Gastrointestinal tumours, colorectal 2

LBA21 - Radioembolization with chemotherapy for colorectal liver metastases: A randomized, open-label, international, multicenter, phase III trial (EPOCH study)

Mary F. Mulcahy, et al.

Conclusions

EPOCH study met both primary endpoints, demonstrating the addition of TARE to systemic therapy for second-line colorectal liver metastases leads to significantly longer PFS and hPFS. Further subset analyses will better define the ideal patient population benefitting from TARE.

https://s3.eu-central-1.amazonaws.com/m-anage.com.storage.esmo/static/esmo2021_abstracts/LBA21.html.pdf

 

384O - Laparoscopic versus open hemihepatectomy: The ORANGE II PLUS multicenter randomized controlled trial

Robert S. Fichtinger, et al.

Conclusions

LH is superior to OH in terms of TFR and LOS. No significant differences in oncological outcomes were observed but follow-up continues to permit a mature survival analysis.

https://s3.eu-central-1.amazonaws.com/m-anage.com.storage.esmo/static/esmo2021_abstracts/384O.html.pdf

  

LBA22 - Neoadjuvant chemotherapy with oxaliplatin and capecitabine versus chemoradiation with capecitabine for locally advanced rectal cancer with uninvolved mesorectal fascia (CONVERT): Initial results of a multicenter randomised, open-label, phase III trial

Pei-Rong Ding, et al.

Conclusions

nCT achieved similar pCR and good downstaging rate with less peri-operative distance metastasis and preventive colostomy compared to nCRT. This regimen could serve as a potential alternative to CRT in LARC with uninvolved MRF. Long-term follow- up is needed to confirm these results.

https://s3.eu-central-1.amazonaws.com/m-anage.com.storage.esmo/static/esmo2021_abstracts/LBA22.html.pdf

 

385O - Automated detection of microsatellite status in early colon cancer (CC) using artificial intelligence (AI) integrated infrared (IR) imaging on unstained samples from the AIO ColoPredictPlus 2.0 (CPP) registry study

Frederik Großerüschkamp, et al.

Conclusions

QCL IR imaging combined with AI can automatically classify unstained tumour tissue accurately in 30 min with an AUC-ROC of 0.99. Further, it provides concurrently molecular tumour classification, as shown here for the MS. Based on the morphological and molecular alterations encoded in the IR images, AI models will be extended to issues such as prognosis and response

https://s3.eu-central-1.amazonaws.com/m-anage.com.storage.esmo/static/esmo2021_abstracts/385O.html.pdf