• In contrast to reference values that are obtained from cancer patients (see “What is reference data?”), normative data are obtained from the general population. Like with reference values, general population norm data enable the comparison of patient-reported outcomes (PRO) data collected in a specific context (e.g., clinical trial, routine monitoring) with a reference group, in this case, the general population of a specific country or the general populations of several countries combined. When comparing trial data (or routine data, etc.) to norm data, it can be established whether one’s data are in line with expectations and it can also be identified which of the EORTC QLQ-C30 scales show discrepancies that would be considered clinically meaningful (see “How do I interpret QoL scores?”).

    General population norm data are often collected through a panel research company which is an efficient way of collecting a large amount of data that is representative of a country’s general population in terms of sex, age, region, hometown size, household size and socioeconomic status (note, as these panels typically run online, panel research companies usually claim that their internet panels are representative for only those of the general population that have internet access). Ideally, as with reference values, the comparison is undertaken within subgroups, e.g., a female patient, aged 54 years, is ideally compared to the female general population in age group 50-59 years rather than comparing her to an overall general population norm score.

    Norm data for the EORTC quality of life questionnaires are currently available for the EORTC QLQ-C30 and the EORTC computer-adaptive test (CAT), the EORTC CAT Core. The European Norm for both EORTC instruments is based on 11 European countries (i.e., 10 countries of the European Union and the UK). National general population norm data are available for each of these 11 countries and also for Russia, Turkey, Canada and the US (see the two core papers Nolte et al., 2019, https://doi.org/10.1016/j.ejca.2018.11.024 and Liegl et al., 2019, https://doi.org/10.1016/j.ejca.2018.11.023). If you are interested in using EORTC QLQ-C30 norm data for your project (beyond those data that have already been published), these data are available upon request. Please use the following link: eortc.be/services/forms/erp/request.aspx, using EORTC study number 1519.

  • The use of the EORTC QLQ-C30 Summary Score, available here, has increased since its publication. Although, there is a debate going on within the EORTC QLG in which context applying the summary score is appropriate. Furthermore, regulatory agencies have expressed concern that the summary score is not specific enough for regulatory decision-making. Therefore, more research is needed on the use of the EORTC QLQ-C30 summary score in both cancer clinical trials and clinical practice settings. Currently, a project aiming to provide recommendations for the use of the EORTC QLQ-C30 summary score in cancer clinical trials and clinical practice. This project is expected to finish by the beginning of 2025.

  • The standard approach to scoring should be followed, with items being scored according to the scale structure they originate from, following the guidelines as stipulated in the relevant EORTC Scoring Manual(s). These guidelines include instructions that single items and multi-item scales be scored as such and transformed to a 0-100 scale with appropriate direction. For descriptive purposes, users may consider using the raw, non-transformed scores of single items and single item scales and presenting these as simple proportions for each of the relevant response categories. Such an approach may be easier to present and interpret, compared to the use of mean scores. However, such an approach should be regarded as novel, and distinguished appropriately, given the divergence from the standard scoring instructions. More information can be found in the Item Library User Guidelines here.

  • The EORTC CAT Core tailors the questionnaire to the individual patient without compromising comparability across patients. CATs are dynamically administered, computer-based questionnaires. They select in real-time the next question based on the responses provided to prior questions, tailoring the assessment to the patients’ needs. This allows for a more precise and efficient assessment of quality of life than static questionnaires and lowers burden through the selection of questions which are the most relevant to the individual patient.

    If you want to know more about this tool, please visit the EORTC CAT webpage.

  • There are no regulatory guidelines specific for the EORTC QLQ instruments. However, several general guidelines about the use of patient reported outcomes exist, which contains information helpful for the implementation of the EORTC QLQ-C30 and its modules in cancer clinical trials.

