To the Editor:
Patient and physician perspectives about surgical risk may differ. Physicians are mostly focused on objective end-points (i.e. mortality and survival), whereas most patients are worried about permanent physical and emotional disability resulting from the operation [1]. Can objective clinical information be used to predict patient-reported health status?
In the attempt to respond to this question, we studied 221 consecutive patients submitted to major anatomic pulmonary resections (204 lobectomy and 17 pneumonectomy) during a 36-month period. All patients had a pre-operative measurement of maximum oxygen uptake (V′O2max), as a part of their routine pre-operative functional work-up, and a complete assessment of their pre-operative and post-operative (3 months after surgery) quality of life. All patients gave their consent for inclusion of their clinical data in our institutional database for clinical and scientific purposes and the Institutional Review Board of our hospital approved the study. No formal pre-admission or post-discharge physiotherapy or psychological support programmes were administered in this series. Neurological or psychotropic personal medications, if present, were generally resumed the day after surgery.
Quality of life was assessed before and 3 months after the operation by the administration of Short Form 36v2 (SF36v2) survey [2], which is a generic instrument assessing eight physical and mental health concepts (physical functioning, role limitation caused by physical problems, bodily pain, general health perception, vitality, social functioning, role limitation caused by emotional problems and mental health). Scores were standardised to norms and weighted averages were used to create the physical component summary (PCS) and mental component summary (MCS) scores on a standard scale. Norm-based scores have a mean±sd of 50±10. Patients were divided into two groups according to their pre-operative level of V′O2max (low-V′O2 group: V′O2max <15 mL·kg−1·min−1; high-V′O2 group: V′O2max >15 mL·kg−1·min−1). The peri-operative meaningful decline (PMD) of SF36 physical and mental scores was estimated using two methods: 1) Cohen's effect size method (mean change of the variable divided by its baseline standard deviation), where an effect size >0.8 was regarded as PMD [3]; 2) standard deviation method, where a difference greater than one standard deviation (>10) is regarded as PMD.
We found that a similar proportion of patients in the low-V′O2 and high-V′O2 groups had pre-operative scores of PCS (27% versus 21%, p=0.3) and MCS (67% versus 70%, p=0.6) lower than 50 (norm for the general population). Likewise, a similar proportion of patients in the low-V′O2 and high-V′O2 groups had post-operative scores of PCS (55% versus 49%, p=0.5) and MCS (53% versus 44%, p=0.2) lower than 50 (norm for the general population).
The comparison of the standardised peri-operative changes (effect size) of the quality of life scales did not show any significant differences between low-V′O2 and high-V′O2 groups. Furthermore, in both groups the average effect sizes of all quality of life domains were always lower than 0.8, indicating the absence of an average PMD in any of the quality of life domains. According to the effect size method, 35 (16%) patients had a PMD of PCS and 68 (31%) had a PMD of MCS. However, the proportion of patients experiencing a PMD of PCS and MCS were similar in the low-V′O2 and high-V′O2 groups (PCS: 14% versus 17%, p=0.6; MCS: 27% versus 32%, p=0.6, respectively). According to the standard deviation method, 50 (23%) patients had a PMD of PCS and 40 (18%) patients had a PMD of MCS. The proportion of patients experiencing a PMD of PCS and MCS were similar in low-V′O2 and high-V′O2 groups (PCS: 33% versus 21%, p=0.5; MCS: 24% versus 16%, p=0.2).
The results generated by this study showed that the quality of life evolution of patients with impaired aerobic capacity was similar to the one observed in patients in better physical shape and that V′O2max was not a reliable parameter to predict residual self-rated quality of life. These results are in line with previous evidence showing that traditional objective risk factors (i.e. age, chronic obstructive lung disease, forced expiratory volume in 1 s (FEV1), diffusing capacity of the lung for carbon dioxide) are generally not associated with residual quality of life [4–8].
Why do objective data not predict patient-reported health status? Self-rated health is an active cognitive process in which numerous aspects of health, both subjective and objective, are summarised within the perceptual framework of the individual (social, cultural, demographic, reference groups, health expectations, previous experience with health, mental disposition, etc.) [9]. For this reason, individual objective components of health, when they are extrapolated from the patient contextual framework, may constitute only the basis of self-rating, which can be subsequently modified by the context of the evaluation.
How can we use this information in clinical practice? The fact that we are not able to predict how the patient will feel months after surgery questions the entire process of surgical patient selection, currently based on objective parameters. What is the real meaning of predicted post-operative FEV1, V′O2max, etc. if these parameters will not be associated with the residual patient-perceived health status, which is what counts the most for the patient? How can we appropriately define surgical risk? Mortality is not sufficiently comprehensive to be used as the sole end-point for risk stratification. How can we account for other patient-centred outcomes (i.e. quality of life, pain, dyspnoea, satisfaction with care) and what should be their relative weight during the surgical decision process?
Unfortunately, our knowledge of the body-mind interaction is still too limited to find adequate answers. More research is needed to better understand the biological basis of health-related quality of life and its association with different genetic, inflammatory, psychoendocrinological and psychoneuroimmunological biomarkers, which may more accurately explain its peri-operative evolution.
Footnotes
Conflict of interest: None declared.
- Received December 10, 2012.
- Accepted January 2, 2013.
- ©ERS 2013