Similarly, the ODSS discriminated all 3 pain subgroups (legs score and sum score) or the pDSPN-s subgroup (arms score, P < 0.001; Table 5 and Suppl. Fig. 3, available online at http://links.lww.com/PAIN/A475), and the ODSS sum score correlated with severity of pain (r = 0.60; P < 0.001).
3.8. The relation between clinical examination and quantitative sensory testing
Quantitative sensory testing thermal and mechanical parameters correlated well with the clinical scores when considering all study participants, that is, including those with and without NeuP (Suppl. Table 5, available online at http://links.lww.com/PAIN/A474). The mTCNS sum score correlated negatively with QST z-scores (P < 0.01 for CDT, WDT, TSL, CPT, HPT, MPT, MPS, MDT, and VDT; P < 0.05 for PPT and wind-up ratio). Similarly, the ODSS sum score correlated negatively with most QST z-scores (P < 0.001 for CDT, WDT, TSL, CPT, HPT, and MPS; P < 0.05 for MPT). Finally, the mMRC sum score correlated negatively with most thermal QST z-scores (P < 0.01 for CDT, WDT, TSL; P < 0.05 for CPT). Therefore, the higher the clinical scores, that is, more severe the DSPN, the greater was the loss of sensation on QST parameters. The correlation was stronger for thermal QST parameters.
3.9. Nerve conduction studies and skin biopsies
Nerve conduction studies were abnormal in all but 7 DSPN cases, in whom the diagnosis of DSPN was based on abnormal IENFD findings. There were no differences in any of the evaluated NCS parameters between pain subgroups (Suppl. Table 6, available online at http://links.lww.com/PAIN/A474).
IENFD was determined in 9 DSPN cases with normal NCS and was abnormal in 7 cases, in whom the diagnosis of DSPN was based on IENFD decrease; the median IENFD was 2.8 (range 0-10.0) fibers/mm.
3.10. Logistic models to predict pain
Using multivariate logistic regression analysis and the most robust independent predictors (mTCNS total score ≥7, mMRC leg total score <60, WDT z-score <1.5 and abnormal serum creatinine), it was possible to find a model predicting the presence of NeuP with high sensitivity (>90%) and moderate specificity (76%) (Table 6). Accuracy of the predictive models in terms of sensitivity, specificity, and positive and negative predictive value was even higher in model 2, predicting/discriminating pDSPN with severe pain compared with painless cases and based on DSPN severity predictors (mTCNS total score ≥7, and ODSS total score >1; Table 6).
As mTCNS scores reflecting neuropathy severity seem to be the strongest predictors of NeuP, we compared characteristics of the pDSPN and nDSPN subgroups matched for the severity of neuropathy. Patients with pDSPN were more frequently women (P < 0.001; Suppl. Table 7, only selected parameters with significant differences included; available online at http://links.lww.com/PAIN/A474).
This study reports detailed phenotyping using structured neurological examination and QST in a well-defined largest-ever published cohort of patients with DSPN. Key findings are that the presence and severity of NeuP was associated with more advanced diabetic neuropathy leading to higher disability and more frequent and advanced dysfunction of sensory fibers. No correlation was found between NeuP and factors related to diabetes and its control with the exception of laboratory signs of nephropathy. Our study, conducted in a large independent cohort, confirms key findings of a recent large-scale cohort study of DSPN subjects,38 and adds additional information.
There is a continuous effort to uncover distinct sensory profiles specific not only for the presence of NeuP as such, but also for predicting the response to therapy. Quantitative sensory testing findings in previous studies revealed a heterogeneity of sensory profiles in different pain syndromes, and some sensory profiles have been suggested to represent specific pathophysiological mechanisms.4,24 In a large cohort of 343 patients with painful polyneuropathy of different etiologies, 83.4% had a QST abnormality.24 Gain-of-function abnormalities were found in 31.2% and loss-of-function abnormalities in 72.9%.24 In previously described DSPN cohorts, loss-of-function abnormalities of small fiber–mediated and large fiber–mediated sensory modalities disclosed by not only QST, but also by clinical and electrophysiological methods was predominant, whereas gain-of-function abnormalities were only found in a minority,21,42 which corresponds to our findings.
