In this study, we evaluated inflammatory biomarkers at baseline and within three months until death of patients who received palliative care for terminal cancer. Our findings provide novel evidence that there was a significant longitudinal linear relationship between change in CRP, CAR and albumin and death. CRP and CAR levels increased while albumin decreased during the last three months of life.
Systemic inflammation is a recognized as a hallmark of cancer and reflects the body’s defense to mitotic processes and develops through the action of various proinflammatory mediators, including cytokines, such as interleukins (IL) 1, IL 6 and tumor necrosis factor alpha (TNF-α) leading to accelerated tumor progression [22–24]. According to our results, terminal cancer is related to a progressive increase in serum CRP/CAR levels, and a decrease in serum albumin levels with the approach of death. This can be explained by the fact that cytokines play a role in inflammation, including induction of acute phase reactants and down-regulation of albumin production, therefore CRP synthesis by the liver increases as the disease progresses, while albumin synthesis could be significantly decreased [25].
The current findings are of clinical importance given that these biomarkers are commonly available as part of the standard routine management of patients with cancer. In addition, assessing the change in a variable rather than an absolute value at a single point in time is crucial because albumin and CRP alterations over time indicate an ongoing increase in inflammation. Furthermore, there is lesser susceptibility to biases related to an acute elevation of the biomarker.
Another point to be mentioned is that prognostic scoring systems [3, 6, 26, 27] are typically developed from cross sectional data in relation to survival, and this technique allows a measure of association between a variable cut-off value and time but assumes a common trajectory among individuals [21]. Our findings demonstrated that the assessment of the rate of change over time of the biomarkers (trajectory) demonstrated prognostic predictive power. These suggest that CRP, albumin and CAR could be used to predict death in patients with incurable cancer referred for exclusive palliative care regardless of a specific cut-off point evaluated by a single measurement at baseline.
The median concentrations of inflammatory biomarkers in our study were worse than those reported in a longitudinal study in patients with acute myeloid leukaemia [28] which may be explained by the fact that our study dealt with patients at the most advanced stage of the disease. To our knowledge, no studies have specifically studied longitudinal albumin, CRP, and CAR in an exclusive palliative setting. Concerning cross-sectional studies that involve patients with cancer in palliative care [4, 8, 9, 29] median and cut-off values vary according to the cancer population and period analyzed which makes it difficult to compare our results with those observed in other previous studies.
At the present time there is no consensus on the best cutoff points for CRP, albumin and CAR, with different studies using different values as reference [5, 7]. The meta-analysis conducted by Dolan et al. [5] showed variation in the cutoff points for albumin and CRP in the included studies. The most widely used cut-off point in the 63 articles that assessed the prognostic power of CRP was > 10 mg/L (n = 19; 30.1%), followed by > 5 mg/L (n = 5; 7.9%). As for the 33 that related albumin to overall survival, the most common cutoff points studied were < 3.5 g/dL (n = 13; 39.4%) and < 3.0 g/dL (n = 5; 15.1%). According to the results of a meta-analysis by Li et al. [7] different CAR cutoff points, ranging from 0.25 to 6.7, are used to describe the association between CAR and overall survival [29].
Regarding the intercept values, our results provided a combined estimate of the associations between participants and within participants over time as a useful “end point” indication of predicted or expected values for that variable as death approaches. The clinical interpretation consists in observing that these values were above the normal reference limits or thresholds values of these biomarkers [21]. In addition, it is worth highlighting that according to our crude and adjusted LME models, changes in inflammatory biomarkers over 90 days were associated with death regardless of age, sex, KPS, primary tumor site, distant metastasis, previous systemic treatment, BMI, percentage weight loss in six months, HGS, and score of PG-SGA SF. In practical terms, for example each 0.11mg/L increase in CRP above the mean CRP at baseline was associated with one-day survival reduction, or considering the mean baseline value is expected a 0.9 to 1.8 g/dL decrease in serum albumin levels and an increase of 9.0 to 10.8 mg/L in CRP and 5.4 CAR levels until patient’s death. Another important point was that the inclusion of more than two measures in the multivariate model did not alter our results. It is interesting to note that two routine measurements of blood-based biomarkers were enough to observe such dynamics in relation to death.
Although the current study presents clinically relevant data, there are strengths and weaknesses that should be considered when interpreting our findings. The strength is the longitudinal design of the study, which allowed a better understanding of the relationship between the biomarkers evaluated and the patients’ prognosis. A potential weakness was the high number of excluded patients. However, no differences were observed in relation to demographic and clinical variables when we compared the excluded and the analyzed patients. To the best of our knowledge, this is the only study that has described changes in albumin, CRP, and CAR values in patients with terminal cancer receiving exclusive palliative care using an LME model. Thus, comparisons between our data and the available literature are limited. Finally, this was a single-center study without an external validation cohort, which limits generalizability of the study results.
Identification of biomarkers of dying is an important area for future research, which could contribute to improved clinical practices for patient management. However, further investigations in multicenter studies are required to understand how these laboratory measures and proposed cutoffs should be used to better employ biomarkers in prognostication of terminal cancer.