The administration of the study medicine in trials (for example, dose, dose titration/escalation, frequency, route of administration, monitoring) may differ from the schedule that is likely to be used in clinical practice. This is perhaps more likely if the new therapy is added to current usual care, or if the treatment itself may be intentionally misused by patients if its administration is not under strict control (for example, opioids in pain relief). In some cases the clinical background and skill level of the administering clinicians may be important.
Tag: Regulatory
Trial participants are at a different position in treatment pathway
‘Treatment pathway’ refers to the sequence of previous treatments received, based on patient selection criteria and response to previous therapies, often reflected in clinical guidelines. The position of patients in the treatment pathway drives the choice of appropriate comparator.
The position in the treatment pathway occupied by trial participants may differ from that which they would occupy in usual practice in the healthcare system of interest. For example, in usual practice the new medicine may be considered for use (only) after the disease progressed on two types of therapy, whereas trial participants may have experienced disease progression on just one. This assumes that the pathway has not changed during the course of the trial.
Other study design choices may limit generalisability
In multi-national studies the general level of care (concomitant therapies, access to technologies, patent support programmes) received by trial participants in some healthcare systems or study sites may differ from usual practice in the healthcare system of interest. This may have implications for the generalisability of the effectiveness results to that system. Recruitment of study participants may require a specific diagnostic activity that is currently not part of usual practice. Clinicians’ or participants’ willingness to participate or complete the trial may not be independent of factors such as adherence or underlying risk, which may be associated with effectiveness. This may be important when considering the applicability of results from studies in highly-resourced healthcare systems such as US, with increased access to sophisticated diagnostic and monitoring services as well as high-intensity care, to local populations where such services may not be available. If the effect of the medicine itself cannot be isolated from trial setting, then the combination of setting and intervention may need to be considered more broadly as an intervention strategy in its own right.
Trial settings and sites do not reflect usual clinical practice
In multi-national studies the general level of care (concomitant therapies, access to technologies, patent support programmes) received by trial participants in some healthcare systems or study sites may differ from usual practice in the healthcare system of interest. This may have implications for the generalisability of the effectiveness results to that system. Recruitment of study participants may require a specific diagnostic activity that is currently not part of usual practice. Clinicians’ or participants’ willingness to participate or complete the trial may not be independent of factors such as adherence or underlying risk, which may be associated with effectiveness. This may be important when considering the applicability of results from studies in highly-resourced healthcare systems such as US, with increased access to sophisticated diagnostic and monitoring services as well as high-intensity care, to local populations where such services may not be available. If the effect of the medicine itself cannot be isolated from trial setting, then the combination of setting and intervention may need to be considered more broadly as an intervention strategy in its own right.
There is a high risk of biased comparisons from observational (non-randomised) data
During medicine development, observational data are generally not available on effectiveness of the new therapy. They are however used for a number of purposes: to describe the natural history of disease, disease burden and treatment patterns, or the relationship between surrogate and final endpoints, or to validate new study endpoints or provide information on the effectiveness of comparator therapies. Some of this information may be used indirectly in estimating the effectiveness of the new therapy, for example through predictive modelling of long-term outcomes. Assessors will be particularly interested in the generalisability of the study population and the statistical methods used to control for bias.
In situations of conditional reimbursement, potentially within an adaptive pathway for a new medicine, observational data (for example, from registries) on the effectiveness of new medicine may be presented and assessed at HTA reviews. Comparisons between therapy alternatives of health outcomes based on non-randomised studies are particularly subject to bias: careful study design is required to minimise the bias. A variety of analytical techniques are available to adjust for imbalances observed between study groups that may affect the comparison, although this is unlikely to fully eliminate bias.
There is uncertainty in reported trial outcomes
Trial results may be difficult to interpret because of large uncertainty (wide confidence intervals) in the outcome measures. Trials may not have been powered specifically to detect differences in patient-relevant endpoints such as health-related quality of life. In some healthcare systems, secondary and tertiary outcomes may be considered to be lower quality evidence. High levels of uncertainty may be reported if there are lower rates of the outcome event than expected. Results for subgroups of importance to the health system of interest will have greater uncertainty, and in some cases may not have been reported.
Trial outcomes not considered to be measures of effectiveness
Outcomes reported in pivotal trials may not be considered to be measures of relative effectiveness from a health technology assessment (HTA) or reimbursement perspective. These outcomes (efficacy or safety) are selected to meet the needs of regulatory approval, but may not be optimal for some HTA agencies. A number of factors may be relevant. Trial outcomes may represent physiological parameters, such as tumour response, blood haemoglobin level or lung function, which are not considered to be patient-relevant. However, these may serve as surrogate endpoints (proxies) for effectiveness outcomes of relevance to HTA, but the relationship between the surrogate and ‘final’ endpoint needs to be demonstrated quantitatively. Outcomes that are clinically assessed disease activity indices may be considered measures of effectiveness if they are validated and are widely used. Outcomes that are composite endpoints (for example, MACE: major adverse cardiac events) may need to be disaggregated into their components for consideration in HTA.