Correlations of thermal QST abnormalities (CDT and WDT thresholds) with the severity of NeuP in patients with diabetic neuropathy have been reported previously in a smaller study.21 Others41 suggested that severe neuropathy is associated with an increased risk of developing pDSPN, although their small cohort was hospital-based and thus selective. In a cohort of diabetic patients with a low prevalence of neuropathy, pDSPN was more likely to occur in those with clinically manifest neuropathy.31 In a smaller community-based study, 51 patients with pDSPN had a higher severity of neuropathy compared with patients with painless DSPN.8
The PiNS study38 was the first that used the DFNS QST protocol in a large cohort of DSPN subjects with and without NeuP and correlated sensory profiles with the severity of NeuP, measures of neuropathy severity, and disability. In this study, the QST pattern of diabetic neuropathy was consistent with loss of function in both large and small sensory fibers. Furthermore, study participants with moderate to severe NeuP had the greatest loss of function in QST and more severe neuropathy assessed with neuropathy disability scores.38 Our results are in concordance with all these findings. The DA QST profile was predominant in our patients with pDSPN, and the frequency and severity of thermal loss correlated not only with the presence and severity of NeuP, but also to severity of neuropathy and disability. Gain-of-function sensory abnormalities in general were rare in pDSPN in both the PiNS and our study. Dynamic mechanical allodynia was the only gain-of-function abnormality in the PiNS, whereas we also observed a high frequency of PHS, in concordance with the findings of Maier et al.24 Paradoxical heat sensations was more frequent in our patients with moderate to severe pain. This is plausible because PHS represent disturbances of thermal processing in the peripheral or central nervous system. Such disturbances were recently reported as a typical component of a “loss of function” QST sensory cluster in neuropathic pain syndromes including polyneuropathies.4 The IN pattern, recently described as a “thermal hyperalgesia” sensory cluster,4was only present in a minority of our patients with painful DSPN (13.6%), although not so rarely as in the PiNS study (6.3%).38 Similar to the PiNS study,38 the DA profile prevailed in our study. Patients with the IN profile showed lower neuropathy disability scores, shorter duration of pain, higher level of pain catastrophizing, and different characteristics of pain associated with lower GCPS and NSPI scores in comparison with most patients with pDSPN with the DA profile. Further research is needed to confirm whether or not the IN profile might represent a promising target for stratification of patients for analgesic treatment and future drug trials.
Correlations between NeuP and hyposensitivity to small-fiber–mediated thermal perception in both our and the PiNS study, and the absence of any correlation between NeuP and NCS underline the importance of small-fiber loss or dysfunction for the generation of pDSPN. The subpopulation of pDSPN subjects with less hyposensitivity to thermal and mechanical pain stimuli, either manifesting as the IN profile or displaying gain-of-function abnormalities like DMA or PHS, might represent a subgroup with specific mechanisms of NeuP.
Study participants with more severe NeuP reported higher scores for anxiety, depressive symptoms, and pain catastrophizing, and also more frequently reported other chronic pain compared with the study participants with no NeuP and mild NeuP. The association of emotional distress with the severity of NeuP in DSPN, although not indicating causal relationship, is in concordance with a previous study that reported a high prevalence of depression and anxiety in pDSPN, and which underlined the necessity to integrate these psychological factors into treatment of NeuP in DSPN.29
As for demographic factors, the proportion of women displaying severe NeuP was higher compared with men. The “risk factor” female sex was already reported several times.1,12,17,19 The influence of age, reported by some studies,18,40,45,46 was neither confirmed in our study nor in PiNS study.38
Unsatisfactory diabetes control, usually expressed as elevated HbA1c levels, and other factors associated with diabetes have been repeatedly associated with the development of DSPN, whereas association of factors related to diabetes with painful DSPN discussed is contradictory.32 Among factors related to diabetes reported as associated with increased risk of pain in some studies, but not confirmed in the others, were diabetes duration,17–19,31,40 diabetes type 119 and type 2,1 dyslipidemia (low high density lipoproteins,40 increased triglycerides40), obesity, increased weight, body mass index or waist circumference,33,40,45,46 peripheral arterial disease,45,46 and nephropathy.40 The PiNS study reported higher levels of HbA1c in painful DSPN38 as the only parameter related to pain, although the association was not as robust as in the other factors, such as severity of neuropathy. In our study, we were not able to confirm an association of painful neuropathy with any of these parameters with the exception of a higher proportion of increased creatinine serum levels or decreased estimated glomerular filtration rate as a sign of nephropathy in patients with pain. Increased serum level of methylgyoxal has been shown in painful diabetic neuropathy5 and knockdown of glyoxalase 1 in mice causes alterations in kidney morphology indistinguishable from those caused by diabetes,16 but the possible link between pain and nephropathy in diabetes is still unclear.
