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Pimpin Incharoen



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    P2.01 - Advanced NSCLC (Not CME Accredited Session) (ID 950)

    • Event: WCLC 2018
    • Type: Poster Viewing in the Exhibit Hall
    • Track:
    • Presentations: 1
    • Moderators:
    • Coordinates: 9/25/2018, 16:45 - 18:00, Exhibit Hall
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      P2.01-90 - PD-L1 Expression as a Predictive Biomarker in Advanced Non-Small Cell Lung Cancer Patients with or without EGFR Mutation (ID 13528)

      16:45 - 18:00  |  Author(s): Pimpin Incharoen

      • Abstract
      • Slides

      Background

      The prognostic value of PD-L1 expression and its clinical relevance of NSCLC is controversy. The impact of PD-L1 expression as the predictive biomarker for EGFR-TKIs treatment is needed to explore.

      a9ded1e5ce5d75814730bb4caaf49419 Method

      Medical records of metastatic NSCLC during September 2015-2016 had been reviewed. PD-L1 immunohistochemistry (IHC) staining with Antibody clone 22C3 was used. The PD-L1 positive was defined by tumor proportion score (TPS) > 1%.

      4c3880bb027f159e801041b1021e88e8 Result

      204 patients were included. Patients with positive PD-L1 expression had significantly increased numbers of metastatic sites (P=0.009) and lung metastasis (P=0.045) compared to PD-L1 negative patients. Overall survival (OS) was longer in PD-L1 negative patients (22.7 months) compared to PD-L1 positive groups (13.6 months) (HR=1.48; P=0.03). Median OS were significantly different with the number of 7.2, 11.1, 25.7, 42.6 months in EGFR-/PD-L1+, EGFR-/PD-L1-, EGFR+/PD-L1+ and EGFR+/PD-L1- , respectively (P<0.001). Among EGFR positive patients, mOS of T790M-/PD-L1+, T790M-/PD-L1-, T790M+/PD-L1-, and T790M+/PD-L1+ were 22.1, 28, 42.6 and 48.4 months, respectively (P=0.03).

      Patient characteristics categorized by PD-L1 expression (N = 204)
      Characteristics

      PD-L1 Negative

      N=134 (65.69%)

      PD-L1 Positive

      N=70 (34.31%)

      P value

      Age

      - Median age (range)

      - < 65 years

      - > 65 years

      65 (36-85)

      64 (47.76)

      70 (52.24)

      65 (35-86)

      33 (47.14

      37 (52.86)

      0.933

      Sex

      - Male

      - Female

      62 (46.27)

      72 )53.73)

      37 (52.86)

      33 (47.14)

      0.371

      ECOG PS

      - 0-1

      - > 2

      116 (86.57)

      18 (13.43)

      57 (82.61

      12 (17.39)

      0.452

      Smoking status

      - Never

      - Ex-smoker

      - Current smoker

      82 (61.65)

      36 (27.07)

      15 (11.28)

      36 (52.17)

      18 (26.09)

      15 (21.74)

      0.131
      Mean smoking pack-year (range) 29.72 (2-100) 25.68 (2-40) 0.873

      Initial staging

      - Recurrent

      - Denovo metastasis

      32 (23.88)

      102 (76.12)

      14 (20)

      56 (80)

      0.529

      Histology

      - Adenocarcinoma

      - Squamous cell carcinoma

      - Adenosquamous carcinoma

      - Others

      117 (87.31)

      1 (0.75)

      2 (1.49)

      14 (10.45)

      58 (84.06)

      3 (4.35)

      2 (2.9)

      6 (8.7)

      0.288

      EGFR mutation

      - Negative

      - Positive

      47 (35.07)

      87 (64.93)

      32 (45.71)

      38 (54.29)

      0.092

      Exon 19 deletion

      - No

      - Yes

      87 (64.93)

      47 (35.07)

      50 (71.43)

      20 (28.57)

      0.348

      L858R

      - No

      - Yes

      100 (74.63)

      34 (25.37)

      53 (75.71)

      17 (24.29)

      0.865

      ALK results

      - Negative

      - Positive

      79 (92.94)

      6 (7.06)

      47 (97.92)

      1 (2.08)

      0.421

      Number of site of metastasis

      - 0-1

      - > 2

      88 (65.67)

      46 (34.33)

      37 (52.86)

      33 (47.14)

      0.009

      Lung metastasis

      - No

      - Yes

      92 (69.17)

      41 (30.83)

