However, our understanding of the biophysical and pharmacological properties of the channels in sensory neurons is largely based on the study of heterologous systems or rodent tissue, despite evidence that both expression systems and species differences influence these properties. Therefore, we sought to determine the extent to which the biophysical and pharmacological properties of VGSCs were comparable in rat and human sensory neurons. Whole cell patch clamp techniques were used to study Na+ currents in acutely dissociated neurons from human and rat. Our results indicate that while the two major current types, generally referred to as tetrodotoxin (TTX)-sensitive and TTX-resistant were qualitatively similar in neurons from rats and humans, there were several differences that have important implications for drug development as well as our understanding of pain mechanisms.Available evidence indicates voltage-gated NaDOI:http://dx.doi.org/10.7554/eLife.23235.001 Our results suggest that while the two major Na+ current from the more slowly activating and slowly inactivating TTX-resistant (TTX-R) Na+ current, as we have previously done in the rat . The average age of the donors was 45.2 years with a range of 13 to 77. Additional demographic data are summarized in  the rat . We subs the rat . Based o+ channels in sensory neurons has largely been in the context of pain. In this context, data from guinea pig and rodents suggest that neurons with a small to medium cell body diameter are more likely to give rise to slowly conducting axons  and −62.2 ± 4.3 pA/pF (n = 78), respectively) compared to those in rat neurons (−47.7 ± 3.3 pA/pF (n = 26) and −42.6 ± 4.6 pA/pF (n = 26), respectively). Furthermore, the ratio of TTX-S to TTX-R current density was significantly greater in human than rat DRG neurons .+ currents in human DRG neurons. An inflammatory soup, consisting of bradykinin (10 μM), histamine (1 μM) and prostaglandin E2 (1 μM), was applied to neurons following establishment of stable recordings. Consistent with previous results from rat and subsequently mouse sensory neurons  male rats that were deeply anesthetized at the time of tissue collection. Unfortunately, we were unable to rule out the time between cross-clamp and tissue collection as a factor contributing to the differences observed, as preliminary results indicated that the viability of rat DRG neurons fell off precipitously 15 min after death, even in rats perfused with ice-cold saline. However, we suggest that neither of the other two main factors were likely to contribute to the differences observed, as there was no detectable influence of either age (at least comparing neurons from young (<30) and old (>65) donors) or donor sex on the biophysical properties of Na+ currents assessed (data not shown). It is also possible that the larger currents and larger cell body size of human DRG neurons resulted in a decrease in clamp control that contributed to the hyperpolarizing shift in both TTX-R and TTX-S current G-V curves as well as the faster rates of current activation observed in human neurons. Arguing against this possibility, however, is the fact that while the slopes of the G-V curves for both current types were steeper in human than in rat neurons , these small differences could not account for the observed differences in the V0.5 of activation, nor are they consistent with a loss of clamp control, which would be predicted to result in a much larger decrease in the slope of the G-V curve. In addition, differences in the V0.5 of activation persisted when data from only the smallest human and largest rat neurons were compared. For example, the V0.5 of current activation for TTX-R in the overlapping subpopulation of rat and human sensory neurons were −2.1 ± 0.4 mV and −10.8 ± 1.7 mV, respectively.While several potentially important differences were observed in the Na2+ currents while maximizing patch stability had a significant influence on the biophysical properties of the currents recorded. That is, the properties of the currents observed in rat neurons recorded under conditions identical to those used for the study of human neurons, were comparable to those we have previously observed  male Sprague-Dawley rats ) were used for all experiments. Rats were housed two per cage in a temperature and humidity controlled, Association for Assessment and Accreditation of Laboratory Animal Care International (AAALAC) accredited animal housing facility on a 12 hr:12 hr light:dark schedule. Food and water were available ad libitum. All procedures were approved by the University of Pittsburgh Institutional Animal Care and Use Committee and performed in accordance with National Institutes of Health guidelines for the use of laboratory animals in research. The number of rats used in this study was based on estimates made from variability observed in our previous biophysical and pharmacological analysis of NaDRG were obtained from organ donors following collection of tissue needed for transplantation purposes as previously described . FollowiAdult rat sensory neurons were surgically obtained, enzymatically treated and mechanically dissociated as previously described . Cells w2 1, EGTA 11, HEPES 10, Mg-ATP 2, and GTP 1; pH was adjusted to 7.2 with Tris-base and osmolality was adjusted to 310 mOsm with sucrose. The bath solution consisted of (in mM): NaCl 35, Choline-Cl 65, TEA-Cl 30, CaCl2 0.1, MgCl2 5, CdCl2 0.1, HEPES 10, and glucose 10; pH was adjusted to 7.4 with Tris-Base, and the osmolality adjusted to 320 with sucrose.Whole-cell patch-clamp recordings were performed with an Axopatch 200B controlled with pClamp (v 10.2) software  used in combination with a Digidata 1320A A/D converter (Molecular Devices). Unless otherwise noted, data were acquired at 20 kHz and filtered at 5 kHz. Borosilicate glass  electrodes were 0.75–2 MΩ when filled with an electrode solution that contained (in mM): Cs- Methansulphonate 100, TEA-Cl 40, NaCl 5, CaCl+ reduced to 20 mM. Thus, all data included in this data set were from neurons <24 hr in culture. A p/−4 leak subtraction was employed from a holding potential of −80 mV. Steady-state availability curves were determined for each neuron in which both TTX-S and TTX-R currents were detected, so as to confirm the pre-pulse potential amplitude necessary for relief of steady-state inactivation, as well as the pre-pulse potential at which TTX-S currents were completely inactivated  as a 1 mM stock solution, and stored at 4°C until use. A-803467 was dissolved in dimethylsulfoxide (DMSO) at a concentration of 10 mM, immediately before use, and subsequently diluted in bath solution. Bradykinin was dissolved in 0.1% acetic acid as a 10 mM stock solution, and stored at −20°C until use. Prostaglandin E2 was dissolved in ethanol as a 10 mM stock solution and stored at −20°C until use. Histamine was dissolved in dH2O as a 10 mM stock solution and stored at −20°C until use. Lidocaine was prepared as a 10 mM stock solution with 5 mM Na-HEPES buffered dH2O, with a pH adjusted to 7.0 with TEA-OH, and stored at −20°C until use.