Stopping rules for therapy are unclear
The administration of the study medicine in trials (for example, dose, dose titration/escalation, frequency, route of administration, monitoring) may differ from the schedule that is likely to be used in clinical practice. This is perhaps more likely if the new therapy is added to current usual care, or if the treatment itself may be intentionally misused by patients if its administration is not under strict control (for example, opioids in pain relief). In some cases the clinical background and skill level of the administering clinicians may be important.
Administration of therapy is inconsistent with usual practice
The administration of the study medicine in trials (for example, dose, dose titration/escalation, frequency, route of administration, monitoring) may differ from the schedule that is likely to be used in clinical practice. This is perhaps more likely if the new therapy is added to current usual care, or if the treatment itself may be intentionally misused by patients if its administration is not under strict control (for example, opioids in pain relief). In some cases the clinical background and skill level of the administering clinicians may be important.
Trial participants are at a different position in treatment pathway
‘Treatment pathway’ refers to the sequence of previous treatments received, based on patient selection criteria and response to previous therapies, often reflected in clinical guidelines. The position of patients in the treatment pathway drives the choice of appropriate comparator.
The position in the treatment pathway occupied by trial participants may differ from that which they would occupy in usual practice in the healthcare system of interest. For example, in usual practice the new medicine may be considered for use (only) after the disease progressed on two types of therapy, whereas trial participants may have experienced disease progression on just one. This assumes that the pathway has not changed during the course of the trial.
Trial population mix differs from usual practice
Application of trial inclusion/exclusion criteria, together with other factors affecting recruitment, may mean that the trial population does not coincide with the population likely to be treated locally in usual practice. There may be differences in the distribution by age, gender, ethnicity, socio-economic factors, co-morbidities or other factors. Firstly, this is of concern if the intervention of interest has different efficacy across these factors. Secondly, even in the absence of such efficacy differences, the risk profile of the study population for the outcome of interest may differ from that of the population likely to be treated in usual practice. In this case there may be different levels of absolute effect (events averted etc.) associated with levels of trial-reported efficacy for the different populations.
Other study design choices may limit generalisability
In multi-national studies the general level of care (concomitant therapies, access to technologies, patent support programmes) received by trial participants in some healthcare systems or study sites may differ from usual practice in the healthcare system of interest. This may have implications for the generalisability of the effectiveness results to that system. Recruitment of study participants may require a specific diagnostic activity that is currently not part of usual practice. Clinicians’ or participants’ willingness to participate or complete the trial may not be independent of factors such as adherence or underlying risk, which may be associated with effectiveness. This may be important when considering the applicability of results from studies in highly-resourced healthcare systems such as US, with increased access to sophisticated diagnostic and monitoring services as well as high-intensity care, to local populations where such services may not be available. If the effect of the medicine itself cannot be isolated from trial setting, then the combination of setting and intervention may need to be considered more broadly as an intervention strategy in its own right.
Trial settings and sites do not reflect usual clinical practice
In multi-national studies the general level of care (concomitant therapies, access to technologies, patent support programmes) received by trial participants in some healthcare systems or study sites may differ from usual practice in the healthcare system of interest. This may have implications for the generalisability of the effectiveness results to that system. Recruitment of study participants may require a specific diagnostic activity that is currently not part of usual practice. Clinicians’ or participants’ willingness to participate or complete the trial may not be independent of factors such as adherence or underlying risk, which may be associated with effectiveness. This may be important when considering the applicability of results from studies in highly-resourced healthcare systems such as US, with increased access to sophisticated diagnostic and monitoring services as well as high-intensity care, to local populations where such services may not be available. If the effect of the medicine itself cannot be isolated from trial setting, then the combination of setting and intervention may need to be considered more broadly as an intervention strategy in its own right.
Trial participants withdraw from therapy or cross over between treatment groups
Differential withdrawal rates between study arms in a trial may complicate interpretation of the findings, especially if there is divergence between intention-to-treat and on-treatment results. If study participants cross over between treatment groups after reaching a study endpoint (for example, disease progression in cancer) the ability of the trial to report unbiased comparisons for longer-term ‘effectiveness’ outcomes (for example, overall survival) is compromised.
