung cancer patients


31 Mar 2023


Poster Display session




Journal of Hepatology (2023) 18 (4S): S154-S159.


H.A. TAFENZI1, F. Choulli2, A. Baladi2, M. El Fadli2, I. Essadi2, R. Belbaraka3

Author affiliations

  • 1 Marrakech/MA
  • 2 Cadi Ayad University - Faculty of Medicine and Pharmacy, Marrakech/MA
  • 3 Cadi Ayad University - Faculty of Medicine and Pharmacy, 40080 - Marrakech/MA


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Abstract 214P


Evidences over decades made clear that lung cancer is the most aggressive cancer worldwide causing a high probability of progression and death. The aim of this study, is to build and validate internally a nomogram to predict the progression-free survival (PFS) in Moroccan patients diagnosed with lung cancer.


Data of 1200 lung cancer patients diagnosed between 2013 and 2021 in the Medical Oncology Department at Mohammed VI University Hospital of Marrakech were extracted manually from patient medical record, and filtered by applying exclusion criteria. The cohort was then split into training and test cohorts with a ratio 2:1. In the training cohort, the independent prognostic factors were determined using Cox Proportional Hazards Regression through univariate and multivariate analyses. We then constructed a nomogram to predict 6-, and 12- months PFS of LC patients, calibrate it and checking the discriminative ability of nomogram. Finally, the model was validated internally based on test cohort.


A total of 342 patients fitted with inclusion criteria, were split and interred into the analysis. From 29 selected factors, five have been independent to predict SSP including performance status, surgery, radiotherapy, number of cures of the first-line chemotherapy, and thrombocytopenia and therefore integrated to establish the nomogram. The calibration and receiver operating characteristics curves also shows that the clinical prediction model performed satisfactorily in predicting the outcome. The area under the ROC curve (AUC) value of the nomogram predicting 6-, and 12-months PFS rates were 0.8, and 0.83 for the training cohort, 0.8 and 0.78 for the validation cohort respectively. The median PFS time was 209 days (95% CI, 185 to 227 days).


We tried to established a novel medical tool to predict the PFS based on a purely well-defined African cohort taking into account demographic, clinic-pathologic, oncogenic drivers, treatments related patients including chemotherapy drugs, alcohol and tabaco status as parameters for analyses.

Legal entity responsible for the study

The authors.


Has not received any funding.


All authors have declared no conflicts of interest.

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