HRQoL (Health Related Quality of Life)

Health related quality of life (HRQoL) refers to an individual's or group's perceived physical and mental health over time. It is measured using validated instruments such as the EQ 5D or SF 36 and captures dimensions of wellbeing that clinical endpoints alone cannot represent. Preference based HRQoL instruments, such as the EQ 5D, supply the utility values that cost effectiveness analyses need to calculate quality adjusted life years (QALYs).

Clinical trials traditionally focus on objective endpoints such as survival, lab values, and imaging results. However, treatments that extend life may do so at the expense of daily functioning, emotional wellbeing, or social participation. HRQoL fills this gap by capturing the patient's own perspective on how a disease and its treatment affect everyday life. Health technology assessment (HTA) bodies use HRQoL evidence in different ways: NICE in England names the EQ 5D as its preferred measure of HRQoL in adults for the utility values in its reference case, Canada's Drug Agency (formerly CADTH) also expects economic evaluations based on QALYs, and Germany's IQWiG counts HRQoL among the patient relevant outcomes in its benefit assessments. This makes HRQoL evidence an important factor in many reimbursement decisions. Clinicians also use HRQoL scores to compare therapeutic options and to involve patients in shared decision making.

HRQoL is assessed through standardized questionnaires administered to patients at specified time points during a study. Instruments fall into two broad categories. Generic instruments cover broad health domains that apply across conditions. The EQ 5D 5L describes health on five dimensions (mobility, self care, usual activities, pain and discomfort, anxiety and depression), each at five levels, giving a health profile that a country's value set converts into a single index score. The SF 36 covers eight domains (physical functioning, role limitations due to physical health, bodily pain, general health, vitality, social functioning, role limitations due to emotional problems, and mental health) and produces a score for each domain plus physical and mental component summary scores. Disease specific instruments, such as the EORTC QLQ C30 for cancer or the KCCQ for heart failure, capture symptoms and functional limitations unique to a condition.

For economic evaluations, generic preference based instruments are preferred: each health state they describe has a utility value, taken from a value set based on general population preferences, on a scale anchored at 0 (equivalent to death) and 1 (perfect health), with some health states scoring below zero. The EQ 5D is preference based in this way; the SF 36 is not, although the SF 6D, derived from SF 36 items, is. A utility is a valuation of a health state, not the HRQoL questionnaire score itself. These utility values are multiplied by the time spent in each health state to calculate QALYs. For example, if a patient lives two years at a utility of 0.7, that contributes 1.4 QALYs.

Data collection timing matters. Researchers typically administer instruments at baseline, at regular intervals during treatment, and at follow up. Missing data are common, especially in sicker populations, and must be handled carefully using appropriate imputation techniques. The minimal clinically important difference (MCID) for each instrument helps distinguish statistically significant changes from changes that patients actually notice and value.

HRQoL measurement is appropriate in any study where treatment effects on patient wellbeing are relevant, which includes most trials of treatments. It is essential in trials supporting economic evaluations and HTA submissions. Use a generic instrument when cross disease comparisons are needed, a generic preference based instrument such as the EQ 5D when QALYs must be calculated, and add a disease specific instrument when you want greater sensitivity to condition specific symptoms. HRQoL is less informative in very short studies where health states have little time to change, or in populations that cannot reliably self report, such as young children or patients with severe cognitive impairment, although proxy versions exist.

A common error is selecting an instrument without considering the study population and the domains most relevant to the disease. Using only a disease specific instrument when QALYs are needed for an economic evaluation leaves the analysis incomplete, because most disease specific scores cannot be directly converted to utilities without a mapping study. Another mistake is administering questionnaires at too few time points, which forces analysts to interpolate between distant observations and reduces precision. Researchers also sometimes report mean utility scores without accounting for floor or ceiling effects, which compress the distribution and obscure true treatment differences.

In a phase III oncology trial comparing a new immunotherapy to standard chemotherapy, 800 patients complete the EQ 5D 5L at baseline, 3 months, 6 months, and 12 months. The immunotherapy arm shows a mean utility of 0.72 across follow up compared to 0.64 in the chemotherapy arm. Combined with mean survival of 20.5 months versus 16.5 months (a mean gain of 4 months, estimated from extrapolated survival curves, because QALYs need mean rather than median survival), and assuming each arm's mean utility holds for its whole survival time, the health economics team calculates an undiscounted incremental gain of 0.35 QALYs (0.72 × 20.5 ÷ 12 − 0.64 × 16.5 ÷ 12 = 1.23 − 0.88), which feeds into the ICER comparing the two treatments.