Background: Optimal surgical recovery is critical to readiness to return to intended oncologic therapy (RIOT). The current study defined the value of patient-reported outcomes (PROs) in predicting the risk for delayed RIOT after oncologic hepatic resection.
Methods: In a prospective longitudinal study, perioperative symptoms were assessed using a valid PRO assessment tool, the MD Anderson Symptom Inventory module for hepatectomy perioperative care (MDASI-PeriOp-Hep), for 4 weeks after surgery. The timed up and go test (TUGT) was administered before surgery, by discharge day, and at the first postoperative follow-up visit. Multivariate logistic regression analysis assessed the predictive value of PROs for delayed RIOT.
Results: We enrolled 210 patients and analyzed 148 patients who received adjuvant chemotherapy and contributed more than 3 PRO assessments postoperatively. About 36 percent of the patients had delayed RIOT (>5 weeks, range 1-14 weeks). MDASI scores for drowsiness, fatigue, dry mouth, and interference with general activity, walking, and work on day 7 after discharge and MDASI scores for incisional tightness, fatigue, dry mouth, shortness of breath, and interference with work on day 14 after discharge were associated with delayed RIOT (all P < 0.05). Walking and general activity items on the MDASI-Interference subscale on day 7 after discharge were highly correlated with prolonged TUGT scores at discharge (P < 0.01).
Conclusion: We defined clinically meaningful PROs on MDASI-PeriOp-Hep after hepatic resection that predicted increased risk of delayed RIOT. These findings highlight the importance PROs for monitoring symptoms and functioning 1-2 weeks after discharge to be implementing into perioperative care.
Keywords: Functional recovery; Liver surgery; MDASI; Patient-reported outcome; Perioperative care; Return to intended oncologic therapy; Symptom burden.
© 2024 Elsevier Ltd, BASO ∼ The Association for Cancer Surgery, and the European Society of Surgical Oncology. All rights are reserved, including those for text and data mining, AI training, and similar technologies.