    Some regulatory guidelines can be found here:

    • Food and Drug Administration. Patient-Reported Outcome Measures: Use in Medical Product Development to Support Labeling Claims: Guidance for Industry Final. 2009.
    • European Medicine Agency. Appendix 2 to the guideline on the evaluation of anticancer medicinal products in man. The use of patient-reported outcome (PRO) measures in oncology studies. 2016.
  • No, this information is not needed per se. It is not part of the actual HRQOL outcomes. Besides, certain authorities and/or ethical committees consider that this info is part of patient’s privacy and should not be collected. So, this question may be omitted or modified. However, be aware that in most studies one will need an unambiguous method of matching a person’s questionnaire with other relevant study data. Many regulatory bodies (e.g. The World Medical Association’s Declaration of Helsinki, International Conference on Harmonization (ICH), Good Clinical Practice (GCP) and EU Clinical Trials Directive guidelines) require that a study subject’s right to data protection and privacy must be safeguarded in the context of a clinical study. This usually implies that the names of the study participants cannot be collected since these must remain anonymous to the study investigators handling the data. If you are unsure which privacy data you can or cannot collect, please check with your local or national governing Ethical Committee for guidance.

  • Yes. Your patients can use these types of systems for questionnaire completion, as equivalency of derived scores is considered sufficient. You can distribute the questionnaires via an electronic platform e.g. on touch screen devices or via web. You can also use Interactive Voice Response systems (IVRS over telephone). There is a statement to this effect in both the academic and commercial users’ agreement. But please be aware that there may be additional fees to pay. In case of commercial use, the standard royalty fee for use of questionnaires still applies and is not connected with any fee you may have to pay for use of proprietary software.

    We also have a voice script for administering our questionnaires over the phone in an interview. This is different than the IVRS option because it is done with an interviewer that follows the script. If you need the voice script, please contact us.

    An online platform (CHES) was established to provide electronic data collection infrastructure for projects conducted by the EORTC Quality of Life Group. The software company ESD – Evaluation Software Development (www.ches.pro) has developed this platform also for the demonstration and implementation of CHES in daily oncology practice when using EORTC QLQ measures. CHES allows questionnaire administration, sophisticated graphical presentation of questionnaire results as well as the completion of electronic case report forms. The CHES platform can be used in all common web-browsers and does not require any local software installation. The software complies with the Good clinical practice guidelines (GCP) for electronic data collection. For more info: https://ches.eortc.be/cms/. If you use electronic data capture there are specific confidentiality and security concerns. It is your responsibility to check that your system complies with any regulations in the countries where you are collecting data.

  • There are no specific guidelines for selecting MIDs for the modules. For more information, it might be helpful to contact the lead developer of the specific module via the questionnaires page on our website.

  • The thresholds for interpreting clinically meaningful change in QoL scores between groups of patients (see FAQ: How do I interpret QoL scores?) are also often used to interpret individual level score change clinically meaningful. For instance, a patient who changes by the MID or more can be considered to be a ‘responder’.

    The proportion of responders can be compared between groups (e.g., between two treatment arms).

    However, note that MIDs for interpreting group-level change might be insufficiently precise for monitoring individual patients because individuals can only change by specific points (jumps) in their QoL scores. It is important to investigate whether individual-level change can be interpreted as “real change”, and that it is not just an artifact of measurement error. Please see the reference below for more details.

    • Ref: King MT. A point of minimal important difference (MID): a critique of terminology and methods. Expert Rev Pharmacoecon Outcome Res. 2011 Apr; 11(2):171-84.)

    Giesinger et al (Health Qual Life Outcomes, 2016) have established thresholds for clinical importance for four EORTC QLQ-C30 scales: Physical Functioning (PF), Emotional Functioning (EF), Pain (PA) and Fatigue (FA). These thresholds are useful for screening of individual patients with clinically important problems requiring further exploration and possibly intervention by health care professionals in daily clinical practice.

  • The QLQ-C30 and its modules have been designed to evaluate change of HRQOL in clinical trials setting. Therefore, the scores are mainly used in a comparative setting such as:

    • comparing different patient groups at a given time point
    • comparing changes within one group over time
    • comparing changes over time between different patient groups.

