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MRI-based deep learning model predicts distant metastasis and chemotherapy benefit in stage II nasopharyngeal carcinoma.

ABSTRACT: Chemotherapy remains controversial for stage II nasopharyngeal carcinoma because of its considerable prognostic heterogeneity. We aimed to develop an MRI-based deep learning model for predicting distant metastasis and assessing chemotherapy efficacy in stage II nasopharyngeal carcinoma. This multicenter retrospective study enrolled 1072 patients from three Chinese centers for training (Center 1, n = 575) and external validation (Centers 2 and 3, n = 497). The deep learning model significantly predicted the risk of distant metastases for stage II nasopharyngeal carcinoma and was validated in the external validation cohort. In addition, the deep learning model outperformed the clinical and radiomics models in terms of predictive performance. Furthermore, the deep learning model facilitates the identification of high-risk patients who could benefit from chemotherapy, providing useful additional information for individualized treatment decisions.

SUBMITTER: Hu YJ

PROVIDER: S-EPMC10291473 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature

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MRI-based deep learning model predicts distant metastasis and chemotherapy benefit in stage II nasopharyngeal carcinoma.

Hu Yu-Jun YJ Zhang Lin L Xiao You-Ping YP Lu Tian-Zhu TZ Guo Qiao-Juan QJ Lin Shao-Jun SJ Liu Lan L Chen Yun-Bin YB Huang Zi-Lu ZL Liu Ya Y Su Yong Y Liu Li-Zhi LZ Gong Xiao-Chang XC Pan Jian-Ji JJ Li Jin-Gao JG Xia Yun-Fei YF

iScience 20230519 6

Chemotherapy remains controversial for stage II nasopharyngeal carcinoma because of its considerable prognostic heterogeneity. We aimed to develop an MRI-based deep learning model for predicting distant metastasis and assessing chemotherapy efficacy in stage II nasopharyngeal carcinoma. This multicenter retrospective study enrolled 1072 patients from three Chinese centers for training (Center 1, n = 575) and external validation (Centers 2 and 3, n = 497). The deep learning model significantly pr ...[more]

PMID: 37378335

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Project description:PurposeThe value of adding induction chemotherapy to chemoradiotherapy in locoregionally advanced nasopharyngeal carcinoma (LA-NPC) remains controversial, yet high-risk patients with LA-NPC have poor outcomes after chemoradiotherapy. We aimed to assess the survival benefits of induction chemotherapy in stage IVa-b NPC.Patients and methodsA total of 602 patients with stage IVa-b NPC treated with intensity-modulated radiation therapy (IMRT) and concurrent chemotherapy with or without induction chemotherapy were retrospectively analyzed. Overall survival (OS), locoregional relapse-free survival (LRFS), distant metastasis-free survival (DMFS) and progression-free survival (PFS) were evaluated using the Kaplan-Meier method, log-rank test and Cox regression analysis.ResultsIn univariate analysis, 5-year OS was 83.2% for induction chemotherapy plus concurrent chemotherapy and 74.8% for concurrent chemotherapy alone, corresponding to an absolute risk reduction of 8.4% (P = 0.022). Compared to concurrent chemotherapy alone, addition of induction chemotherapy improved 5-year DMFS (83.2% vs. 74.4%, P = 0.018) but not 5-year LRFS (83.7% vs. 83.0%, P = 0.848) or PFS (71.9% vs. 66.0%, P = 0.12). Age, T category, N category, chemotherapy strategy and clinical stage were associated with 5-year OS (P = 0.017, P = 0.031, P = 0.007, P = 0.022, P = 0.001, respectively). In multivariate analysis, induction chemotherapy plus concurrent chemotherapy was an independent favorable prognostic factor for OS (HR, 0.62; 95% CI, 0.43-0.90, P = 0.012) and DMFS (HR, 0.57; 95% CI, 0.38-0.83, P = 0.004). In subgroup analysis, induction chemotherapy significantly improved 5-year DMFS in stage IVa (86.8% vs. 77.3%, P = 0.008), but provided no significant benefit in stage IVb.ConclusionsIn patients with stage IVa-b NPC treated with IMRT, addition of induction chemotherapy to concurrent chemotherapy significantly improved 5-year OS and 5-year DMFS. This study provides a basis for selection of high risk patients in future clinical therapeutic trials.

Project description:BackgroundPoor nutritional status is associated with progression and advanced disease in patients with cancer. The prognostic nutritional index (PNI) may represent a simple method of assessing host immunonutritional status. This study was designed to investigate the prognostic value of the PNI for distant metastasis-free survival (DMFS) in patients with nasopharyngeal carcinoma (NPC).MethodsA training cohort of 1,168 patients with non-metastatic NPC from two institutions was retrospectively analyzed. The optimal PNI cutoff value for DMFS was identified using the online tool "Cutoff Finder". DMFS was analyzed using stratified and adjusted analysis. Propensity score-matched analysis was performed to balance baseline characteristics between the high and low PNI groups. Subsequently, the prognostic value of the PNI for DMFS was validated in an external validation cohort of 756 patients with NPC. The area under the receiver operating characteristics curve (AUC) was calculated to compare the discriminatory ability of different prognostic scores.ResultsThe optimal PNI cutoff value was determined to be 51. Low PNI was significantly associated with poorer DMFS than high PNI in univariate analysis (P<0.001) as well as multivariate analysis (P<0.001) before propensity score matching. In subgroup analyses, PNI could also stratify different risks of distant metastases. Propensity score-matched analyses confirmed the prognostic value of PNI, excluding other interpretations and selection bias. In the external validation cohort, patients with high PNI also had significantly lower risk of distant metastases than those with low PNI (Hazards Ratios, 0.487; P<0.001). The PNI consistently showed a higher AUC value at 1-year (0.780), 3-year (0.793) and 5-year (0.812) in comparison with other prognostic scores.ConclusionPNI, an inexpensive and easily assessable inflammatory index, could aid clinicians in developing individualized treatment and follow-up strategies for patients with non-metastatic NPC.

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MRI-based deep learning model predicts distant metastasis and chemotherapy benefit in stage II nasopharyngeal carcinoma.

Publications

MRI-based deep learning model predicts distant metastasis and chemotherapy benefit in stage II nasopharyngeal carcinoma.

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