Clinical trial · Observational
Methods of Identifying Effective Off-Guideline Treatments for Advanced Cancer Patients (CC N-of-1)
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 26, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260926-000001
Summary
Brief summary (as posted)
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.
Conditions
Conditions (1)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Advanced Cancer | Malignant Neoplasm | CURATED_BROADER | 0.78 |
Interventions
Interventions (0)
Data not yet available
Design
Arms and outcomes
Arms (0)
[]Primary outcomes (1)
- measure
- The predictive accuracy for each drug sensitivity testing (DST) used in the study
- timeFrame
- Through study completion, an average of 1 year
- description
- For each participant in the study who is treated with an off-guideline drug, the oncologist will provide the study with a binary assessment of "response" or "no response" from the participant, using the RECIST criteria or other criteria proposed by the treating oncologist. For each participant, we will compare the test prediction of "response" or "no response" to the oncologist assessment of "response" and "no response" to determine if the test prediction was correct or incorrect. For each test, we will compute the predictive accuracy of the test by dividing the number of correct predictions by dividing the number of correct predictions by the total number of predictions made by the test in the course of the study. For example, if a test made fifty (50) predictions and thirty five (35) of those predictions were correct, then the predictive accuracy of the test would be 35/50 = 70%.
Secondary outcomes (1)
- measure
- The overall patient response rate for each DST-guided therapy and for each cancer.
- timeFrame
- 12 months
- description
- To compare individual outcomes (response and disease-free survival) in patients treated with DST-guided therapy as compared to non-DST guided (conventional) therapy.
Eligibility
Eligibility (as posted)
- Sex
- All
Show eligibility criteria text
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
References
Publications (4)
- BACKGROUNDSadik 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
- BACKGROUNDLiu 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
- BACKGROUNDAcanda 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
- BACKGROUNDKornauth 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 O, Miura K, Mullauer L, Neumeister P, Noesslinger T, Ocko K, Ohler L, Panny M, Pichler A, Porpaczy E, Prager GW, Raderer M, Ristl R, Ruckser R, Salamon J, Schiefer AI, Schmolke AS, Schwarzinger I, Selzer E, Sillaber C, Skrabs C, Sperr WR, Srndic I, Thalhammer R, Valent P, van der Kouwe E, Vanura K, Vogt S, Waldstein C, Wolf D, Zielinski CC, Zojer N, Simonitsch-Klupp I, Superti-Furga G, Snijder B, Staber PB. Functional Precision Medicine Provides Clinical Benefit in Advanced Aggressive Hematologic Cancers and Identifies Exceptional Responders. Cancer Discov. 2022 Feb;12(2):372-387. doi: 10.1158/2159-8290.CD-21-0538. Epub 2021 Oct 11. PMID 34635570