    When comparing scores, it is important keep in mind that statistically significant differences do not necessarily imply clinically relevant differences or changes and vice versa.

    A minimum important difference (MID) of 5 to 10 points, as defined by Osoba et al (J Clin Oncol 1998), is generally recommended for interpreting group differences and changes in the EORTC QLQ-C30 scale scores as clinically meaningful. The rationale for using MIDs of 5 to 10 points has been supported in several papers, specific for the QLQ-C30. Of note is the paper by King et al (Qual Res 1996) where known-group comparisons were used to establish a between group difference.

    However, note that more recent guidelines have highlighted that the 5 to 10 points rule may be too simplistic in that it does not differentiate between the QLQ-C30 scales, between directions of change (improvement vs deterioration), and may not be achievable in all settings (Cocks et al J; Clin Oncol 2010, and Cocks et al; EJC 2012). Below are some additional useful references that should also be consulted when selecting clinically meaningful thresholds for group differences and changes across the different QLQ-C30 scales, for improving and deteriorating scores, and in different disease settings.

    • Musoro JZ, Coens C, Sprangers et al. EORTC Melanoma, Breast, Head and Neck, Genito-urinary, Gynecological, Gastro-intestinal, Brain, Lung and Quality of Life Groups. Minimally important differences for interpreting EORTC QLQ-C30 change scores over time: A synthesis across 21 clinical trials involving nine different cancer types. Eur J Cancer. 2023 Jul;188:171-182. doi: 10.1016/j.ejca.2023.04.027. Epub 2023 May 7. PMID: 37257278.
    • Cocks K, et al. Evidence-Based Guidelines for Determination of Sample Size and Interpretation of the European Organisation for the Research and Treatment of Cancer Quality of Life Questionnaire Core 30. J Clin Oncol 2010; 29(1): 89–96.
    • Cocks K, et al. Evidence-based guidelines for interpreting change scores for the European Organisation for the Research and Treatment of Cancer Quality of Life Questionnaire Core 30. European Journal of Cancer (2012) 48, 1713– 1721.
    • Maringwa JT, et al. on behalf of the EORTC PROBE project and the Lung Cancer Group. Minimal important differences for interpreting health-related quality of life scores from the EORTC QLQ-C30 in lung cancer patients participating in randomized controlled trials. Support Care Cancer. 2011 Nov; 19(11):1753-60.
    • Maringwa J, et al. Minimal Clinically Meaningful Differences for the EORTC QLQ-C30 and EORTC QLQ-BN20 Scales in Brain Cancer Patients. Ann Oncol. 2011 Sep; 22(9):2107-12.
  • The EORTC QLQ-C30 comprises 30 items (i.e. single questions), 24 of which are aggregated into nine multi-item scales, that is, five functioning scales (physical, role, cognitive, emotional and social), three symptom scales (fatigue, pain and nausea/vomiting) and one global health status scale. The remaining six single-item (dyspnoea, appetite loss, sleep disturbance, constipation, diarrhoea and the financial impact) scales assess symptoms. No item occurs in more than one scale.

    Scoring of the QLQ-C30 is performed according to QLQ-C30 Scoring manual, which is available to download via our website on the manuals page. All of the scales and single-item measures range in score from 0 to 100. Higher score for the functioning scales and global health status denotes a better level of functioning (i.e. a better state of the patient), while higher scores on the symptom and single-item scales indicate a higher level of symptoms (i.e. a worse state of the patient).

    Note: Some authors may reverse the symptom scores to follow the functioning scales interpretation (and vice versa). The reason for this is usually for consistency in signs of the change scores across the various scales. Care should be taken when interpreting the change scores in such scenarios.

  • Yes, you can use single items/scales from different modules. With the EORTC Item Library, you can make an item list that can be used in conjunction with the QLQ-C30 and an existing validated module, to cover missing issues that you want to assess.

  • The order of the items in a validated questionnaire cannot be changed. The questionnaire has been developed and validated in this format, and changing the order of the items might affect the psychometric properties of the questionnaire.