+ current reversal potential (Vr) was determined for each neuron from the linear phase of the I-V curve. Conductance-voltage curves (G-V) were determined by dividing current evoked at each test potential (Vt) by the driving force on the current (Vr – Vt). A two-pulse protocol was used to determine the recovery from inactivation, where the first pulse to 0 mV, was used to completely inactivate Na+ currents, and the second pulse to −50 mV or −90 mV of increasing duration was used to drive recovery of TTX-R and TTX-S currents from inactivation, respectively. The second pulse was followed by a final test pulse to 0 mV. Steady-state inactivation and G-V curves were fitted with modified Boltzmann equations so as to determine maximal conductance (Gmax), the voltage at which current were either half inactivated or half activated (V0.5), as well as the slopes of the two curves. Recovery from inactivation data were fitted with a double exponential. Current activation, inactivation, and when possible, deactivation, were determined with a single exponential fitted to the rising phase (activation), falling phase (inactivation), and tail currents (deactivation) of currents evoked with an I-V protocol. Use-dependent block was determined with 20 pulses to 0 mV delivered at 1, 2, or 5 Hz. Fractional use-dependent block was estimated by dividing current evoked after the 20th pulse by the current evoked after the first. Finally, concentration-response curves were fitted with a modified Hill equation to enable estimation of the concentration needed to block 50% of evoked current.Amplifier circuitry was used to estimate membrane capacitance which was used to estimate current density. NaA t-test was used for statistical comparisons between human and rat data, where a difference with p<0.05 was considered statistically significant. If comparisons were made between human and rat across voltage, a two-way ANOVA was used. Prior to use of a t-test of ANOVA, data to be compared was assessed for normality and equal variance. Linear regression and a one-way ANOVA were used to assess the potential impact of age on evoked currents. In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.+ Currents in Human Dorsal Root Ganglion Neurons" for consideration by eLife. Your article has been reviewed by two peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Gary Westbrook as the Senior Editor. The following individuals involved in review of your submission have agreed to reveal their identity: Bruce P Bean (Reviewer #1); Stephen Cannon (Reviewer #2).Thank you for submitting your article "Voltage-Gated NaThe reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.Summary:This manuscript describes the biophysical properties and pharmacology of voltage-dependent sodium channels in dorsal root ganglion neurons from adult humans and provides a comparison of the characteristics of those sodium currents to the more common experimental model of rats. The work identifies both similarities and differences between the human and rat preparations.Essential revisions:Both reviewers found the work to be very important, informative, and well done. Their compiled favorable comments are quoted verbatim below in "General Comments." Several key points came up that require addressing, however, relating to pharmacology, which was seen as the weakest area of the manuscript, and a few other aspects of voltage protocols and cell selection. The points that require addressing are summarized here and elaborated upon in the reviewers' words under "Detailed Points for Essential Revisions."1) Verify that the very surprising results indicating that the primary TTX-S channels in humans (a) are not 1.7 and (b) are not blocked by the broad-spectrum Protoxin II are not influenced by plausible sources of error, e.g., those relating to complications of peptide perfusion.2) Omit or address the very unexpected result that TTX increases ramp current, which also raises questions about the efficacy/specificity of drug perfusion.3) Clarify voltage protocols used and (a) use the information to strengthen/clarify/curtail conclusions based on pharmacology and (b) validate  the prepulse approach as opposed to a pharmacological approach to separate the currents in humans.4) Test and/or clarify ambiguities arising from size differences and size-based selection to verify that differences between species weren't based on clamp artifacts from the different sizes of neurons.5) Address or omit the deactivation time constant measurements, about which specific questions were raised.We recognize that the availability of human tissue may be limited. If it is not possible or practical to address the issues directly, a (less desirable) alternative is to tone down or qualify the conclusion that Nav1.7 may not contribute much to the TTX-S current, indicating that further pharmacological work is necessary for a definitive conclusion.General commentsThis is important experimental information, because almost all previous knowledge about the properties and functional roles of sodium channels in DRG neurons has come either from studies on rodent DRG neurons or on cloned human channels in heterologous expression systems. Since an important goal of the research area, especially on the pharmacology, is to help guide development of new treatments for pain, possible differences in the pharmacology of native human channels compared to those in rodent neurons or to human channels in heterologous systems are of great interest. Consequently, the surprising results in this manuscript suggesting that the pharmacological properties of both TTX-resistant and TTX-sensitive populations of sodium channels in human neurons differ from those in rat neurons give the