      38 (54.29)

      32 (45.71)

      0.045

      Bone metastasis

      - No

      - Yes

      101 (75.37)

      33 (24.63)

      53 (75.71)

      17 (24.29)

      0.957

      Liver metastasis

      - No

      - Yes

      122 (91.04)

      12 (8.96)

      62 (88.57)

      8 (11.43)

      0.573

      Pleural metastasis

      - No

      - Yes

      91 (67.91)

      43 (32.09)

      62 (88.57)

      20 (28.57)

      0.606

      Brain metastasis

      - No

      - Yes

      117 (87.31)

      17 (12.69)

      58 (82.86)

      12 (17.14)

      0.387

      Adrenal metastasis

      - No

      - Yes

      122 (91.04)

      12 (8.96)

      62 (88.57)

      8 (11.43)

      0.573

      figure pd-l1.jpg

      8eea62084ca7e541d918e823422bd82e Conclusion

      PD-L1 expression was associated with poorer survival outcomes among advanced NSCLC patients regardless of EGFR mutation status. PD-L1 expression is also the potential of predictive biomarker for EGFR TKIs treatment. The larger studies are needed to identify the prognostic and predictive values in T790M mutation population.

      6f8b794f3246b0c1e1780bb4d4d5dc53

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    P3.09 - Pathology (Not CME Accredited Session) (ID 975)

    • Event: WCLC 2018
    • Type: Poster Viewing in the Exhibit Hall
    • Track:
    • Presentations: 3
    • Moderators:
    • Coordinates: 9/26/2018, 12:00 - 13:30, Exhibit Hall
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      P3.09-08 - Tumor Heterogeneity and Molecular Profile of NSCLC in Thai Population (ID 14016)

      12:00 - 13:30  |  Author(s): Pimpin Incharoen

      • Abstract
      • Slides

      Background

      Oncogenic driven mutation is the key to develop targeted therapy in lung cancer. Different ethnicity and tumor heterogeneity affect the prevalence of molecular alteration. This study aimed to explore the unique molecular profile of lung adenocarcinoma in Thai population.

      a9ded1e5ce5d75814730bb4caaf49419 Method

      We studied 166 lung adenocarcinoma patients’ molecular profile using Next Generation Sequencing (NGS) on 45 genes lung cancer panel (Ion Torrent system). Variants from NGS with coverage of higher than 1000X and cut off at 2% alternate variant frequency were considered positive. We validated the positive mutation of EGFR, BRAF, and KRAS by Real- Time PCR using the Amoy DX kit.

      4c3880bb027f159e801041b1021e88e8 Result

      This study found 68%(113/166) of EGFR mutation, 9.6%(16/166) of BRAF V600E, 32.5% (54/166) of KRAS mutation, 9%(15/166) of MET exon14 splice site, 4.8% (8/166) AKT mutation (E17K), 2.4% (4/166) of ROS1 mutation, 0.6% (1/166) of PIK3CA mutation (H1047R), and 0.6% (1/166) of PTEN mutation. Furthermore, we also found 40 patients (24.1%) who had more than one mutation in each person. We further validated the positive results by Real-Time PCR. Thirteen patients were obtained tissue from different organs and some with different period of time. T790M usually develop later in EGFR-positive patients who failed 1st or 2nd generation EGFR-TKI. Two patients (patient 5&9) who had lung surgery different lobe in same operation, had different mutation in tissues and one patient (patient 13) who obtained tissue from lung and pleural effusion cell block in different period of time had totally different mutation (Table1).

