Virtual Library

 x 
My Library Virtual Library FAQ

Start Your Search

Shengping Wang



Author of

  • +

    JCSE01 - Joint IASLC-CSCO-CAALC Session (ID 63)

    • Event: WCLC 2019
    • Type: Joint IASLC-CSCO-CAALC Session
    • Track:
    • Presentations: 1
    • +

      JCSE01.18 - A CT-Based Radiomics Approach to Predict PD1 Inhibitor Response in Non-Small-Cell Lung Cancer (ID 3432)

      07:00 - 11:15  |  Author(s): Shengping Wang

      • Abstract
      • Slides

      Abstract
      Background
      The purpose of this study was to investigate the use of radiomics features as predictive parameters of clinical outcomes of non-small-cell lung cancer (NSCLC) patients treated with PD1 inhibitor.

      Methods
      Forty-three stage IIIB/IV NSCLC patients without EGFR mutation or ALK rearrangement who received nivolumab were enrolled between Apr 2016 and Jan 2019. High-dimensional quantitative feature analysis via Pyradiomics was applied to extract 852 radiomics features of pre-anti-PD1 treatment CT. A radiomic score model was constructed from these features with the use of least absolute shrinkage and selection operator (LASSO) Cox regression. The radiomic score for each patient was computed using an equation in which the coefficients were derived from the LASSO Cox model to subgroup patients by progression-free survival (PFS). The median value of radiomic score was used as the cut-off value to cluster patients into high or low score groups.

      Results
      We developed a radiomic signature for PFS that included seven variables. The median value of radiomic score was 0.23. The objective response rate (ORR) was 16.3% (7/43), the median PFS was 2 months and median overall survival (OS) was 3.2 months of all 43 patients. A low radiomic score was associated with a higher ORR (33.7% vs 0%, p= 0.0036), improved PFS (median: 3 months vs 2 months; HR 0.14, 95% CI   0.053-0.39, P < 0.0001) and longer OS (median: 11.2 months vs 7.0 months; HR 0.12, 95%CI 0.04-0.31, p < 0.0001). Multivariate analysis also showed that a low radiomic score was related to better PFS (HR 0.12, 95% CI   0.041-0.32, P < 0.0001) and OS (HR 0.11, 95%CI 0.03-0.28, p < 0.0001).



      Conclusion
      The radiomic signature as an imaging predictor provided a promising way to predict clinical outcomes for NSCLC patients treated with PD-1 inhibitor.

      Only Active Members that have purchased this event or have registered via an access code will be able to view this content. To view this presentation, please login or select "Add to Cart" and proceed to checkout.

  • +

    P1.01 - Advanced NSCLC (ID 158)

    • Event: WCLC 2019
    • Type: Poster Viewing in the Exhibit Hall
    • Track: Advanced NSCLC
    • Presentations: 1
    • Now Available
    • Moderators:
    • Coordinates: 9/08/2019, 09:45 - 18:00, Exhibit Hall
    • +

      P1.01-66 - A CT-Based Radiomics Approach to Predict PD1 Inhibitor Response in Non-Small-Cell Lung Cancer (Now Available) (ID 565)

      09:45 - 18:00  |  Author(s): Shengping Wang

      • Abstract
      • Slides

      Background

      The purpose of this study was to investigate the use of radiomics features as predictive parameters of clinical outcomes of non-small-cell lung cancer (NSCLC) patients treated with PD1 inhibitor.

      Method

      Forty-three stage IIIB/IV NSCLC patients without EGFR mutation or ALK rearrangement who received nivolumab were enrolled between Apr 2016 and Jan 2019. High-dimensional quantitative feature analysis via Pyradiomics was applied to extract 852 radiomics features of pre-anti-PD1 treatment CT. A radiomic score model was constructed from these features with the use of least absolute shrinkage and selection operator (LASSO) Cox regression. The radiomic score for each patient was computed using an equation in which the coefficients were derived from the LASSO Cox model to subgroup patients by progression-free survival (PFS). The median value of radiomic score was used as the cut-off value to cluster patients into high or low score groups.

      Result

      We developed a radiomic signature for PFS that included seven variables. The median value of radiomic score was 0.23. The objective response rate (ORR) was 16.3% (7/43), the median PFS was 2 months and median overall survival (OS) was 3.2 months of all 43 patients. A low radiomic score was associated with a higher ORR (33.7% vs 0%, p= 0.0036), improved PFS (median: 3 months vs 2 months; HR 0.14, 95% CI   0.053-0.39, P < 0.0001) and longer OS (median: 11.2 months vs 7.0 months; HR 0.12, 95%CI 0.04-0.31, p < 0.0001). Multivariate analysis also showed that a low radiomic score was related to better PFS (HR 0.12, 95% CI   0.041-0.32, P < 0.0001) and OS (HR 0.11, 95%CI 0.03-0.28, p < 0.0001).

      8.pic_hd.jpg

      Conclusion

      The radiomic signature as an imaging predictor provided a promising way to predict clinical outcomes for NSCLC patients treated with PD-1 inhibitor.

      Only Active Members that have purchased this event or have registered via an access code will be able to view this content. To view this presentation, please login or select "Add to Cart" and proceed to checkout.