manuscript considerable interest. Beyond this, the work shows, very surprisingly, that obtaining electrophysiologically healthy neurons acutely-dissociated from human DRGs is actually easier (or at least has a higher success rate once the DRGs are obtained) than with rat DRG neurons of fully adult animals. The technical quality of the voltage-clamp studies in the manuscript are excellent and the volume of data for many of the figures leaves no doubt of the possibility of obtaining statistically impressive data from human neurons. Thus an important secondary message of the manuscript will be to encourage others to study human DRG neurons.An excellent feature of the work is a detailed comparison with the properties of rat DRG neurons studies with the same protocols. This gives confidence that the differences seen are genuine and not the result of slightly different protocols .In general, the biophysical description of both the TTX-R and TTX-S components of sodium current are thorough and convincing .The repertoire of voltage gated sodium channels (VGSCs) in dorsal root ganglia (DRG) and their modulation by inflammatory mediators are important for the perception of pain and the hypersensitivity of pain syndromes associated with tissue injury. Much of this knowledge has come from studies in rodent DRG neurons or from human VGSCs expressed in heterologous systems. This practical constraint leaves open the question of whether the VGSC properties of human DRG neurons are comparable. Zhang and colleagues have recorded Na currents from human DRG neurons acutely isolated from organ donors. In broad terms, the two major classes of Na currents (TTX-R and TTX-S) were both present and comparable in rat and human DRG neurons. Several differences, however, were identified and these may have important consequences for the pathogenesis of pain syndromes and for therapeutic strategies. For example, the putative NaV1.8-selective blocker, A803467, did not cause a detectable reduction of human TTX-R currents until 1 μm was applied, whereas rat TTX-R currents are much more sensitive to block. Human TTX-R currents also had no evidence of use-dependent cumulative inactivation or use-dependent lidocaine block (1-5 HZ) whereas rat TTX-R current had substantial use dependence for both. Differences of intrinsic gating were also observed. Most striking were faster activation and recovery from inactivation for human TTX-S currents as compared to rat TTX-S. Overall, this is a carefully designed and conducted study that demonstrates while the VGSC properties in DRG neurons are overall similar for rat and human, there are clear differences that may have important implications for development of therapeutics.Detailed points for essential revisions:1) The area in which the results in the manuscript could be stronger is the most important – the conclusion that the TTX-S channels in the human neurons are not primarily carried by Nav1.7 channels. If true, this is very important, since multiple companies are developing Nav1.7 inhibitors with the assumption that these channels are critical for the function of nociceptors. Also, the conclusion that Nav1.7 do not contribute to the TTX-S currents is opposite to a previous study of human DRG neurons in which it was concluded that the majority of the TTX-S current was carried by Nav1.7 channels, based on inhibition of 75% of the current by 30 nM PF-05089771, a fairly selective blocker of Nav1.7 channels. The authors point out this previous study used neurons in culture for up to 9 days, which could cause an upregulation of Nav1.7 channels – a valid point. They also suggest that the result could have been from imperfect selectivity of PF-05089771, which while possible seems a lot less likely, since Alexandrou et al., 2016 saw big effects of 30 nM PF-05089771, which would be expected to have minimal effects on any of the other channel types.Here the authors present two pieces of evidence arguing against mediation of TTX-S by Nav1.7. One is the lack of effect of 10 nM Protoxin II. It seemed very puzzling that the authors chose protoxin II as a blocker, because a previous review of the properties of this toxin stated "ProTx-I and ProTx-II inhibit all sodium channel (Nav1) subtypes tested with similar potency." . This is certainly not clear from the presentation, where a reader would naturally infer that the toxin was used because it had selectivity for Nav1.7. The evidence against Nav1.7 would be far stronger if the authors had used PF-05089771, which is much more selective. This compound has been commercially available (from both Σ and Tocris) for some time.Given the efficacy of protoxin-II against all sodium channels, the lack of effect is very surprising whatever channels underlie the TTX-S current. A possible experimental problem with potent peptide toxins of this type is that they can bind to plastic tubing and glassware and be difficult to remove, so that subsequent application appears to have no effect because of presence of the agent under "control" conditions. I raise that because the lack of any effect of the toxin is unexpected whatever channels the sodium currents are coming from and because we have experienced that insidious problem several times in my own lab with similar toxins – a problem that could only be resolved by completely replacing tubing and chambers.2) The second piece of evidence that authors present against the contribution pf Nav1.7 channels is the most puzzling result in the paper – that TTX not only did not inhibit a current induced by ramp of voltage but actually enhanced the current and shifted its voltage dependence to more hyperpolarizing voltages. The shift of current to more hyperpolarized voltage makes no sense at all and suggests some sort of experimental problem. It would suggest that TTX enhances sodium current for small depolarizations which has never been described for any channels. At a minimum, the authors need to follow up the ramp experiment with step depolarization experiments to characterize this effect in more detail. Even if TTX simply had no effect on the ramp current, this is only weak evidence against mediation by Nav1.7. It could reflect for example faster or more complete closed-state inactivation in human Nav1.7 channels versus rodent Nav1.7 channels, which would be interesting. The authors did not compare closed-state inactivation in the human vs rat neurons so this