Concept Architecture
Concept
Theoretically, Duration of Response (DoR) is a time-to-event endpoint that measures the length of time a patient maintains an objective tumour response after the first documented complete or partial response until disease progression or death. It is founded on survival analysis and censoring theory and is widely used in oncology to assess the durability of treatment benefit. The concept exists to distinguish therapies that produce transient responses from those providing sustained clinical benefit.
Mathematically, Duration of Response is represented as the elapsed time between the date of the initial objective response and the date of documented disease progression or death, whichever occurs first. Because not all patients experience progression during follow-up, DoR is analysed using censored survival data and summarised using Kaplan-Meier estimation, median duration of response and corresponding confidence intervals. Comparative analyses frequently employ hazard ratios estimated using Cox proportional hazards models.
In practice, Duration of Response is calculated for patients achieving complete or partial response according to standard response criteria such as RECIST. Patients without progression at the time of analysis are censored at their last tumour assessment. In health economics, Duration of Response informs estimates of progression-free health states, treatment persistence, healthcare resource utilisation and quality-adjusted life years within oncology decision models.
Purpose
Used to quantify the durability of tumour response following successful treatment, supporting evaluation of oncology therapies and informing health economic models of long-term treatment benefit.
Mathematical Formulae
Primary Formula
DoR = Tprogression or death ? Tfirst response
Supporting Formulae
Kaplan-Meier survival estimate:
?(t) = ?(1 ? d? / n?)
Hazard function:
h(t) = f(t) / S(t)
Hazard ratio:
HR = h?(t) / h?(t)
Related Mathematical Methods
- Kaplan-Meier Estimation
- Survival Analysis
- Cox Proportional Hazards Model
- Censoring
- Log-Rank Test
- Progression-Free Survival Analysis
Example
A patient achieves a confirmed partial response 3 months after treatment initiation.
Disease progression occurs 14 months after treatment initiation.
Duration of Response:
DoR = 14 ? 3
DoR = 11 months
If the patient had not experienced progression by the study cut-off date, the observation would be censored at the date of the last tumour assessment.
Excel Implementation
| Function | Example Formula | Health Economics Application |
|---|---|---|
| DATEDIF | =DATEDIF(ResponseDate,ProgressionDate,"m") | Calculates the duration of response in months. |
| IF | =IF(Progression="","Censored",DATEDIF(ResponseDate,ProgressionDate,"d")) | Identifies censored observations. |
| MEDIAN | =MEDIAN(DurationRange) | Estimates the median duration of response when complete observations are available. |
| COUNTIFS | =COUNTIFS(StatusRange,"Response") | Counts patients eligible for Duration of Response analysis. |
| AVERAGE | =AVERAGE(DurationRange) | Summarises observed response duration, recognising that Kaplan-Meier methods remain the preferred analytical approach. |
VBA (Optional)
VBA can automate calculation of Duration of Response, identify censored observations and prepare datasets for Kaplan-Meier and Cox regression analyses.
Sources
- Eisenhauer EA, Therasse P, Bogaerts J, et al. New response evaluation criteria in solid tumours: Revised RECIST guideline (version 1.1). European Journal of Cancer. 2009.
- FDA. Clinical Trial Endpoints for the Approval of Cancer Drugs and Biologics.
- Kaplan EL, Meier P. Nonparametric estimation from incomplete observations.
- Cox DR. Regression Models and Life-Tables.
- Drummond MF, Sculpher MJ, Claxton K, Stoddart GL, Torrance GW. Methods for the Economic Evaluation of Health Care Programmes.
- Briggs A, Claxton K, Sculpher M. Decision Modelling for Health Economic Evaluation.
Related Concepts (2)
Library
Publications
1
A Systematic Review of the Effectiveness of Adalimumab, Etanercept and Infliximab for the Treatment of Rheumatoid Arthritis in Adults and an Economic Evaluation of Their Cost-Effectiveness — Chen, Jobanputra, Barton, Jowett, Bryan, Clark, Fry-Smith & Burls, Vol. 10, No. 42 ed., 2006 (Health Technology Assessment (NIHR))
A landmark NIHR HTA monograph systematically reviewing the clinical effectiveness and modelling the cost-effectiveness of anti-TNF biologics (adalimumab, etanercept, infliximab) for rheumatoid arthritis using the Birmingham Rheumatoid Arthritis Model, an exemplar of HTA-body economic evaluation in a musculoskeletal disease.
Frequently Asked Questions (6)
What is the objective response rate?
The proportion of patients whose tumour shrinks by a predefined amount or disappears entirely following treatment, measured using standardised radiological criteria.
Source: Eisenhauer et al. 2009
What proportion of patients does the objective response rate report?
The objective response rate reports the proportion of patients whose tumours shrank by a set amount or disappeared entirely after treatment, judged by standardised radiological criteria. It counts those achieving a complete or partial response, giving a clear, measurable sign that a treatment is shrinking cancer. Because it is objective and observed on scans, rather than resting on how a patient feels, it is a common early gauge of a treatment's activity. The share whose tumours measurably shrank is what it captures. Eisenhauer and colleagues (2009) describe this.
Source: Eisenhauer et al. 2009
How is the objective response rate measured?
The objective response rate is measured using standardised radiological criteria to assess whether a patient's tumour has shrunk by a predefined amount or disappeared, counting the proportion who achieve a complete or partial response. So the objective response rate is measured by standardised assessment of tumour shrinkage, which is why criteria are used, since determining a response requires a defined threshold of shrinkage or disappearance, and using standardised radiological criteria to assess the tumours allows the proportion of patients responding to be measured consistently, giving the objective response rate as a reliable measure of tumour response.
Source: Eisenhauer et al. 2009
What does the objective response rate include?
The objective response rate includes patients with a complete response, whose tumour disappears, and those with a partial response, whose tumour shrinks by a predefined amount, counting both as responders. So the objective response rate includes complete and partial responses, which is why it counts both, since a response can be complete disappearance or significant shrinkage, and combining these gives the proportion of patients whose tumours responded to treatment, making the objective response rate a measure of the patients who achieve a defined tumour response, whether complete or partial.
Source: Eisenhauer et al. 2009
Why is the objective response rate used?
The objective response rate is used to measure how often a treatment produces a tumour response, providing a standardised, objective indicator of a treatment's activity against the cancer. So the objective response rate is used to gauge treatment activity, which is why it is a common measure, since the proportion of patients whose tumours respond indicates how well a treatment works against the cancer, and using standardised criteria makes the measure objective and comparable, allowing the objective response rate to serve as a reliable indicator of a treatment's ability to shrink or eliminate tumours.
Source: Eisenhauer et al. 2009
How does the objective response rate differ from disease control rate?
The objective response rate differs from the disease control rate in that it counts only complete and partial responses, while the disease control rate also includes stable disease. So the objective response rate is narrower than the disease control rate, which is why it excludes stable disease, since it counts only tumours that shrink or disappear, whereas the disease control rate adds those whose disease is stable, and this means the objective response rate measures tumour response while the disease control rate captures the broader group whose disease is controlled, including stability as well as response.
Source: Eisenhauer et al. 2009
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British health economist
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Verification date: 15 May 2026
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