  • +

    P1.13 - Staging (ID 181)

    • Event: WCLC 2019
    • Type: Poster Viewing in the Exhibit Hall
    • Track: Staging
    • Presentations: 1
    • Moderators:
    • Coordinates: 9/08/2019, 09:45 - 18:00, Exhibit Hall
    • +

      P1.13-03 - Lung Adenocarcinomas Manifesting as Radiological Part-Solid Nodules Define a Special Clinical Subtype (ID 35)

      09:45 - 18:00  |  Author(s): Shengping Wang

      • Abstract

      Background

      According to guidelines from the Fleischner Society in 2017, subsolid nodules are categorized into pure ground glass nodules (pGGNs) having only a GGO component and part-solid nodules having both GGO and solid components on thin-section computed tomography (TS-CT). Persistent part-solid nodules with solid components ≥ 6mm should be considered highly suspicious.Clinicopathologic features and prognostic predictors of radiological part-solid lung adenocarcinomas were unclear.

      Method

      We retrospectively compared clinicopathologic features and survivals of part-solid tumors with those of pure ground glass nodules (pGGNs) and pure solid tumors receiving surgery at Fudan University Shanghai Cancer Center, and evaluated prognostic implications of consolidation-to-tumor ratio (CTR), solid component size and tumor size for part-solid lung adenocarcinomas.

      figure 1副本.png

      Result

      911 patients and 988 pulmonary nodules (including 329 part-solid nodules (PSNs), 501 pGGNs & 158 pure solid nodules) were analyzed. More female patients (P=0.015) and non-smokers (P=0.003) were seen in PSNs than those in pure solid nodules. Prevalence of lymphatic metastasis was lower in PSNs than that in pure solid tumors (2.2% vs 27%, P=0.000). 5-year lung cancer specific recurrence free survival (LCS-RFS) and overall survival (OS) of PSNs were worse than those of pGGNs (P<0.001; P=0.042), but better than those of pure solid tumors (P<0.001; P<0.0001), respectively. CTR (OR: 12.90; 95% CI: 1.85-90.04), solid component size (OR: 1.45; 95% CI: 1.28-1.64) and tumor size (OR: 1.23; 95% CI: 1.15-1.31) could predict pathologic invasive adenocarcinoma for PSNs. None of them could predict the prognosis. Patients receiving sublobar resection had comparable prognoses with those receiving lobectomy (5-year LCS-RFS: P=0.178; 5-year LCS-OS: P=0.319). Prognostic differences between patients with systemic lymph node dissection (sLND) and those without sLND were statistically insignificant.

      Table1 Baseline clinicopathologic characteristics of objects in this study

      All

      N=988

      Part Solid nodule

      N=329

      Pure Ground Glass nodule

      N=501

      Pure Solid nodule

      N=158      		 P value
      Age (Mean±SD) 56.49±10.83 58.89±9.71 53.64±10.86 60.54±10.52 0.000
      Gender 0.015
      Male 277(30.4) 91 (28.9) 124 (28.2) 62 (39.5)
      Female 634(69.6) 224 (71.1) 315 (71.8) 95 (60.5)
      Smoking status 0.003
      Smoker 153(16.8) 52 (16.5) 62(14.1) 39(24.8)
      Non-smoker 758(83.2) 263(83.5) 377(85.9) 118(75.2)
      Tumor size(mm) 15.14±7.38 20.51±7.18 10.22±3.84 19.54±5.58 0.000
      Location 0.009
      RUL 364 (36.8) 126 (38.3) 197 (39.3) 41 (25.9)
      RML 67 (6.8) 21 (6.4) 29 (5.8) 17 (10.7)
      RLL 181 (18.3) 48(14.6) 93 (18.6) 40 (25.3)
      LUL 266 (26.9) 98 (29.8) 130 (25.9) 38 (24)
      LLL 110 (11.2) 36 (10.9) 52 (10.4 ) 22 (14.1)
      Surgery 0.000
      Wedge resection 456(46.2) 72(21.9) 370(73.8) 14(8.9)
      Segmentectomy 97(9.8) 33(10.0) 58(11.6) 6(3.8)
      Lobectomy 435(44.0) 224(68.1) 73(14.6) 138(87.3)
      Pathology 0.000
      AIS/MIA 509(51.5) 56(17.0) 447(89.2) 6(3.8)
      IAD 479(48.5) 273(83.0) 54(10.8) 152(96.2)
      Lepidic predominant 154(32.6) 104(38.8) 30(55.5) 30(55.5) 0.000
      Solid/Micropapillary predominant 21(4.5) 4(1.5) 1(1.9) 16(3.4) 0.000
      Acinar/Papillary predominant 290(61.4) 157(58.6) 22(40.7) 111(74.0) 0.000
      Mucinous adenocarcinoma 7(1.5) 3(1.1) 1(1.9) 3(2.0) 0.753
      Pathologic N status 0.000
      N0 904 (94.9) 305(97.8) 488 (100) 111(73)

      N1/2 48(5.1) 7(2.2) 0 (0) 41 (27)
      Conclusion

      Part-solid lung adenocarcinoma showed different clinicopathologic features compared with pure solid tumor. CTR, solid component size and tumor size could not predict the prognosis. Part-solid lung adenocarcinomas define one special clinical subtype.