seems like an open possibility.3) It would be helpful if all the figures had clear statements of exactly what the voltage protocols were, which were not always clear to me. In Additionally, the separation of TTX-R and TTX-S components by using a conditioning voltage pulse (instead of the more laborious method of TTX block) is a key aspect of the analysis and interpretation. Deficiencies in this separation technique, which may be different for rat versus human DRG neurons, could result in apparent differences or underestimate differences. With that in mind, how was it possible to determine the availability curve for TTX-R specific currents in A great feature of the work is the comparison to studies in rat neurons done in the same lab. If these were actually done in parallel, using for example exactly the same batches of pharmacological reagents and by the same experimenter, this might be mentioned explicitly as it further strengthens the point that the differences are genuine and not the result of differences in procedures or reagents.4) A missing piece of information is exactly how the authors selected which cells to record from. From the fact that they all had TTX-R current, the experimenter presumably chose smaller-diameter cells to record from, but what exactly was the selection criterion? Do the authors think the cells all correspond to cell bodies of C-fibers? The authors have discussed the challenges of high Na current density and series resistance that often plague studies of VGSCs. Because human DRG soma are much larger than rat, the demands on clamp quality would be systematically more challenging in recordings from human than rat neurons. This might cause a systematic difference in the apparent gating behavior. The distribution of cell capacitance did, however, have a region of overlap around 50 pF. Perhaps a subset of rat and human DRG neurons with comparable size could be analyzed to provide reassurance that the observed species differences were still detectable in a population of similar-sized neurons?5) The interpretation and discussion of VGSC deactivation was confusing , a Reviewing editor, and two reviewers.Thank you for resubmitting your work entitled "Voltage-Gated NaThe manuscript has been improved but there are some remaining issues that need to be addressed before acceptance, as outlined below:"TTX-S" and "TTX-R" are used as shorthand for prepulse subtraction, which is validated for control solutions in 1) To make sure that readers are clear that "TTX-S" and "TTX-R" actually refer to currents inactivated at -40 mV and available at -40 mV,2) To ensure that the prepulse subtraction procedure is kept in mind in interpreting the effects of the blockers, and3) To limit or constrain claims that NaV1.7 is not the primary TTX-S current, as appropriate.Please also include a statement about informed consent (as appropriate) for collection of human tissue.The full comments pertaining to the requested revisions are below and have been agreed upon by all participants in the review.General assessment and major comments:The most important change in the manuscript is new data with the Pfizer Nav1.7 inhibitor PF-05089771, which the authors find inhibits the TTX-S current quite potently, with an IC50 of about 10 nM. In addition, the authors have clarified some the details of the voltage protocols and cell selection.I was very surprised that with the new data showing potent block of the TTX-S current by PF-05089771, the authors still end up concluding that Nav1.7 channels make little contribution to the TTX-S current in human DRG neurons. If it were my data, my interpretation of the overall set of the results the authors present would be the opposite, that the TTX-S current is likely to be primarily from Nav1.7 channels based on its sensitivity to PF-05089771, but that it is (interestingly) less sensitive to Protoxin-II than rat Nav1.7 channels. The observation that PF-05089771 also seems to inhibit TTX-R currents in human DRG neurons at higher concentrations is interesting and important. So, like most small molecules, the selectivity of PF-05089771 is imperfect. That is important to know, and constitutes another of the many interesting points in the manuscript about different pharmacology of the native currents in human DRG neurons compared to rat DRG neurons or heterologously-expressed human channels. However, it is still true that PF-05089771 inhibits the TTX-S current with significantly higher potency, and about what is expected from the effects on cloned human Nav1.7 channels. So my interpretation would be that the results with PF-05089771 imply that the TTX-S current is mostly from Nav1.7, but that the compound is less selective than previously realized and at higher concentrations also inhibits native human Nav1.8 channels – a very important point that adds to the significance of the results in the manuscript.To me, the flow of the revised manuscript now seems strange in that final set of experimental results in Results showing potent block by PF-05089771 gives the reader the impression that the TTX-S current is likely mainly Nav1.7, but then in the Discussion the first mention of this issue suggests the opposite without explaining why. The first part of the Discussion summarizing the pharmacology is very reasonable and straightforward . However, the suggestion that the contribution of NaV1.7 varies across subpopulations of human sensory neurons is also consistent with the suggestion that NaV1.7 is not the dominant, let alone only VGSC subtype in human sensory neurons." In the original version, this sentence referred to a stated conclusion in Results based on the protoxin-II results that Nav1.7 was not the dominant current. But in the revised version, there has been no explanation yet of why the authors would conclude this, and it seems to come out of nowhere.The authors' argument about Nav1.7 comes later, in the paragraph starting "The possibility that NaV1.7 may not be the dominant subunit underlying TTX-S currents, let alone significantly contribute to these currents in human DRG neurons, as suggested by our inflammatory mediator results, was further supported by our results with Pro-Tx II and PF-05089771." This is where the authors argue that the block by PF-05089771 is not good evidence for Nav1.7 mediating the TTX-S because they find that PF-05089771 at higher concentrations also inhibits the TTX-R