A narrative review: depth of response as a predictor of the long-term outcomes for solid tumors

Abstract

Response Evaluation Criteria in Solid Tumors (RECIST 1.1) is classical and popular for public. However, there are some problems recently. For example, partial response ranges from 30% to 99%, objective response is dichotomous, so there may be some heterogeneity. New metrics for evaluating the efficacy have been investigating, such as early tumor shrinkage, time to response and depth of response (DpR). DpR has been used in hematologic malignancies and is considered as a predictor of efficiency. In solid tumors, DpR was firstly proposed by Mansmann et al. in metastatic colorectal cancer (mCRC) and defined as the percentage of tumor shrinkage, which is a continuous metric, and could avoid the information loss due to dichotomization of responses that has been widely applied to several kinds of solid tumors. Some authors have found associations between DpR and OS, DpR is a valuable surrogate endpoint for mCRC, metastatic breast cancer, metastatic melanoma and advanced pancreatic cancer. However, the predictive value of DpR is still uncertain in the research of lung cancer and gastric cancer. Which indicating that a mature and unified application standard has not yet been formed for DpR. This article summarizes researches on the DpR as a predictor of the long-term outcomes for solid tumors, it also discusses the challenges and limitations in the applications of DpR.

Defining unique clinical hallmarks for immune checkpoint inhibitor-based therapies

“… 6 122 A limitation associated with DepOR is that its predictive value remains uncertain. 123 Non-measurable lesions are not considered in the calculation of DepOR, which is based on measurement of tumor diameter. Additionally, reductions in target lesions do not always result in a diameter reduction, and tumor shrinkage may not always be symmetrical.…”

“…Additionally, reductions in target lesions do not always result in a diameter reduction, and tumor shrinkage may not always be symmetrical. 123 For HRQOL, instruments currently used were designed for earlier chemotherapies and may not be sufficiently sensitive to capture important symptomatology unique to ICIs. 122 124 Challenges with generalizing HRQOL data from prospective studies include limited data, heterogeneity in definitions and measurement tools, time point and duration of measurements, poor compliance, and missed data points between intervention and control arms.…”

Functional Gene Expression Signatures from On-Treatment Tumor Specimens Predict Anti-PD1 Blockade Response in Metastatic Melanoma

“…The Youden index method was used to select the optimal threshold point from the ROC curve in the Riaz et al dataset [21,22]. After combining all the test samples, we used the Matthews correlation coefficient to assess the correlation between the predicted and the response outcome [23]. We also calculated the odds ratio of each sample based on the signature score.…”

Depth of response may predict clinical outcome in patients with recurrent/metastatic head and neck cancer treated with pembrolizumab-containing regimens

“…DpR was initially reported as a surrogate marker of survival in metastatic colorectal cancer ( 6 ). Since then, the correlation between DpR and survival benefits has been investigated in other types of cancers, such as melanoma, lung, gastric, breast, and pancreatic cancers ( 7 , 8 ). However, in R/M HNSCC, the association of DpR and pembrolizumab regimens with survival outcomes remains unclear.…”