  • Yes, with the EORTC Item Library you can make an item list, adding items to an existing questionnaire if you think that important domains or symptoms might be missing.

  • No, it is not possible to modify the wording of questions or to alter the time scale, if you want to use a validated questionnaire and preserve its psychometric qualities. When creating an item list using the Item Library, we recommend using the time frame of the original questionnaire from which the item originates. The wording of the item as such can never be altered. You can find more information in the Item Library Guidelines.

  • A short version of the questionnaire is not available. However, the EORTC is currently validating a shorter version focused on the functional scales (QLQ-F17). In addition, a shorter form for use in palliative care, the QLQ-C15-PAL, is available as a validated measure, based on items from the QLQ-C30. Please see our questionnaires page.

  • The various modules have been designed to be used in conjunction with the core questionnaire, and their content validity is based on this combination. The core questionnaire covers important generic cancer symptoms and side effects which could be missed if only the module alone is used. As such, we strongly recommend using the module in conjunction with the core questionnaire. In the few cases where a module can be used without the QLQ-C30 (standalone modules) this is specifically mentioned.

  • As for the best way to analyse longitudinal data, there is no straight answer. The most important thing to keep in mind is that the analysis techniques should reflect your objective. This depends on the objective of the study, its design, the amount of missing data, sample size, available software, etc.

    The most common endpoints are as follows:

    • Analysis at each time point separately
    • Change from baseline
    • Time until event (predefined in/decrease)
    • Responder
    • Area under the curve or overall average over time

    Longitudinal modelling is recommended over repeated univariate analysis.
    This approach will try to model the data, including the time dependence. Estimates of time and group parameters allow you to test the significance of comparisons and/or construct confidence intervals for predictions. Many different types of models are possible according to the assumptions one is willing to make. Most commonly used are general linear models (GLM) and general linear mixed models (GLMM).

    Some good references are:

    • Fairclough DL. Design and Analysis of Quality of Life Studies in Clinical Trials. Chapman and Hall/CRC Press, Boca Raton, Florida, 2002.
    • Diggle P et al. Analysis of Longitudinal Data, Oxford University Press, 1994.
    • Fahrmeir, Tutz. Multivariate Statistical Modelling using Generalized Linear Models Springer Statistics, New York, 1994.
    • Verbeke G & Molenberghs G. Linear Mixed Models for Longitudinal Data, New York: Springer – Verlag, 2000.
    • Coens C et al. International standards for the analysis of quality-of-life and patient-reported outcome endpoints in cancer randomised controlled trials: recommendations of the SISAQOL Consortium. Lancet Oncol. 2020 Feb;21(2):e83-e96.
    • Pe M et al. Statistical analysis of patient-reported outcome data in randomised controlled trials of locally advanced and metastatic breast cancer: a systematic review. Lancet Oncol. 2018 Sep;19(9):e459-e469.
  • In the EORTC, the following information concerning the different reasons for missing data is collected:

    • patient felt too ill;
    • clinician or nurse felt the patient was too ill;
    • patient felt it was inconvenient or took too much time;
    • patient felt it was a violation of privacy;
    • patient did not understand the actual language or was illiterate;
    • administrative failure to distribute the questionnaire;
    • not required at this time point;
    • other, specify…;
    • unknown.
  • This depends on whether the data is missing completely at random, missing at random or missing not at random. The importance of keeping missing data to a minimum cannot be over-emphasized. General recommendations concerning missing data can be found in the scoring manual here.