current. To me, the argument in this paragraph was not convincing, as it essentially argues that the lack of effect of protoxin-II is more convincing than the potent block by PF-05089771. .There is a reason to be cautious about interpreting the results with PF-05089771 and Protoxin-II, because both interact with their target channels in a state-dependent manner. The authors did not study the effects of the blockers on isolated currents from TTX-R or TTX-S channels, but rather used a prepulse procedure to distinguish them by inactivation. They show that this protocol works in the absence of drugs, but obviously it may not in the presence of drugs that can modify the voltage-dependence of inactivation. In my view, that should introduce a lot of caution in interpreting these results. In fact, in reading the paper quickly, it would be very easy for a reader to miss the important point that when the authors refer to "TTX-S" and "TTX-R" currents, this is really shorthand for "currents available from -80 but inactivated by a prepulse to -40 mv" and "currents remaining after a prepulse to -40 mV". Although the authors clearly state this in the course of Results, I think it is an important point to reiterate in the Discussion, because it is an important qualification for interpreting the pharmacological results .Because of these issues, I did not find the authors' suggestion that Nav1.7 accounts for little if any of the TTX-S current convincing and it would not be my interpretation. Of course, the authors should be free to interpret their own data, but they should probably consider at least qualifying their conclusion.Whatever the interpretation given, the experimental results are very interesting and leave no doubt that the detailed pharmacology of the channels in human cells is quantitatively different in interesting ways compared to the currents in rat neurons, probably most importantly in the relative lack of use-dependence with lidocaine and the apparent significant sensitivity of TTX-R channels to PF-05089771.I did not see a statement about informed consent for the collection of the human tissue, which seems important. Presumably this is the authors' 2015 paper that is cited for the Methods, but it seems that it should be here also. Essential revisions:Both reviewers found the work to be very important, informative, and well done. Their compiled favorable comments are quoted verbatim below in "General Comments." Several key points came up that require addressing, however, relating to pharmacology, which was seen as the weakest area of the manuscript, and a few other aspects of voltage protocols and cell selection. The points that require addressing are summarized here and elaborated upon in the reviewers' words under "Detailed Points for Essential Revisions."1) Verify that the very surprising results indicating that the primary TTX-S channels in humans (a) are not 1.7 and (b) are not blocked by the broad-spectrum Protoxin II are not influenced by plausible sources of error, e.g., those relating to complications of peptide perfusion.We agree with reviewers that this is an important concern, and as noted below, have addressed this issue with additional data and further discussion. The additional data include results from the application of Protoxin II to rat DRG neurons, as well as data from human DRG neurons in response to the putative NaV1.7 selective small molecule channel blocker PF-05089771. With respect to the former, we were able to demonstrate that Protoxin II blocked a fraction of the TTX-S current in rat DRG neurons, arguing against potential complications with handling the peptide. With respect to the latter, we were able to demonstrate complete block of TTX-S currents in human DRG neurons with PF-05089771 with an IC50 of ~6 nM, remarkably close to that reported by Alexandrou and colleagues . However, in marked contrast to heterologous expression results reported by Alexandrou and colleagues, we observed a significant reduction in TTX-R current in human DRG neurons treated with PF-05089771, with an IC50 of ~50 nM. Given that Alexandrou and colleagues reported that heterologously expressed NaV1.8 was resistant to PF-05089771 at concentrations as high as 10 μM, these observations underscore the need to validate results from heterologous expression studies on native proteins expressed in their native environment. The observation that PF- 05089771 has limited utility for the differential block of TTX-S and TTX-R currents in human DRG neurons raises the possibility that this compound also has limited utility for the differential block of NaV1.7 relative to other TTX-S channels likely present in human DRG neurons. Thus, we would argue that when considered in the context of our results with Protoxin II and our ramp current data, the limited selectivity of PF-05089771 on native channels lends further support to the suggestion that NaV1.7 is not the only, or even dominant channel in human DRG neurons.We have expanded our discussion of these issues to address several points. The first concerns the selectivity of Protoxin II. As noted below, the reviewers are correct to note the sentence in the 2007 Priest paper, in which the authors stated that the toxin blocked all NaV1 isoforms . However, the Priest et al., 2007 paper represents a literature review of limited available data. Importantly, they went on to characterize this toxin in more detail, reporting in 2008, that the toxin was at least 100 time more potent against NaV1.7 than other NaV1 isoforms . Thus, in our revised manuscript, we acknowledge that our negative results with this toxin in human DRG neurons may have been due to technical problems, and the results with PF- 05089771 may still reflect a significant contribution of NaV1.7 to the TTX-S current in human DRG neurons. However, we also suggest an alternative hypothesis, which is that NaV1.7 is not the primary channel underlying TTX-S currents in human DRG neurons, where the negative results with Protoxin II and the altered pharmacological profile of PF- 05089771 reflect the impact of the native environment on the pharmacological properties of the channels present. Consistent with the suggestion that the relative contribution of NaV1.7 to TTX-S currents in rodent sensory neurons may have been over-estimated are the recent results from Deuis and colleagues (2017), who reported that a putative NaV1.7 selective spider