      Table1 Tumor heterogeneity profile in lung cancer patients

      case

      Hetrogenety in different organ

      date obtained tissue

      Gene mutation

      EGFR

      KRAS

      ROS

      PTEN

      AKT

      MET

      BRAF

      1

      RLL lobectomy

      12-Jun-2012

      Exon 19 Deletion

      negative

      negative

      negative

      negative

      negative

      negative

      Right lung

      4-May-2016

      Exon 19 Deletion T790M

      negative

      negative

      negative

      negative

      negative

      negative

      2

      lymph node

      16-Mar-2017

      negative

      negative

      negative

      negative

      negative

      negative

      negative

      Bone

      9-Apr-2017

      negative

      negative

      negative

      negative

      negative

      negative

      negative

      3

      Right upper lung biopsy

      20-Jan-2016

      Exon 19 Deletion

      negative

      negative

      negative

      negative

      negative

      negative

      Lung biopsy

      31-Mar-2017

      T790M

      negative

      negative

      negative

      E17K

      negative

      negative

      4

      lymph node

      13-Jan-2016

      negative

      G12A

      negative

      negative

      negative

      negative

      negative

      skin

      17-Jan-2016

      negative

      G12V G12D

      negative

      negative

      negative

      negative

      negative

      left humerous

      30-Jun-2016

      negative

      G12V

      negative

      negative

      negative

      negative

      negative

      5

      RML lobectomy

      13-Nov-2013

      Exon 19 Deletion

      G13D

      negative

      negative

      negative

      negative

      negative

      LUL lobectomy

      14-May-2014

      negative

      G12D G13D

      negative

      R233*

      negative

      negative

      negative

      LUL lobectomy

      14-May-2014

      negative

      G12V G12D

      D2033N

      negative

      negative

      negative

      negative

      6

      Right pleura biopsy

      11-Jan-2016

      Exon 19 Deletion

      negative

      negative

      negative

      negative

      negative

      negative

      RUL biopsy

      1-Mar-2017

      Exon 19 Deletion

      negative

      negative

      negative

      negative

      negative

      negative

      7

      RUL biopsy

      28-Sep-2015

      L858R

      negative

      negative

      negative

      negative

      negative

      negative

      Left pleural fluid cell block

      27-Jun-2016

      negative

      negative

      negative

      negative

      negative

      negative

      negative

      8

      Right pleural fluid cell block

      25-Mar-2016

      Exon 19 Deletion

      negative

      negative

      negative

      negative

      negative

      negative

      Left pleural fluid cell block

      9-Dec-2016

      T790M

      negative

      negative

      negative

      negative

      negative

      negative

      9

      RML lobectomy

      14-Mar-2013

      negative

      G13S

      negative

      negative

      E17K

      negative

      negative

      RLL wedge resectionRLL lo

      30-Mar-2017

      G719A L861Q

      negative

      negative

      negative

      negative

      negative

      negative

      10

      RLL lobectomy

      26-Aug-2013

      negative

      G12C G12D

      negative

      negative

      negative

      negative

      negative

      Left lingular lobe segmental resection

      9-Oct-2014

      negative

      G12D

      negative

      negative

      negative

      negative

      negative

      LUL wedge resection

      11-Feb-2016

      negative

      G12D

      negative

      negative

      negative

      negative

      negative

      LUL lobectomy

      4-Jun-2017

      negative

      G12D

      negative

      negative

      negative

      negative

      negative

      LLL resection

      9-Oct-2014

      negative

      G12D

      negative

      negative

      negative

      negative

      negative

      11

      Right pleural cell block

      21-Jul-2014

      L858R

      negative

      negative

      negative

      negative

      c.3028G>A exon 14 splicing

      negative

      Ascites

      9-Jun-2017

      T790M L858R

      negative

      negative

      negative

      negative

      negative

      negative

      12

      LUL biopsy

      24-Feb-2015

      L858R

      negative

      negative

      negative

      negative

      negative

      V600E

      Lt lung biopsy

      8-Jul-2016

      L858R

      negative

      negative

      negative

      negative

      negative

      negative

      13

      RLL biopsy

      14-Oct-2015

      negative

      negative

      negative

      negative

      negative

      c.3028+1G>T exon 14 splicing

      negative

      pleural fluid cell block

      15-Nov-2016

      Exon 19 Deletion T790M

      negative

      negative

      negative

      negative

      negative

      negative

      8eea62084ca7e541d918e823422bd82e Conclusion

      Thai populations have unique molecular alteration compared to the other ethnicities, especially, higher of BRAF V600E and MET exon14 splice site. Our population also has high co-mutation prevalence. Tumor heterogeneity is needed to explore in the larger cohort.

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      P3.09-10 - Circulating Cell-Free DNA (cfDNA) Molecular Profile of Thai NSCLC Patients Using Difference Variant Frequency of NGS (ID 13744)

      12:00 - 13:30  |  Author(s): Pimpin Incharoen

      • Abstract
      • Slides

      Background

      Detecting cfDNA in the liquid biopsy has become a promising method to explore the genetic landscape of tumor heterogeneity. We developed a pilot-study to find the suitable cutoff of variant frequencies detected from liquid biopsy by NGS to track tumor-associated mutations in NSCLC patients.

      a9ded1e5ce5d75814730bb4caaf49419 Method

      Ninety-four samples (24 early-stage NSCLC, 70 late-stage NSCLC) were collected from Ramathibodi Hospital, Thailand. Profiling cfDNA using Ion Proton NGS platform. Overall average base coverage depth from NGS was 10,000x, all variants selected have read depths >10x in order to reach 0.1% sensitivity. Each of selected variants has threshold variant quality (QUAL) >20. Droplet digital PCR (ddPCR) was performed for EGFR-mutation testing to determine the appropriated cutoff variant frequency from NGS.