Stopping rules for therapy are unclear
The administration of the study medicine in trials (for example, dose, dose titration/escalation, frequency, route of administration, monitoring) may differ from the schedule that is likely to be used in clinical practice. This is perhaps more likely if the new therapy is added to current usual care, or if the treatment itself may be intentionally misused by patients if its administration is not under strict control (for example, opioids in pain relief). In some cases the clinical background and skill level of the administering clinicians may be important.
There is a high risk of biased comparisons from observational (non-randomised) data
During medicine development, observational data are generally not available on effectiveness of the new therapy. They are however used for a number of purposes: to describe the natural history of disease, disease burden and treatment patterns, or the relationship between surrogate and final endpoints, or to validate new study endpoints or provide information on the effectiveness of comparator therapies. Some of this information may be used indirectly in estimating the effectiveness of the new therapy, for example through predictive modelling of long-term outcomes. Assessors will be particularly interested in the generalisability of the study population and the statistical methods used to control for bias.
In situations of conditional reimbursement, potentially within an adaptive pathway for a new medicine, observational data (for example, from registries) on the effectiveness of new medicine may be presented and assessed at HTA reviews. Comparisons between therapy alternatives of health outcomes based on non-randomised studies are particularly subject to bias: careful study design is required to minimise the bias. A variety of analytical techniques are available to adjust for imbalances observed between study groups that may affect the comparison, although this is unlikely to fully eliminate bias.
There are inconsistent results across or within trials
Trial results may be difficult to interpret because of different (possibly inconsistent) efficacy results across the pivotal studies. This may be due to differences in the trial populations associated with differences in efficacy across important sub-populations.
Results for an individual trial may vary in magnitude and/or direction for different outcomes, making interpretation less straightforward, for example when reviewing results for individual components of composite endpoints.
There is uncertainty in reported trial outcomes
Trial results may be difficult to interpret because of large uncertainty (wide confidence intervals) in the outcome measures. Trials may not have been powered specifically to detect differences in patient-relevant endpoints such as health-related quality of life. In some healthcare systems, secondary and tertiary outcomes may be considered to be lower quality evidence. High levels of uncertainty may be reported if there are lower rates of the outcome event than expected. Results for subgroups of importance to the health system of interest will have greater uncertainty, and in some cases may not have been reported.
Trial outcomes not considered to be measures of effectiveness
Outcomes reported in pivotal trials may not be considered to be measures of relative effectiveness from a health technology assessment (HTA) or reimbursement perspective. These outcomes (efficacy or safety) are selected to meet the needs of regulatory approval, but may not be optimal for some HTA agencies. A number of factors may be relevant. Trial outcomes may represent physiological parameters, such as tumour response, blood haemoglobin level or lung function, which are not considered to be patient-relevant. However, these may serve as surrogate endpoints (proxies) for effectiveness outcomes of relevance to HTA, but the relationship between the surrogate and ‘final’ endpoint needs to be demonstrated quantitatively. Outcomes that are clinically assessed disease activity indices may be considered measures of effectiveness if they are validated and are widely used. Outcomes that are composite endpoints (for example, MACE: major adverse cardiac events) may need to be disaggregated into their components for consideration in HTA.
Disease area is not well defined
The disease/indication may have an imprecise definition, and so there may be no well-established criteria for defining the population of interest (likely to receive the new intervention). A clinical code (ICD or other) may not yet have been established for the disease entity. Correspondingly there may be a lack of clinical guidelines, and usual care (or standard of care) may not be well established for the target population within an agreed treatment pathway. This may lead to uncertainty in applying trial results to the local context, as well as subsequent difficulties in setting up studies to monitor the usage and effectiveness of the medicine post-launch.
Trial participants are at a different position in treatment pathway
‘Treatment pathway’ refers to the sequence of previous treatments received, based on patient selection criteria and response to previous therapies, often reflected in clinical guidelines. The position of patients in the treatment pathway drives the choice of appropriate comparator.
The position in the treatment pathway occupied by trial participants may differ from that which they would occupy in usual practice in the healthcare system of interest. For example, in usual practice the new medicine may be considered for use (only) after the disease progressed on two types of therapy, whereas trial participants may have experienced disease progression on just one. This assumes that the pathway has not changed during the course of the trial.
Trial population mix differs from usual practice
Application of trial inclusion/exclusion criteria, together with other factors affecting recruitment, may mean that the trial population does not coincide with the population likely to be treated locally in usual practice. There may be differences in the distribution by age, gender, ethnicity, socio-economic factors, co-morbidities or other factors. Firstly, this is of concern if the intervention of interest has different efficacy across these factors. Secondly, even in the absence of such efficacy differences, the risk profile of the study population for the outcome of interest may differ from that of the population likely to be treated in usual practice. In this case there may be different levels of absolute effect (events averted etc.) associated with levels of trial-reported efficacy for the different populations.