venom peptide blocked no more than 50% of the TTX-S current in every subpopulation of sensory neurons tested . A relatively limited role for NaV1.7 in human DRG neurons would also be consistent with our observation that a low threshold ramp current is absent in human DRG neurons as well as the relatively limited impact gain of function mutations in NaV1.7 have on the excitability of human nociceptive afferents .2) Omit or address the very unexpected result that TTX increases ramp current, which also raises questions about the efficacy/specificity of drug perfusion.We agree with the reviewers that this was a very perplexing observation. Per the reviewer’s suggestion, we have omitted these data. We still describe the high threshold ramp current in these neurons, however.2+ currents in their recording solution). We used Cd2+ rather than La3+ to block Ca2+ currents in our experiments, but there is also evidence of a Cd2+-induced block of TTX-R currents in DRG neurons . Thus, it is possible that the leftward shift in the ramp current we observed was due to a TTX-induced relief of Cd2+ block. Importantly, such an explanation would support the conclusion that ramp currents in human DRG neurons are largely carried by TTX-R currents. If the reviewer’s agree that the evidence is sufficient to support this speculation, we would happily include our TTX ramp results in the manuscript, but leave this decision to the reviewers/editor.That said, we have pursued this issue further in the literature, and came across a couple of relevant studies. Most relevant is a study by Farmer and colleagues (2008), who observed a TTX-induced increase in TTX-R currents in rat DRG neurons that was associated with a leftward shift in the voltage-dependence of activation . These authors concluded that the modulation of TTX-R currents by TTX was due to the relief of a tonic block of these channels by La3+ (used to block Ca3) Clarify voltage protocols used and (a) use the information to strengthen/clarify/curtail conclusions based on pharmacology and (b) validate  the prepulse approach as opposed to a pharmacological approach to separate the currents in humans.We have provided additional details about the voltage protocols used throughout the study. We have acknowledged the possibility that the use of a voltage- protocol to isolate TTX-S and TTX-R currents introduced a source of error in the characterization of current properties, particularly for pharmacological experiments where the drugs used could have influenced the biophysical properties of the channels such that isolation of current with voltage-steps was no longer possible. We have also added further justification for our decision to rely on voltage protocols for current separation. This decision was primarily based on the facts that 1) there was a finite time- frame over which stable recordings were obtained, 2) the use of a voltage-protocol was faster than a pharmacological approach, at least with respect to the reversal of the pharmacological block of TTX-S channels, and 3) we wanted to maximize the amount of data collected from each neuron. With respect to this last point, the use of voltage protocols to isolate TTX-S and TTX-R currents enabled us to monitor both currents in each neuron.4) Test and/or clarify ambiguities arising from size differences and size-based selection to verify that differences between species weren't based on clamp artifacts from the different sizes of neurons.This is an important point. We have added a section to the revised manuscript specifically addressing this concern. We have laid out the data arguing against clamp artifacts on the biophysical parameters obtained. We have also acknowledged the limitations associated with assumptions about the phenotype of the human neurons.5) Address or omit the deactivation time constant measurements, about which specific questions were raised.DoneWe recognize that the availability of human tissue may be limited. If it is not possible or practical to address the issues directly, a (less desirable) alternative is to tone down or qualify the conclusion that Nav1.7 may not contribute much to the TTX-S current, indicating that further pharmacological work is necessary for a definitive conclusion.The reviewer’s suggestion about the use of other NaV1.7 blockers prompted us to go back into the analysis of compounds that we originally tested for Eli Lilly when we got this project up and running. We were blinded to the compounds used, but in fact had a complete data set with PF-05089771, which included the activity of this compound on TTX-R currents in human DRG neurons, an observation not previously reported.Importantly, and consistent with our original suggestion about the interpretation of the previous data with this compound on human DRG neurons, this drug does not appear to be as selective on native channels in human neurons as it was reported to be against heterologously expressed channels. We have also included additional data with protoxin II against rat TTX-S currents. Thus, while we have now acknowledged the limitations of the conclusions drawn from our pharmacological and biophysical data, we suggest that our results in the context of data available in the literature strongly support the possibility that NaV1.7 is not the dominant channel underlying TTX-S currents in human DRG neurons.[…]Detailed points for essential revisions:1) The area in which the results in the manuscript could be stronger is the most important – the conclusion that the TTX-S channels in the human neurons are not primarily carried by Nav1.7 channels. If true, this is very important, since multiple companies are developing Nav1.7 inhibitors with the assumption that these channels are critical for the function of nociceptors. Also, the conclusion that Nav1.7 do not contribute to the TTX-S currents is opposite to a previous study of human DRG neurons in which it was concluded that the majority of the TTX-S current was carried by Nav1.7 channels, based on inhibition of 75% of the current by 30 nM PF-05089771, a fairly selective blocker of Nav1.7 channels. The authors point out this previous study used neurons in culture for up to 9 days, which could cause an upregulation of Nav1.7 channels – a valid point. They also suggest that the result could have been from imperfect selectivity of PF-05089771, which while possible seems a lot less likely, since Alexandrou