      4c3880bb027f159e801041b1021e88e8 Result

      In early-stage NSCLC, a minimum-threshold variant frequencies at 0.1% could detect EGFR exon19 deletion in all samples (24,100%), with BRAF (12,50%), KRAS (21,87.5%) and other mutations in AKT1, MET, PIK3CA, PTEN, ROS1 (14,58%). None of these mutations identified when using conventional level cutoff at 3% (Table1). ddPCR observed EGFR-mutations in 2 early-stage cases only (8.3%). In late-stage NSCLC, 64 (91.4%) cases were observed multiple mutations, suggesting tumor heterogeneity. At 0.1% cutoff in NGS, Thirty-six (52.9%) cases of EGFR-mutations in NGS and ddPCR were identical. Thirteen (18.6%) samples shown partial discrepancies in the mutations. Interestingly, NGS found EGFR-mutations in 20 (28.6%) samples which ddPCR failed to detect, 12 of them contained T790M. Only one sample (1.4%) using 0.1% cutoff was unable to detect EGFR-mutation. Higher variant allele frequencies were found in EGFR-positive detected by ddPCR compared to not-detected by ddPCR.

      Table1
      Mutations detected variant allele frequencies detected from liquid biopsy by NGS at minimum threshold cut-off 0.1% variant allele frequencies detected from liquid biopsy by NGS at minimum threshold cut-off 0.1% variant allele frequencies detected from liquid biopsy by NGS at conventional level detection of somatic variants cut-off 3% variant allele frequencies detected from liquid biopsy by NGS at conventional level detection of somatic variants cut-off 3% variant allele frequencies detected from liquid biopsy by ddPCR (EGFR only) variant allele frequencies detected from liquid biopsy by ddPCR (EGFR only)
      N (%) median (range) N (%) median (range) N (%) median (range)
      BRAF (V600E) early stage total N=24 12 (50%) 0.8 (0.3-2.5) 0 (0%) 0 NA NA
      BRAF (V600E) late stage total N=70 11 (15.7%) 0.6 (0.1-1.1) 0 (0%) 0 NA NA
      KRAS early stage 21 (87.5%) 0.1 (0.1-0.5) 0 (0%) 0 NA NA
      KRAS late stage 50 (71.4%)

      0.2

      (0.1-13.6)

      3 (4.3%) 11.1 (5.8-14.3) NA NA
      AKT1 (E17K) early stage 7 (29.2%) 0.1 (0.1-0.7) 0 (0%) 0 NA NA
      AKT1 (E17K) late stage 12 (17.1%) 0.1 (0.1-0.7) 0 (0%) 0 NA NA
      MET exon 14 splicing early stage

      4 (16.7%)

      0.1 (0.1-0.1) 0 (0%) 0 NA NA
      MET exon 14 splicing late stage 3 (4.3%) 0.2 (0.2-0.2) 0 (0%) 0 NA NA
      PIK3CA early stage 9 (37.5%) 0.2 (0.1-0.8) 0 (0%) 0 NA NA
      PIK3CA late stage 19 (27.1%) 0.3 (0.1-0.7) 0 (0%) 0 NA NA
      PTEN (R233*) early stage 6 (25.0%) 0.1 (0.1-0.4) 0 (0%) 0 NA NA
      PTEN (R233*) late stage 11 (15.7%) 0.1 (0.1-0.2) 0 (0%) 0 NA NA

      ROS1

      early stage 0 (0%) 0 0 (0%) 0 NA NA

      ROS1

      late stage 4 (5.7%)

      0.55

      (0.1-0.7)

      0 (0%) 0 NA NA

      EGFR

      Exon 19 Deletion

      early stage 24 (100%)

      0.35

      (0.1-2.1)

      0 (0%) 0 1 (4.2%) 0.5 (0.5-0.5)

      EGFR

      Exon 19 Deletion

      late stage 25 (35.7%)

      0.6

      (0.1-49.0)

