RECIST for targeted agents?

targeted-agent

The mode of action of targeted agents is often perceived to be different from that of the cytotoxic agents for which the criteria were initially developed: while the classical chemotherapeutic agents aim to cause the tumor to shrink and disappear, targeted agents often cause changes to the constitution of the tumor which at first do not necessarily lead to obvious shrinkage. This raises questions as to whether different response criteria should be considered to evaluate the activity of such compounds.

In 2011, the RECIST Working Group launched the first calls for databases to contribute to a data warehouse to address this question. After four years of contacting and negotiating terms for sharing data with partners from industry and academia, we have successfully compiled a database based on 50 phase II or phase III trials with clinical data from patients treated with either single targeted agents or targeted agents in combination with the classical cytotoxic compounds.

The data

Data on 23259 patients were shared by partners from industry (66%) and academia (34%).

  Number of patients Number of trials
(N=23259) (N = 50)
                CCTG (Canadian Cancer Trial Group)   4867 12
                MERCK  4421 7
                ASTRA ZENECA  2130 2
                ROCHE  2102 4
                GENENTECH  2069 3
                GSK  2045 3
                EORTC  1457 3
                SANOFI  1216 1
                ECOG-ACRIN Cancer Research Group   788 4
                DCCG (Dutch colorectal Cancer Group)   738 1
                PFIZER   716 7
                AMGEN   601 2
                SWOG   109 1

For the majority of patients, the primary disease was located either in the lung (36%), colon (28%) or breast (11%). A subset of 15620 patients (67%) received treatment with a targeted agent, either as single agent (25%) or in combination with other target agents (5%) or classical chemotherapy (37%).

  Treatment category Total
(N=23259)
Single
target
(N=5776)
Combination
(N=8705)
Non
targeted
(N=6555)
Two
targeted
(N=1139)
Placebo/BSC
(N=1084)
 Primary disease site N (%) N (%) N (%) N (%) N (%) N (%)
Lung  1114 (19.3)  3783 (43.5)  3171 (48.4)     0 (0.0)   297 (27.4)  8365 (36.0)
Colon  1003 (17.4)  2917 (33.5)  1784 (27.2)   376 (33.0)   519 (47.9)  6599 (28.4)
Breast   644 (11.1)   929 (10.7)   218 (3.3)   642 (56.4)     0 (0.0)  2433 (10.5)
Gist  1187 (20.6)     0 (0.0)     0 (0.0)     0 (0.0)     0 (0.0)  1187 (5.1)
Skin/Melanoma   499 (8.6)     0 (0.0)   318 (4.9)   109 (9.6)     0 (0.0)   926 (4.0)
Renal Cell   760 (13.2)     0 (0.0)     0 (0.0)    12 (1.1)   145 (13.4)   917 (3.9)
Gastric     0 (0.0)   446 (5.1)   436 (6.7)     0 (0.0)     0 (0.0)   882 (3.8)
Head And Neck     0 (0.0)   345 (4.0)   344 (5.2)     0 (0.0)     0 (0.0)   689 (3.0)
Pancreas     6 (0.1)   285 (3.3)   284 (4.3)     0 (0.0)     0 (0.0)   575 (2.5)
Soft Tissue Sarcoma   388 (6.7)     0 (0.0)     0 (0.0)     0 (0.0)   123 (11.3)   511 (2.2)
Prostate    96 (1.7)     0 (0.0)     0 (0.0)     0 (0.0)     0 (0.0)    96 (0.4)
Gynaeco    50 (0.9)     0 (0.0)     0 (0.0)     0 (0.0)     0 (0.0)    50 (0.2)
Liver    29 (0.5)     0 (0.0)     0 (0.0)     0 (0.0)     0 (0.0)    29 (0.1)

Objectives of the analyses

  • To investigate the impact of different modifications to the definition of response, and to the predictive value of the response criteria (building on the work of Mandrekar et al. [1] and An et al. [2]):
    • Use different cut-offs for tumor growth to distinguish between a complete response (CR), a partial response (PR), stable disease (SD) and progressive disease (PD)
    • Use different definitions of a “response”, e.g. would clinical benefit rate (CBR) which covers CR, PR and SD be more predictive than an endpoint based on CR and PR alone (as is currently done)
    • Use different parameters to quantify tumor growth, e.g. use the slope of the growth rather than the increase in the sum of diameters.
    • Correlate these to overall survival using landmark analyses
  • To study the heterogeneity of response to targeted treatments between lesions in a patient. Due to tumor heterogeneity within a patient the response of lesions may differ according to genetic characteristics or expression of certain markers. Therefore, one expects the lesions to respond differently to the treatments, especially in the case of targeted agents.
    • To study the optimal number of target lesions required for a stable assessment of response (cfr Schwartz et al. [3]).
  • To investigate the role of the different components of RECIST and how predictive they are for overall survival, especially the contribution of tumor growth based on objective tumor measurements in a model for overall survival which already includes factors for tumor shrinkage and progression of non-target disease (cfr Litière et al. [4])
  • To study the taxonomy of the tumor profiles
    • To assess whether they are different from treatment with cytotoxic agents
    • To investigate their predictive value, i.e. can we find specific profiles which result in a general better or worse prognosis

Timelines

  • 2011: launch of data requests
  • September 2015: pooling of warehouse completed
  • June 2016: finalizing the analyses
  • Early 2017: new RECIST guidelines?

References

1. Mandrekar Sj, An M, Meyers J, Grothey A, Bogaerts J, Sargent Dj. Evaluation of Alternate Categorical Tumor Metrics and Cut Points for Response Categorization Using the RECIST 1.1 Data Warehouse. J Clin Oncol 2014; 32 (8):841-852.
2. An MW, Dong X, Meyers J, Han Y, Grothey A, Bogaerts J, Sargent DJ, Mandrekar SJ; Response Evaluation Criteria in Solid Tumors Steering Committee. Evaluating Continuous Tumor Measurement-Based Metrics as Phase II Endpoints for Predicting Overall Survival. J Natl Cancer Inst. 2015 Aug 21;107(11).
3.Schwartz LH, Mazumdar M, Brown M, Smith A, and Panicek DM: Variability in response assessment in solid tumors: effect of number of lesions chosen for measurement, Clin Cancer Res 2003; 9: 4318-23.
4.Litière S, de Vries EG, Seymour L, Sargent D, Shankar L, Bogaerts J; RECIST Committee: The components of progression as explanatory variables for overall survival in the Response Evaluation Criteria in Solid Tumours 1.1 database. Eur J Cancer 2014; 50: 1847-53.

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