Methods of Identifying Effective Off-Guideline Treatments for Advanced Cancer Patients (CC N-of-1)

Overview

Many FDA-approved drugs are not available to patients with a particular cancer because there has been no successful clinical trial conducted for that drug against that cancer. In the absence of such a successful clinical trial, the drug is not included in the National Comprehensive Cancer Network (NCCN) guidelines list of approved drugs for that cancer. The absence of a drug in the NCCN Guidelines for a particular cancer is usually not an indication that the drug has been shown to be ineffective for patients with that cancer. Rather, it is an indication that there is insufficient clinical trial evidence to include it. A drug that is FDA-approved for one or more cancers but is not in the NCCN Guidelines for a particular cancer is called an "off-guideline" drug for that cancer. This study is being done to measure and compare the reliability of multiple different treatment selection tests to predict a participant's response to an off- guideline cancer therapy. The results can guide oncologists to effective off-guideline drugs that would otherwise not be available to their advanced cancer patients. As this is an observational study, all the data gathered and analyzed will be generated in the normal practice of medicine, not by the study.

Detailed description

A) Significance: This is the first precision medicine study that aims to generate predictive accuracy of functional assays in selecting effective off-guideline treatments. Since the clinical evidence of these assays is severely limited, and as a result, oncologists are reluctant to use them. This study will add to that body of clinical evidence, and if successful, accelerate the acceptance of these functional assays for treatment selection in clinical practice. B) Specific Aims: This study will calculate the predictive accuracy of multiple functional assays (genomic and/or DST) to identify the tests that can be most helpful to patients, and to quantify the potential benefits of these tests. C) Methodology: The Participant's genomic and/ or DST results will be collected and reviewed by the Cancer Commons Scientific team. Furthermore, a literature review relevant to the Participant's cancer will be performed to identify the use of off-guideline drugs. Based on this analysis, the Scientific Team will write a Scientific Report that identifies any Promising Off-guideline Drugs and share with the Participant's oncologist to determine the merit of administering any off-guideline drug or drugs. If a Participant's oncologist is willing to administer one or more off-guideline drugs, the Participant is enrolled in the study. The Participant's oncologist administers one or more off-guideline drugs, and the subsequent Participant results are recorded in the study database. Note that the Participant's oncologist makes all treatment decisions unilaterally. Arms of the Study: The study will consist of multiple assay arms that belong to the categories shown below. Each arm will belong to a specific test. 1. Genomic Mutation Match: Select one or more off-guideline drugs that are indicated for a specific mutation which a genomic test shows to be present in the participant's cancer DNA, 2. Genomic Pathway Match: Select one or more off-guideline drugs that are not indicated for a specific mutation which a genomic test shows to be present in the participant's cancer DNA, but are indicated for a cancer pathway that genomics experts believe are strongly related to a specific mutation which a genomic test shows to be present in the participant's cancer DNA, 3. Drug Sensitivity Assays: Select an off-guideline drug or drugs that are designed as "response" by the test. D) Patient Population: The study will include advanced cancer patients who have test result that can be used by the Scientific Team to identify Promising Off-guideline Drugs. The study is open to patients with any cancer.

Primary outcome measures

• The predictive accuracy for each drug sensitivity testing (DST) used in the study [Time frame: Through study completion, an average of 1 year]

Secondary outcome measures (1)

• The overall patient response rate for each DST-guided therapy and for each cancer. [Time frame: 12 months]

Eligibility criteria

Inclusion criteria

• Participant must have a valid genomic or functional test or willing to undergo a new test
• Analysis of the participant's test must produce a set of Promising Off-guideline Drug(s)
• Oncologist must be willing to administer one or more Promising Off-guideline Drug(s)
• The study team must have an approved method of paying for the administered Off-Guideline Drug(s). Health insurance and self-pay are the two most common sources of payment
• Participant must sign the Informed Consent

Exclusion criteria

• No set of Promising Off-guideline Drug(s)
• Oncologist not willing to administer one or more Promising Off-guideline Drug(s)
• No approved method of paying for the administered off-guideline Drug(s)
• No signed Informed Consent

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: No

Study design

Observational model

Other

Study locations

United States · 1 center

• Cancer Commons — Palo Alto

Publications

• Sadik H, Pritchard D, Keeling DM, Policht F, Riccelli P, Stone G, Finkel K, Schreier J, Munksted S. Impact of Clinical Practice Gaps on the Implementation of Personalized Medicine in Advanced Non-Small-Cell Lung Cancer. JCO Precis Oncol. 2022 Oct;6:e2200246. doi: 10.1200/PO.22.00246. PMID 36315914
• Liu R, Wang L, Rizzo S, Garmhausen MR, Pal N, Waliany S, McGough S, Lin YG, Huang Z, Neal J, Copping R, Zou J. Systematic analysis of off-label and off-guideline cancer therapy usage in a real-world cohort of 165,912 US patients. Cell Rep Med. 2024 Mar 19;5(3):101444. doi: 10.1016/j.xcrm.2024.101444. Epub 2024 Feb 29. PMID 38428426
• Acanda de la Rocha AM, Berlow NE, Azzam DJ. Functional precision medicine: the future of cancer care. Trends Mol Med. 2025 May;31(5):404-408. doi: 10.1016/j.molmed.2024.10.015. Epub 2024 Nov 19. PMID 39567286
• Kornauth C, Pemovska T, Vladimer GI, Bayer G, Bergmann M, Eder S, Eichner R, Erl M, Esterbauer H, Exner R, Felsleitner-Hauer V, Forte M, Gaiger A, Geissler K, Greinix HT, Gstottner W, Hacker M, Hartmann BL, Hauswirth AW, Heinemann T, Heintel D, Hoda MA, Hopfinger G, Jaeger U, Kazianka L, Kenner L, Kiesewetter B, Krall N, Krajnik G, Kubicek S, Le T, Lubowitzki S, Mayerhoefer ME, Menschel E, Merkel PMID 34635570

Identifiers

NCT: NCT07343024 · CCCS001

Primary sources (government registries)

• ClinicalTrials.gov (US NIH)

View this study on ClinicalTrials.gov ↗