      6 (8.6%) 9.4 (4.5-49.5) 20 (28.6%) 0.65 (0-49.0)
      EGFR L858R early stage 5 (20.8%) 0.2 (0.1-0.5) 0 (0%) 0 0 (0%) 0
      EGFR L858R late stage 21 (30%) 1.4 (0.1-9.7) 4 (5.7%) 4.6 (4.4-6.4) 14 (20%) 1.8 (0.3-9.7)
      EGFR T790M early stage 8 (33.3%) 0.1 (0.1-0.2) 0 (0%) 0 0 (0%) 0
      EGFR T790M late stage 30 (42.9%) 0.1 (0.1-4.6) 2 (2.9%) 7.5 (5.3-9.7) 16 (22.9%) 0.15 (0-4.1)
      EGFR Exon18 (G719X) early stage 6 (25%) 0.2 (0.1-0.4) 0 (0%) 0 1 (4.2%) 0.4 (0.4-0.4)
      EGFR Exon18 (G719X) late stage 4 (5.7%)

      4.5

      (0.1-49.2)

      2 (2.9%)

      27.9

      (6.7-49.2)

      2 (2.9%) 25.6 (2-49.2)
      EGFR Exon 20 Insertion early stage 0 (0%) 0 0 (0%) 0 0 (0%) 0
      EGFR Exon 20 Insertion late stage 1 (1.4%)

      73.8

      (73.8-73.8)

      1 (1.4%)

      91.7

      (91.7-91.7)

      0 (0%) 0

      8eea62084ca7e541d918e823422bd82e Conclusion

      Detecting variant frequencies at 0.1% could reveal more hidden tumor-associated mutations compared to variant frequency cutoff at 3%. With a careful validation, profiling cfDNA using NGS can be a crucial method to accurately select treatment for NSCLC patients in the future.

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      P3.09-19 - Matched Thai Lung Cancer Patients Tissue and cfDNA Molecular Profile by NGS (ID 14341)

      12:00 - 13:30  |  Author(s): Pimpin Incharoen

      • Abstract
      • Slides

      Background

      Liquid biopsy is the new non-invasive technology to explore the molecular profile. We evaluate molecular alteration from matched tissue and liquid specimen in NSCLC patients using NGS.

      a9ded1e5ce5d75814730bb4caaf49419 Method

      A total 61 matched tumors and cfDNA in NSCLC patients were retrieved for DNA extraction. All qualified samples were analyzed by using Next Generation Sequencing (NGS) with Gene read Qiagen Lung Cancer Panel sequencing 45 Genes on Ion Torrent system.Variants from NGS with coverage of higher than 1000X of tissues and 10000X of liquid biopsy, cutoff at 3% variant frequency were considered positive. Each detected mutation was validated by the different method. EGFR-mutation detected at this cutoff was validated by Real-time PCR technique using the ARMS-PCR (Amoy DX Kit) for tissue samples and droplet-digital PCR (ddPCR) for blood samples in all samples.

      4c3880bb027f159e801041b1021e88e8 Result

      This study found 59.0% and 19.7% of EGFR mutation, 14.75% and 8.20% of KRAS mutation in tissues and cfDNA, respectively. Moreover, we found 3.29% of BRAF V600E, 1.64% of MET exon14 splice site, and 1.64% of ROS1 mutation in tissue NGS and also confirmed by the other techniques, but there was none of these mutations in the blood sample. Looking at EGFR-mutation detected by different techniques, higher sensitivity, specificity, positive-predictive value, negative-predictive values, and concordant rate were found in tissue NGS and liquid ddPCR compared with liquid NGS at cutoff 3% of variant frequency detection, when the gold standard for validation was ARMS-PCR in tissue testing (Table1).

      Table1. Performance of NGS, ARMS and ddPCR for EGFR mutation detection in matched tissue and cfDNA in lung cancer patients.