In our study, several factors were associated with the presence and severity of NeuP. We calculated a predictive model including the most important independent predictors of pDSPN. This model included neuropathy severity (mTCNS total score, motor function in the legs [mMRC]), pain catastrophizing and anxiety (PCS and STAI-T total scores), and loss of C-fiber function (WDT). The model was able to predict the presence of pain in DSPN with excellent sensitivity and moderate specificity.
One of the limitations of our study was that the pain scoring was not based on a diary, but on a one-time assessment. As analgesic therapy was not stopped before assessment of pain severity, it might have influenced subclassification of painful cases into pDSPN-m and pDSPN-s subgroups. In fact, 21 painful DSPN cases who reported mild pain in the last week before assessment (the mean NRS during the last week between 1 and 3 points), reported pain of higher severity (NRS >4) before administration of analgesic treatment. Numerical rating scale values reported retrospectively with a delay of several months or years are, however, less reliable for subclassification of painful cases.
Despite the fact that patients were included consecutively into the study, the proportion of painful cases is higher than expected. This might be due to a higher motivation of patients with painful DSPN to participate.
The presence of foot pain that per definition must not be present in the painless cases was one of the items of mTCNS that were used to compare severity of neuropathy between painless and painful DSPN subgroups. This fact might slightly influence the differences in mTCNS symptoms and total scores, but not the mTCNS sensory tests subscore or the conclusion concerning the influence of severity of neuropathy on pain presence and severity in DSPN.
In conclusion, NeuP presence and severity is related to neuropathy severity, predominant thermal sensory loss, female sex, and nephropathy. It is also associated with levels of anxiety, depressive symptoms, and pain catastrophizing. A minority of pDSPN subjects display gain QST abnormalities. Different sensory profiles might represent distinctive pathophysiological mechanisms of NeuP in diabetes and new target populations for future pain trials.
Conflict of interest statement
J. Raputova, I. Srotova, E. Vlckova, I. Kovalova, B. Adamova, J. Bednarik, H. Rittner, C. Rebhorn, L. Forer, and F. Birklein report grants from FP7 EU Grant during the conduct of the study. N. Üçeyler reports grants from FP7 EU Grant during the conduct of the study; grants from Genzyme, grants from Shire, other from Daiichi Sankyo, personal fees from Baxalta, outside the submitted work. C. Sommer reports grants from FP7 EU Grant during the conduct of the study; personal fees from Air Liquide, personal fees from Astellas, personal fees from Baxalta, personal fees from CSL Behring, personal fees from Genzyme, personal fees from Pfizer, personal fees from UCB, grants from Kedrion, outside the submitted work. The remaining authors have no conflicts of interest to declare.
Supported by the European Commission (602133—ncRNAPain), and by the project “CEITEC—Central European Institute of Technology” (CZ.1.05/1.1.00/02.0068) from European Regional Development Fund.
The authors thank all patients for their participation and the research support team and medical and nursing staff at University Hospital in Würzburg, Mainz, and Brno for assistance with recruitment (Jana Novohradska, Barbara Broll, Barbara Dekant, Mathias Leinders, Sonja Mildner).
Author contributions: J. Raputova and I. Srotova were involved in the literature review, data collection including QST, data interpretation, data analysis, prepared the first draft of the manuscript and contributed equally to the article. I. Kovalova and C. Rebhorn contributed to data collection and data interpretation. E. Kralickova contributed to data interpretation and analysis (neuropsychological tests). B. Adamova contributed to collection and interpretation of electrophysiological data. J. Belobradkova, J. Olsovsky and P. Weber contributed to recruitment and pre-screening of diabetic patients in 2 diabetologic centers in Brno. L. Dusek contributed to planning of study design and power analysis, performed statistical analysis and contributed to manuscript preparation including figures. J. Jarkovsky contributed to interpretation of data (statistical analysis). L. Forer contributed to design and administration of online database used for data management. E. Vlckova was involved in literature review, contributed to study design, data collection (electrophysiological data), data interpretation, data analysis, prepared draft of the manuscript. N. Üçeyler contributed to study design, was involved in data collection, data interpretation, and reviewed/edited manuscript. H. Rittner contributed to data interpretation, data analysis, and reviewed/edited manuscript. C. Sommer and F. Birklein contributed to study design and data interpretation, to discussion and reviewed/edited manuscript. J. Bednarik assumed overall responsibility for the study, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. He contributed to study design, data analysis, data interpretation, manuscript preparation including figures, and writing, and prepared the first draft of the manuscript. All authors approved the final manuscript.
Supplemental digital content
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Painful diabetic neuropathy; Sensory profile; Quantitative sensory testing; Risk factors
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