et al., 2016 saw big effects of 30 nM PF-05089771, which would be expected to have minimal effects on any of the other channel types.Here the authors present two pieces of evidence arguing against mediation of TTX-S by Nav1.7. One is the lack of effect of 10 nM Protoxin II. It seemed very puzzling that the authors chose protoxin II as a blocker, because a previous review of the properties of this toxin stated "ProTx-I and ProTx-II inhibit all sodium channel (Nav1) subtypes tested with similar potency." . This is certainly not clear from the presentation, where a reader would naturally infer that the toxin was used because it had selectivity for Nav1.7. The evidence against Nav1.7 would be far stronger if the authors had used PF-05089771, which is much more selective. This compound has been commercially available (from both Σ and Tocris) for some time.The reviewer raises important points. We had, in fact tested PF-05089771 on human DRG neurons and observed a complete block of TTX-S currents with 30 minutes of incubation with an IC50 of 6 nM. However, the IC50 for the block of TTX-R currents was 50 nM. Admittedly, these data support the possibility that NaV1.7 does in fact underlie the majority of TTX-S currents in human DRG neurons. However, given that heterologous expression data in the Alexandrou paper indicated that heterologously expressed NaV1.8 is insensitive to PF-05089771 at concentrations as high as 10 μM, our data with this compound at support the possibility that the TTX-S current blocked reflects more than activity in NaV1.7. Of note, Alexandrou and colleagues studied TTX-S currents in the presence of A-803467 to block NaV1.8, and therefore would not have detected an influence of PF-0589771 on TTX-R currents. These data have been added to the revised manuscript.By way of an explanation for our failure to include results with PF-05089771 in our original manuscript, these data were collected in a series of experiments in which other proprietary compounds from Eli Lilly were also tested. We had not broken the code on the compounds assessed until this question was raised (results were submitted to Lilly in the blinded manner in which they were obtained). These data have now been added to the revised manuscript.On the other hand, the choice of Pro-Tx II was based on evidence that this toxin is a potent and selective blocker of NaV1.7 as documented by Schmalhofer and colleagues , and subsequently others. The toxin is sold as an NaV1.7 selective blocker through companies such as Σ and Tocris. The Priest et al. 2007 paper referred to contains a sentence in the Abstract that is admittedly misleading, based largely on the results of a study by Middleton and colleagues (2002), in which results from variety of assay protocols were combined . The Schmalhofer paper was a follow-up to this 2007 review which contained a more careful characterization of Pro-Tx II, in which the selectivity of the toxin was clearly documented .+ influx and associated changes in gene expression than it does in the electrical properties of these neurons , while a more prominent role in transmitter release from the central terminals , may also contribute to a more limited role for this channel in the TTX-S currents detected in the afferent cell body.The negative data with Pro-Tx II combined with the considerably lower level of selectivity of PF-05089771 in human DRG neurons than that reported in heterologous expression system and the absence of low threshold ramp currents in human DRG neurons all point to the possibility that NaV1.7 may not be the dominant TTX-S channel in human DRG neurons. This suggestion is further substantiated by the relatively minor impact of NaV1.7 gain of function mutations on the excitability of human nociceptive afferents documented in microneurography studies . While the activity of the spider venom peptide Pn3a on native TTX-R currents was not well described, recent results with this putatively NaV1.7 selective blocker would also suggest that NaV1.7 does not even underlie the majority of TTX-S current in rat DRG neurons . It should also be noted that recent data from the NaV1.7 null mutant mice suggest that this subunit may, in fact play a more important role in mediating NaNevertheless, because these lines of evidence are indirect, these possibilities are only suggested in the revised manuscript.Given the efficacy of protoxin-II against all sodium channels, the lack of effect is very surprising whatever channels underlie the TTX-S current. A possible experimental problem with potent peptide toxins of this type is that they can bind to plastic tubing and glassware and be difficult to remove, so that subsequent application appears to have no effect because of presence of the agent under "control" conditions. I raise that because the lack of any effect of the toxin is unexpected whatever channels the sodium currents are coming from and because we have experienced that insidious problem several times in my own lab with similar toxins – a problem that could only be resolved by completely replacing tubing and chambers.We appreciate the reviewer’s suggestion, but tried a number of different strategies, including siliconizing glass tubes and the application of the toxin via siliconized glass pipettes. We suggest that the issue is really the concentration range over which the drug was tested. While we did use concentrations as high as 300 nM, the majority of experiments involved concentrations of 30 nM or lower. More importantly, we were able to demonstrate a block of TTX-S currents in rat DRG neurons of 50.5 ± 13.7 (n = 5)% with 10 nM toxin. Thus, while we have acknowledged that our failure to detect an effect of the toxin in human DRG neurons may reflect problems with working with the toxin, we do not think that was the primary source of the negative results obtained.2) The second piece of evidence that authors present against the contribution pf Nav1.7 channels is the most puzzling result in the paper – that TTX not only did not inhibit a current induced by ramp of voltage but actually enhanced the current and shifted its voltage dependence to more hyperpolarizing voltages. The shift of current to more hyperpolarized voltage makes no sense at all and suggests some sort of experimental problem. It would suggest that TTX enhances sodium current for small depolarizations which has never been described for any channels. At a