      Tissue by ARMS PCR

      Result

      Tissues by NGS

      negative

      positive

      total

      Sensitivity= 87.7%

      negative

      14

      11

      25

      Specificity= 100%

      positive

      0

      36

      36

      Positive predictive value= 100%

      Total

      14

      47

      61

      Negative predictive value= 75.6%

      Concordance = 82%

      Tissue by ARMS PCR

      cfDNA by NGS

      negative

      positive

      total

      Sensitivity= 35.7%

      negative

      12

      37

      49

      Specificity= 98.2%

      positive

      2

      10

      12

      Positive predictive value= 97.9%

      Total

      14

      47

      61

      Negative predictive value= 38.9%

      Concordance = 42.6%

      Tissue by ARMS PCR

      cfDNA by ddPCR

      negative

      positive

      total

      Sensitivity= 82.7%

      negative

      14

      14

      28

      Specificity= 100%

      positive

      0

      33

      33

      Positive predictive value= 100%

      Total

      14

      47

      61

      Negative predictive value= 69.4%

      Concordance = 77.05%

      Tissue by NGS

      cfDNA by NGS

      negative

      positive

      total

      Sensitivity= 36%

      negative

      20

      29

      49

      Specificity= 93.2%

      positive

      5

      7

      12

      Positive predictive value= 84.8%

      Total

      25

      36

      61

      Negative predictive value= 55.8%

      Concordance = 60.66%

      cfDNA by ddPCR

      cfDNA by NGS

      negative

      positive

      total

      Sensitivity= 45.5%

      negative

      25

      24

      49

      Specificity= 97.7%

      positive

      3

      9

      12

      Positive predictive value= 94.5%

      Total

      28

      33

      61

      Negative predictive value= 65.6%

      Concordance = 65.58%

      8eea62084ca7e541d918e823422bd82e Conclusion

      Using tissue for molecular profile testing is still being the gold standard testing. Liquid biopsy is less invasive, but in our study, liquid NGS performed less sensitivity, specificity, PPV, NPV, and concordance rate compared with tissue NGS. We need to explore more for proper cutoff of variant allele frequency to develop more sensitivity and specificity of liquid NGS.

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    P3.15 - Treatment in the Real World - Support, Survivorship, Systems Research (Not CME Accredited Session) (ID 981)

    • Event: WCLC 2018
    • Type: Poster Viewing in the Exhibit Hall
    • Track:
    • Presentations: 1
    • Moderators:
    • Coordinates: 9/26/2018, 12:00 - 13:30, Exhibit Hall
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      P3.15-24 - Ramathibodi Lung Cancer Consortium (RLC) Model: Multidisciplinary Team Approach Improves Lung Cancer Patients’ Survival Outcome (ID 14396)

      12:00 - 13:30  |  Author(s): Pimpin Incharoen

      • Abstract
      • Slides

      Background

      Technologies for investigation, diagnosis, and treatment for lung cancer are advance to improve patients’ survival. Many investigations will be performed once the patients were suspected to have lung cancer. All processes sometime take a long time to complete investigations before starting the treatment which may affect treatment outcomes.

      a9ded1e5ce5d75814730bb4caaf49419 Method

      Ramathibodi Lung Cancer Consortium (RLC) was established in October 2014, aims to help the patients accessing all investigations and treatments faster by multidisciplinary team (MDT) approach and patient-center with one-stop service system. We conduct RLC meeting every 1st and 3rd Tuesday of the month. As of May 2017, 200 new lung cancer patients were solved all problems by RLC team. We collected and analyzed the data of lung cancer patients between 2 groups. The first group was the patient whom underwent RLC model (160 cases) and the second group was control group which was the patient whom diagnosed before establishing RLC (72 cases). Our primary endpoint was time from first visit to first treatment. Secondary endpoints were time from first visit to first interventions, number visits from first visit to first treatment, and overall survival (OS). We also did subgroups analysis for time from first visit to first biopsy, to first imaging study, to surgery, to chemotherapy, and to radiation.

      4c3880bb027f159e801041b1021e88e8 Result

      Median time from first visit to first treatment was significantly decreased in RLC group (14 days) compared to 57 days in control group with HR of 2.86 (95% CI; 2.11-3.87, P<0.001). Median time from first visit to first intervention was also significantly decreased in RLC group (2 days) compared to 11 days in control group with HR of 2.01 (95% CI; 1.53-2.62, P<0.001). Median number of hospital visits was significantly lower in RLC group (1 visits) compared to control group (8 visits). All subgroup analyses showed significantly decreased duration of each investigation and each treatment in RLC group. In survival analysis, lung cancer patients whom underwent RLC model had significantly longer mOS compared to control group, especially in stage 3 and 4 disease [mOS = 2.4 vs 0.8 years, HR=0.42 (95% CI; 0.3-0.7, P<0.001)].

      8eea62084ca7e541d918e823422bd82e Conclusion

      RLC model is a very useful model helping lung cancer patients to access treatment and investigations in short period of time and translate to have significantly longer survival. RLC model also provides the cooperation in lung cancer research. This model should be applied for all cancers treatment. Working as MDT is the utmost importance for cancer treatment.

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