Predicting Complete Response to Neoadjuvant Chemotherapy in Muscle-Invasive Bladder Cancer.
Hiroko MiyagiElizabeth P KwendaBrian H RamnaraignJonathan A ChatzkelWayne G BrisbanePadraic O'MalleyPaul L CrispenPublished in: Cancers (2022)
Muscle-invasive bladder cancer is a life-threatening disease best managed with multimodal therapy. Neoadjuvant chemotherapy prior to cystectomy significantly improves survival with the greatest benefit noted in patients with a complete pathologic response noted at cystectomy. While radical cystectomy is currently an important part of the treatment plan, surgical morbidity remains high. Accurate prediction of complete responses to chemotherapy would enable avoiding the morbidity of radical cystectomy. Multiple clinical, pathologic, molecular, and radiographic predictors have been evaluated. Clinical and standard pathologic findings have not been found to be accurate predictors of complete response. To date, tumor genomic findings have been the most promising and have led to multiple clinical trials to evaluate if bladder preservation is possible in select patients. Radiomics has shown initial promise with larger validation series needed. These predictors can be further characterized as treatment specific and non-treatment specific. With the potential changing landscape of neoadjuvant therapy prior to radical cystectomy and the limitations of individual predictors of a complete response, a panel of several biomarkers may enhance patient selection for bladder preservation. The aim of this review is to summarize predictors of complete response to neoadjuvant chemotherapy.
Keyphrases
- neoadjuvant chemotherapy
- locally advanced
- lymph node
- rectal cancer
- sentinel lymph node
- muscle invasive bladder cancer
- squamous cell carcinoma
- clinical trial
- spinal cord injury
- end stage renal disease
- chronic kidney disease
- newly diagnosed
- stem cells
- gene expression
- high resolution
- ejection fraction
- case report
- risk assessment
- magnetic resonance imaging
- replacement therapy
- minimally invasive
- early stage
- prognostic factors
- machine learning
- deep learning
- big data
- open label
- cell therapy
- robot assisted
- artificial intelligence
- smoking cessation
- study protocol
- free survival