Development and external validation of a dynamic prognostic nomogram for primary extremity soft tissue sarcoma survivors

Abstract

Background: Prognostic nomograms for patients with extremity soft tissue sarcoma (eSTS) typically predict survival or the occurrence of local recurrence or distant metastasis at time of surgery. Our aim was to develop and externally validate a dynamic prognostic nomogram for overall survival in eSTS survivors for use during follow-up.

Methods: All primary eSTS patients operated with curative intent between 1994 and 2013 at three European and one Canadian sarcoma centers formed the development cohort. Patients with Fédération Française des Centres de Lutte Contre le Cancer (FNCLCC) grade II and grade III eSTS operated between 2000 and 2016 at seven other European reference centers formed the external validation cohort. We used a landmark analysis approach and a multivariable Cox model to create a dynamic nomogram; the prediction window was fixed at five years. A backward procedure based on the Akaike Information Criterion was adopted for variable selection. We tested the nomogram performance in terms of calibration and discrimination.

Findings: The development and validation cohorts included 3740 and 893 patients, respectively. The variables selected applying the backward procedure were patient's age, tumor size and its interaction with landmark time, tumor FNCLCC grade and its interaction with landmark time, histology, and both local recurrence and distant metastasis (as first event) indicator variables. The nomogram showed good calibration and discrimination. Harrell C indexes at different landmark times were between 0.776 (0.761-0.790) and 0.845 (0.823-0.862) in the development series and between 0.675 (0.643-0.704) and 0.810 (0.775-0.844) in the validation series.

Interpretation: A new dynamic nomogram is available to predict 5-year overall survival at different times during the first three years of follow-up in patients operated for primary eSTS. This nomogram allows physicians to update the individual survival prediction during follow-up on the basis of baseline variables, time elapsed from surgery and first-event history.

Keywords: Dynamic prediction; Landmark analysis; Prognostic nomogram; Sarcoma; Soft tissue sarcoma: Survivors.

Fig. 1

Overall survival dynamic nomogram. Dynamic nomogram for 5-year overall survival (OS) in patients with primary resected eSTS. The nomogram allows the user to compute the 5-year survival probability on the basis of patient's age, tumor size, tumor grade, histology, occurrence of distant metastasis or occurrence of local recurrence as first events. The prediction can be calculated at baseline (time 0, at surgery) or post baseline (at 1 year, 2 years or 3 years after surgery). The prediction window is fixed at 5 years. Importantly, the choice of the proper size axis depends upon tumor grade and time at which the prediction is computed. For example, (i) to predict at time 0 (surgery) the 5-year OS of a 60 year-old patient with a 5 cm G3 MPNST, the user should locate patient's tumor size on the axis ‘Size cm (T = =0 mo, GIII)’ and draw a line straight upward to the “Points” axis to determine the score associated with that size and grade (55 points). Then repeat the process for patient's age at surgery (60 years = 6 points), histologic subtype (10 points), and sum the scores achieved for each covariate (sum=71 points). Locate this sum on the “Total Points” axis. Draw a line straight down to the “5-year survival probability, baseline” axis to find the predicted probability (about 78%). (ii) to predict 5-year OS of a patient with the same clinical characteristics as above but who had been operated two years before and has not had any events during the first two years of follow-up, the user should locate patient's tumor size on the axis ‘Size cm (T = =24 mo, GIII)’ and draw a line straight upward to the “Points” axis to determine the score associated with that size and grade (24 points). Then repeat the process for patient's age at surgery (60 years = 6 points), histologic subtype (10 points), local relapse (0 points), distant metastasis (0 points) and sum the scores achieved for each covariate (sum=40 points). Locate this sum on the “Total Points” axis. Draw a line straight down to the “5-year survival probability, post baseline” axis to find the predicted probability (about 94%). Histology abbreviations: (a), leiomyosarcoma; (b), pleomorphic/DD liposarcoma; (c), myxoid liposarcoma; (d), MPNST; (e), myxofibrosarcoma; (f), other; (g), synovial sarcoma; (h), UPS; (e), vascular sarcoma.

Fig. 2

Change in 5-year Overall Survival probability over time in different hypothetical clinical scenarios for individual patients. Five-year OS nomogram-predicted probabilities plotted against the time at which the prediction is computed. Line 1: uneventful follow-up. Line 2: occurrence of LR at 18 months. Line 3: occurrence of DM at 18 months. Panel A: 50-year-old patient operated for a 5 cm, GI, LMS. The predicted 5-year OS probability rises from 95.9% at baseline to 96.9% after two years of FU without events and to 97.4% after 3 years of FU without events. On the contrary, the prognosis of patients who develop LR or DM during FU drops significantly as compared to the baseline prediction, i.e. from 96.0% at 12 months to 72.1% at 24 months if the patient developed DM. At further uneventful follow-up, the 5-year survival probability will start to rise again. Panel B: 50-year-old patient operated for a 5 cm, GIII, LMS. The higher grade contributed to a global lowering of 5-year OS predictions. Lines 1–3 refer to the same event occurrences as in Panel A above. Abbreviations: OS, Overall Survival; LMS, leiomyosarcoma, LR: local relapse; DM, distant metastasis.

Fig. 3

Change in 5-year Overall Survival probability over time in different hypothetical clinical scenario. Five-year OS nomogram-predicted probabilities plotted against the time at which the prediction is computed. Line 1: uneventful follow-up. Line 2: occurrence of LR at 18 months. Line 3: occurrence of DM at 18 months. Panel A: 50 year-old patient operated for a 15 cm, GI, LMS. The predicted 5-year OS probability rises from 87.6% at baseline to 94.5% after two years of FU without events and to 96.1% after 3 years of FU without events. On the contrary, the prognosis of patients who develop LR or DM during FU drops significantly as compared to the baseline prediction, i.e., from 91.2% at 12 months to 55.8% at 24 months if the patient developed DM. At further uneventful follow-up, the 5-year survival probability will start to rise again. Panel B: 50 year-old patient operated for a 15 cm, GIII, LMS. Line 1: uneventful follow-up. Line 2: occurrence of LR at 18 months. Line 3: occurrence of DM at 18 months. Abbreviations: OS, Overall Survival; LMS, leiomyosarcoma, LR: local relapse; DM, distant metastasis.

Fig. 4

Calibration plots of the dynamic Overall Survival nomogram in the development and validation series. Five-year OS at baseline (A) and (E), 12 months (B) and (F), 24 months (C) and (G) and 36 months (D) and (H). Data are from the development cohort (A)–(D) and from the validation cohort (E)–(H). The nomogram predicted probabilities were stratified in equally sized subgroups. For each subgroup, the average nomogram-predicted probability (x-axis) was plotted against the Kaplan–Meier probability observed in the same subgroup (y-axis). The 95% CIs of the Kaplan–Meier estimates are indicated with vertical lines. The continuous line indicates the reference line, where an ideal nomogram would lie. Abbreviations: TLM, landmark time; OS, overall survival.