  • A general recommendation is provided in the scoring manual here. Users should be careful to impute missing values if there are a lot of them – and especially, if they seem to be non-random. There might be a clinical reason/explanation of why patients have dropped a specific item. Volume 17, issue 5-7 (1998) of Statistics in Medicine contains a series of published papers on missing data in quality of life research in cancer clinical trials. References of interest are:

    • Incomplete quality of life data in randomized trials: missing forms. Curran D, Molenberghs G, Fayers PM, Machin D. Stat Med. 1998 Mar 15-Apr 15;17(5-7):697-709
    • Why are missing quality of life data a problem in clinical trials of cancer therapy? Fairclough DL, Peterson HF, Chang V. Stat Med. 1998 Mar 15-Apr 15;17(5-7):667-77.
  • There are 4 main steps to consider for the design of a HRQOL study:

    1. Determine your HRQOL objective

    • Write down the specific question you want to answer. Take extra care to determine which specific HRQOL domains, what time periods and what type of changes/differences you are expecting to be relevant for your question.

    2. Choose an instrument

    • It should be a validated (i.e. reliable, valid, responsive) questionnaire in the trial population.
    • It should address the HRQOL domains that are essential for your hypothesis: global measures, disease-specific measures, and symptom checklists.
    • Check if appropriate translations are available.

    3. Select your assessment time points

    • Assessment schedule should closely reflect the objective.
    • Schedule should include at least a baseline (i.e. before treatment/randomization).
    • If comparing multiple arms: schedule should be identical/comparable between the arms.
    • Keep the patient in mind: do not overburden by collecting more than necessary.

    4. Develop an analysis plan

    • Analysis plan should reflect the objective.
    • Address issues of scale/domain selection, sample size, compliance, missing data, minimal clinically important difference and sensitivity analyses.

    Note that objectives, instrument, assessment schedule and analysis techniques should be specified a priori. A good trial design, conduct, analysis and reporting is only possible if these aspects have been determined beforehand.

  • No, this is not allowed. We can only authorise the use of a specimen of the questionnaire. A specimen is a copy with a watermark, provided in a non-editable file. Our measures are protected by copyright, so we cannot allow unauthorised use of our questionnaires. If you want to receive a specimen to put in a leaflet, please see the specimen in each questionnaire dedicated page. When you publish the specimen, you also need to mention the full reference of the original publication of the validation paper of the QLQ-C30. Furthermore, you need to add a statement that if someone wants to use our measures, they need to contact the Quality of Life Department. You can also mention our website address.

  • If you have signed a user’s agreement to use the module in your study, you may publish the data from the module.

    Publication rights of EORTC modules:

    1. The module itself may not be published, except by EORTC.
    2. EORTC shall have the right to publish any paper or make any presentation which utilizes generated data prior written consent.
    3. Collaboration may be sought with the Module Developer for scoring the module if necessary, for guidance in interpretation of results.
    4. Publications on the module that are focused primarily on the psychometrics of the questionnaire should include one of the module’s developers as a co-author. One of the module’s developers should be given the opportunity to: (1) make a contribution to the conception and design of the study, acquisition of data, or analysis and interpretation of data; (2) review a draft of the article or revise it critically for important intellectual content; and (3) approve as co-author the final version to be published. For contact details for the module developer please contact EORTC QOL Dept.

    For more information about the use of modules under development, please click here.

  • References to publications on the questionnaires can be found in the Resources – Publications or in the relevant questionnaire page.

  • Since the tables present the total sample size and the percentage in each group, you could easily calculate the mean and SD if you really want to. (Standard stats books tell how to do this for grouped data). But many of the scales are asymmetric (depending on the disease / stage grouping), many have floor or ceiling effects, and all are discrete not continuous. Mean and SD would not reflect this. E.g., for many scales, the (mean) +/- (2xSD) will give “impossible” values outside 0 to 100.

