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Rectal Cancer Tweetorial!! Rectal cancer is a highly heterogeneous disease with rapid evolution in practice. Let's review current data to generate a pragmatic, patient-centric, approach to management! #GI24#GIonc#RadOnc Thank you @ASCO for the opportunity!🙏🏽 1/
✅Pre-operative RT reduces the risk of pelvic recurrence for patients with rectal cancer. But some patients will suffer from acute and long term toxicity (bladder, bowel, sexual, endocrine dysfunction) ❓How can we tailor therapy to balance QoL & cancer control?
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Rectal cancer is highly heterogeneous with a broad spectrum of risk for both pelvic and distant recurrence. 🔥🔥🔥 Understanding risk of recurrence is critical in clinical decision making! 3/
Which pts may omit RT? Mercury, OCUM, and Quicksilver included pts with predominately mid-upper rectal cancers, T2-3bN0, clear MRF, and no EMVI Patients treated with up-front surgery
Chemotherapy only for pN+ patients ✅ < 5% + margins
✅< 5% 5-year pelvic recurrence
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For pts with favorable risk cT3N0-1/cT2N1 rectal cancer amenable to LAR, PROSPECT compared: LC-CRT
vs
Pre-op chemo +/- selective CRT Study found no detriment in:
✅Local control
✅Disease free survival
✅Overall survival BUT
🔺 pre-op toxicity with FOLFOX
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The study included robust collection of PROs which demonstrated: There were substantial differences in acute PROs favoring CRT but
✅ No difference in overall QoL
✅ RT omission did better preserve sexual function
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Based upon these data, RT may be safely omitted in patients with favorable risk LARC, including those with: ✅Tumors in the mid-upper rectum
✅cT2-3
✅Clear MRF
✅N0-1, limited to the mesorectum
✅Planned for surgery with a LAR 7/
What about high-risk rectal cancer? RAPIDO included pts with T4, cN2, +EMVI, +MRF, or +LPNs.
Randomized:
CRT (Adj chemo optional: 42% received)
vs.
Intensified TNT regimen of SC-RT➡️FOLFOX. Key results improved with TNT:
✅⬇️Disease related treatment failure
✅Decreased DM
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PRODIGE 23 included pts with cT3-4 disease Randomized:
CRT➡️FOLFOX
vs.
mFOLFIRINOX ➡️CRT➡️S ➡️FOLFOX Key results improved with TNT!
✅Improved DFS
✅Decreased DM
✅✅✅Improved OS!!!
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PROSPECT, CONVERT, and FOWARC suggest there is a subset of pts with LARC effectively treated with pre-op FOLFOX without RT However, these studies had limited representation of high risk disease‼️ 🔥 TNT, inclusive of RT, is preferred for patients with high risk disease!
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Let’s summarize! 🟢cT3a-bN0 tumors in the mid-upper rectum amenable to LAR with no additional risk factors ➡️ consider RT omission. 🔴High-risk rectal cancer (cT4, N2, + MRF, LPLNs, EMVI) ➡️ TNT 11/
The intermediate risk cohort is much more nuanced! 🟡 Isolated N1, limited to mesorectum
➡️ Consider pre-operative chemotherapy with omission of RT
🟠 Additional pelvic risk factors (T3c-d, tumor deposits, EMVI, distal tumor)
➡️ Favor addition of RT
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Let’s discuss SC-RT vs. LC-CRT SCRT= similar LC, DFS, OS in prior studies of “average risk” patients. 🔥RAPIDO= high risk: ⬆️ pelvic recurrence (10% vs. 6%) with SC-TNT vs. LC-CRT. LC-CRT may be preferred for patients with high-risk rectal cancer 13/
Organ preservation❓❓ Goal= Preserve QoL and Function LAR resulting in a low/coloanal anastomosis associated with poor bowel function RT + Surgery is associated with poorer function
🔴Bowel
🔴Bladder
🔴Sexual ✅ Omission of surgery may better preserve function 14/
Let's review sequence of therapy!! OPRA: ~50% may achieve long term organ preservation‼️ CRT ➡️chemo sequence vs. chemo ➡️ CRT:
✅⬇️ local regrowth and
✅⬆️ organ preservation with CRT➡️chemo
✅No difference in DFS or DFS after TME (initial iCR or regrowth) 15/
How can we improve cCR and organ preservation❓ RT perspective: OPERA Trial
54 Gy/30 Fx CRT
vs.
45 Gy/25 Fx CRT + Brachy boost (90 Gy/3 Fx) ✅Brachy= 3-year organ preservation: 81% vs. 59%
✅No detriment in severe toxicity or function! Supports RT dose intensification‼️ 16/
Key conclusions‼️ 🔵 RT may be omitted in patients with MRI defined- favorable risk disease
🔵 TNT preferred for high risk disease
🔵 Organ preservation better preserves QoL and function
🔵CRT➡️chemo sequence preferred for NOM 🚨 LARC Algorithm here! 👆🏽 For discussion!
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