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Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different...
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Determining the optimal dose size and dosing frequency in pharmacotherapy is crucial for achieving therapeutic effectiveness while minimizing adverse effects. This article explores the methodologies employed in determining these parameters, focusing on their significance and interplay to tailor dosing regimens.Dose Size: Dose size refers to the amount of a drug administered in a single dose. It is determined based on the drug's pharmacodynamics and pharmacokinetics properties and...
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Designing a dosage regimen, which refers to the manner of drug administration, is a complex process involving the selection of drug dose, route, and frequency. This process is underpinned by pharmacokinetic parameters derived from tests and population averages. These parameters are then tailored to patient-specific variables such as diagnosis, demographics, and allergy status. Once therapy commences, therapeutic response monitoring is critical and achieved through clinical and physical...
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Bioavailability Study Design: Single Versus Multiple Dose Studies01:11

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Bioavailability studies are essential for understanding how a drug is absorbed, distributed, metabolized, and excreted in the body. These studies assess the extent and rate at which the active pharmaceutical agent becomes available at the site of action. The design of bioavailability studies can involve single-dose or multiple-dose regimens, each with distinct advantages and limitations.Single-dose studies are the preferred approach due to their simplicity and reduced drug exposure for...
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Gentamicin, an aminoglycoside antibiotic, is commonly administered via intermittent intravenous infusion to treat severe infections. An intermittent one-hour infusion of gentamicin, administered at eight-hour intervals, allows for precise control of plasma drug concentrations, minimizing toxicity while ensuring therapeutic efficacy. Pharmacokinetic principles govern the dynamics of plasma concentrations and can be mathematically described using specific equations.The plasma drug concentration...
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Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
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Dose-finding design and benchmark for a right censored endpoint.

Anaïs Andrillon1, Sylvie Chevret1, Shing M Lee2

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Summary

New dose-finding methods, Survival-CRM and informative Survival-CRM, address late-onset toxicities in cancer trials. These methods effectively handle censored data and treatment discontinuation, improving accurate dose selection compared to existing approaches.

Keywords:
Dose-findingbenchmarkcompeting riskslate-onset toxicitysurvival datatreatment discontinuation

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Area of Science:

  • Clinical Trial Design
  • Biostatistics
  • Oncology

Background:

  • Traditional oncology dose-finding trials often assume monotonic dose-toxicity relationships and short observation periods.
  • Emerging cancer therapies like targeted agents and immunotherapies frequently exhibit late-onset toxicities.
  • Late-onset toxicities necessitate prolonged observation windows and advanced statistical methods to account for censored endpoints and competing risks.

Purpose of the Study:

  • To propose novel dose-finding designs, Survival-CRM and iSurv-CRM, extending the Continual Reassessment Method (CRM).
  • To adapt CRM for right-censored endpoints using survival models and to handle treatment discontinuation as a competing event.
  • To evaluate the performance of these new methods against existing benchmarks.

Main Methods:

  • Development of Survival-CRM (Surv-CRM) for right-censored endpoints and informative Survival-CRM (iSurv-CRM) for competing risks.
  • Utilized survival working models within the CRM framework.
  • Conducted a simulation study comparing Surv-CRM and iSurv-CRM against Time-to-event (TITE)-CRM and a nonparametric benchmark.

Main Results:

  • The proposed methods demonstrated performance consistent with scenario complexity, validated by the nonparametric benchmark.
  • In scenarios without treatment discontinuation, Surv-CRM achieved dose selection accuracy comparable to TITE-CRM, with fewer toxicities and patients exposed to overly toxic doses.
  • In the presence of treatment discontinuation, iSurv-CRM showed superior performance over TITE-CRM in identifying the correct dose level.

Conclusions:

  • Survival-CRM and iSurv-CRM are effective extensions of the CRM design for oncology dose-finding studies with late-onset toxicities.
  • These methods appropriately handle censored data and competing risks from treatment discontinuation, crucial for modern cancer therapies.
  • iSurv-CRM offers a significant advantage over TITE-CRM when treatment discontinuation is a factor, leading to more accurate dose selection.