  • Reference value data are historical data from the EORTC QLQ-C30 and/or its modules obtained in previous clinical studies, trials, or stored in registries. These data are from specific subgroups of patients with an oncological disease typically further stratified by age, sex, disease stage, and performance status, allowing a more accurate comparison. Reference data provide context to aid interpretation of EORTC PRO scores and can be used in the following scenarios:

    • Sample size calculation
      (Reference data can be used to build estimations of sample size requirements when planning a clinical trial with a primary or secondary PRO endpoint. Adequate sample size is necessary to provide sufficient power to test the significance of treatment effects.)
    • Comparisons of scores from groups of patients with similar characteristics
      (Reference data provide information about the distribution of QoL scores for given cancer populations with certain predefined characteristics, in particular stage and cancer site. This information can be used to explain unexpected differences in clinical outcomes, e.g. an unexpected response rate or median survival, to identify populations that need special attention and carry out comparisons among different countries.)
    • Familiarity with the distribution of scores for a scale
      (Knowledge about the distribution of QOL scores at baseline and the possible magnitude of change over time in a certain patient group is important to be considered at the design stage of a clinical trial. It can help in establishing realistic hypotheses and a priori defined cut-off points.)
    • Comparison of an individual patient’s score with patients with similar characteristics
      (Reference data provide clinicians with a comparison to evaluate if an individual patient’s responses are higher or lower than might be expected when looking at PRO data from patients with similar characteristics or his and her pre-treatment scores. However, there are no widely accepted standard thresholds for reference values to trigger clinical actions.)
    • Quality control in translation procedures
      (The EORTC Quality of Life Study Group has developed procedures for the translation of the EORTC QLQ-C30 and its cancer site-specific modules, available here. Comparison of data from new translations with available reference data from original language versions can be helpful to identify obvious discrepancies caused by incorrect translations.)

    The EORTC QOL Group aims to provide a solid source of reference data for use in research and clinical practice. For this reason, there are current efforts to update the pool of EORTC QOL reference value data, develop a database and an associated online accessible user interface for reference value calculation. The previous version of the manual on EORTC QLQ-C30 Reference Values (Scott et al 2008) is available here.

  • The QLQ-C30, as well as its modules, has been successfully migrated onto electronic platforms and used in a number of studies as ePRO. We do not offer a ready-to-use electronic version, since migration remains the responsibility of the user, but we have our ePRO Migration Guidelines that can be downloaded from the Manuals library.

    Please be aware that for every use of the EORTC questionnaires as ePRO you need a valid user license – also for academic use.

  • Translations are developed using the standard forward/backward translation procedure to ensure high quality. More information on this procedure can be found in the Translation Manual here.

  • No. Academic use is free of charge. As an academic user, you will however still need to register your study and receive permission to use questionnaires. You have to fill in the request form here. Only if your study has commercial sponsorship, you will be required to pay a fee, depending on the number of patients in the study. For further details for commercial use, please click here.

  • Yes. This can be done via our request form that you can access here. By completing the process, your request will go through approval process and you will be authorised to use the questionnaire in the study you mentioned in the request form. For each new study, you will have to enter a new download request.

  • In order to be able to use the QLQ-C30 and modules you need to ask for permission. This can be done via our request form that you can access here. By completing the process, your request will go through approval process and you will be authorised to use the questionnaire in the study you mentioned in the request form. For each new study, you will have to enter a new download request. Academic use requires no charge but if your study has commercial sponsorship, you will be required to pay a fee depending on the number of patients in the study. For further details for commercial use, please click here.

  • More information on getting translations done can be obtained from the Translation Team. You can contact them through the contact form. The Translation manual can also be of help – you can download it from the Manuals page.

  • A list of available translations per questionnaire can be found here.

  • In order to be able to use the QLQ-C30 and modules you need to first get permission.

    • FOR ACADEMIC USE: This can be done via our download process. Academic use is free of charge, but you still need permission for use of the questionnaire for each study. You apply for permission by filling in the request form. It is then sent to the administrator for approval. Once your request has been approved, you will receive an e-mail with links to the questionnaires and you are authorised to use the requested measures in the study you mentioned. Please do not forget, for each new study, you will have to enter a new download request.
    • COMMERCIAL USE: Please note that if your study has commercial sponsorship, you will be required to pay a fee depending on the number of patients in the study. For further details for commercial use, please click here.
  • No and currently there are no on-going efforts to develop such a system.

  • We have a voice script for telephone administration of the QLQ-C30. If you have any questions, please contact us via the contact form.