| Unique ID issued by UMIN | UMIN000048869 |
|---|---|
| Receipt number | R000055693 |
| Scientific Title | Exploratory integrated analysis to build a pathologic finding, recurrence, survival predicting algorithm using artificial intelligence from clinical factors and image finding on thin-section computed tomography in patients with clinical stage IA non-small cell lung cancer |
| Date of disclosure of the study information | 2022/09/07 |
| Last modified on | 2022/09/07 12:03:47 |
Exploratory integrated analysis to build a pathologic finding, recurrence, survival predicting algorithm using artificial intelligence from clinical factors and image finding on thin-section computed tomography in patients with clinical stage IA non-small cell lung cancer
AI PREDICTION
Exploratory integrated analysis to build a pathologic finding, recurrence, survival predicting algorithm using artificial intelligence from clinical factors and image finding on thin-section computed tomography in patients with clinical stage IA non-small cell lung cancer
AI PREDICTION
| Japan |
Non-small cell lung cancer
| Chest surgery |
Malignancy
NO
To develop the prediction model of cancer recurrence or pathological findings in lung cancer patients with stage I NSCLC.
Efficacy
Diagnostic sensitivity and specificity of prediction of cancer recurrence by artificial intelligence prediction model.
Observational
| 20 | years-old | <= |
| 80 | years-old | >= |
Male
Cohort 1
Satisfy one of the following.
1) Registered and eligible in JCOG0802/WJOG4607L
2) Registered and eligible in JCOG0804/WJOG4507L
3) Registered and eligible in JCOG1211.
Cohort 2
All of the following items are satisfied.
1) Non-small cell lung cancer (excluding low-grade malignant tumors) operated at the Department of Thoracic Surgery, National Cancer Center Hospital East from January 2003 to December 2014.
2) Performance status (PS) is 0 or 1 according to ECOG criteria.
3) Complete pathological resection.
4) 80 years old or younger at the time of surgery.
5) Clinical stage 0-IB.
6) Preoperative thin-section CT (with or without contrast enhancement, slice thickness: 10 mm or less) can be obtained by the research office.
7) Written informed consent has been obtained from the survivors to participate in this study.
Cohort 1
1) No thin-section image of the main tumor in CT images submitted for central image review
Cohort 2
1) A history of other cancers at the time of surgery.
2) Multiple lung cancers were observed at the time of surgery.
3) Preoperative treatment was performed.
4) The purpose of the surgery was biopsy or sublobar resection for compromised patients.
5) Insufficient data in the medical record required for this ancillary study.
3129
| 1st name | Masahiro |
| Middle name | |
| Last name | Tsuboi |
National cancer center hospital East
Department of thoracic surgery
277-8577
6-5-1, Kashiwanoha, Kashiwa, Chiba, Japan
0471331111
kaokage@east.ncc.go.jp
| 1st name | Keiju |
| Middle name | |
| Last name | Aokage |
National cancer center hospital East
Department of thoracic surgery
277-8577
6-5-1, Kashiwanoha, Kashiwa, Chiba, Japan
0471331111
kaokage@east.ncc.go.jp
JCOG
AstraZeneca
Profit organization
M3 Inc.
National Cancer Center Hospital, East, Japan
6-5-1, Kashiwanoha, Kashiwa, Chiba, Japan
0471331111
irst@ncc.go.jp
NO
国立がん研究センター東病院
| 2022 | Year | 09 | Month | 07 | Day |
Unpublished
Preinitiation
| 2022 | Year | 09 | Month | 06 | Day |
| 2022 | Year | 09 | Month | 06 | Day |
| 2022 | Year | 09 | Month | 06 | Day |
| 2025 | Year | 12 | Month | 31 | Day |
none
| 2022 | Year | 09 | Month | 07 | Day |
| 2022 | Year | 09 | Month | 07 | Day |
Value
https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000055693