minimum, the authors need to follow up the ramp experiment with step depolarization experiments to characterize this effect in more detail. Even if TTX simply had no effect on the ramp current, this is only weak evidence against mediation by Nav1.7. It could reflect for example faster or more complete closed-state inactivation in human Nav1.7 channels versus rodent Nav1.7 channels, which would be interesting. The authors did not compare closed-state inactivation in the human vs rat neurons so this seems like an open possibility.We completely agree with the reviewer that this was a perplexing and unexpected observation. There was no suggestion from the step depolarization data that TTX-R currents were facilitated by the presence of TTX. Nor was there evidence of a shift in the gating of TTX-R currents in the presence of TTX, as there was no significant change in either the V1/2 of activation (which changed 0.07 ± 0.04 mV after the application of TTX) or the slope of the GV curve (which changed by 0.03 ± 0.03 mV after the application of TTX). Furthermore, with a decrease in total current following application of TTX, a decrease in voltage error should have resulted in a depolarizing shift in the ramp current. We did not observe a similar shift in rat DRG neurons, suggesting that whatever the underlying mechanism, it was only detected in human neurons. Nevertheless, because we did not assess the onset of closed state inactivation, we have removed these data from the manuscript.3) It would be helpful if all the figures had clear statements of exactly what the voltage protocols were, which were not always clear to me. In We apologize for the confusion and have provided the information requested – at least for the raw traces included in each figure because the reviewer is correct, we did vary the protocol in some neurons to facilitate our ability to isolate TTX-S from TTX-R currents.Additionally, the separation of TTX-R and TTX-S components by using a conditioning voltage pulse (instead of the more laborious method of TTX block) is a key aspect of the analysis and interpretation. Deficiencies in this separation technique, which may be different for rat versus human DRG neurons, could result in apparent differences or underestimate differences. With that in mind, how was it possible to determine the availability curve for TTX-R specific currents in We apologize for failing to make this more clear. As can be seen in A great feature of the work is the comparison to studies in rat neurons done in the same lab. If these were actually done in parallel, using for example exactly the same batches of pharmacological reagents and by the same experimenter, this might be mentioned explicitly as it further strengthens the point that the differences are genuine and not the result of differences in procedures or reagents.We initiated the rat experiments toward the end of the collection of data from human DRG neurons. However, the same stocks of test agents were used in both rats and humans. We have added these details to the revised manuscript.4) A missing piece of information is exactly how the authors selected which cells to record from. From the fact that they all had TTX-R current, the experimenter presumably chose smaller-diameter cells to record from, but what exactly was the selection criterion? Do the authors think the cells all correspond to cell bodies of C-fibers? The authors have discussed the challenges of high Na current density and series resistance that often plague studies of VGSCs. Because human DRG soma are much larger than rat, the demands on clamp quality would be systematically more challenging in recordings from human than rat neurons. This might cause a systematic difference in the apparent gating behavior. The distribution of cell capacitance did, however, have a region of overlap around 50 pF. Perhaps a subset of rat and human DRG neurons with comparable size could be analyzed to provide reassurance that the observed species differences were still detectable in a population of similar-sized neurons?We thank the reviewer for raising this issue. We did, in fact start this study with a focus on small to medium diameter human DRG neurons, based on our interest in pain and the rodent data indicating an association between afferent cell body diameter and function. However, when we noticed that the vast majority of even the medium diameter neurons also contained TTX-R currents, those generally associated with nociceptors, we also started to record from larger neurons. And while we generally avoided the largest of neurons because of the higher likelihood for larger currents and consequently greater difficulty with clamp control, in the end, we sampled a relatively broad distribution of cell body sizes, relative to the total distribution observed in cut sections. We have included data from cut sections in the revised manuscript. In doing so, we were able to expand on the implications of the cell body size distribution observed as well as the distribution of TTX-S currents with respect to our understanding of the relationship between cell body size and function in the Discussion of the revised manuscript.While we have acknowledged the potential impact of clamp control problems on our characterization of current properties, we suggest errors associated with clamp control had a minimal impact on differences observed. This suggestion is based on fact that despite the more hyperpolarized voltage-dependence of activation of both TTX-R and TTX-S currents in human DRG neurons, there were only small differences in the slope of the G-V curves for the currents evoked from rat and human neurons.Finally, with respect to the suggestion that it might be possible to record from rat and human neurons of comparable size, as shown in These details have been added to the revised manuscript.5) The interpretation and discussion of VGSC deactivation was confusing  To make sure that readers are clear that "TTX-S" and "TTX-R" actually refer to currents inactivated at -40 mV and available at -40 mV,We appreciate the reviewers concern. As this terminology is widely used throughout the literature to describe these two general current types in DRG neurons, that are not only readily distinguishable based on their sensitivity to TTX, but by their biophysical properties (both steady-state and kinetic) we have largely retained the use of the terminology in the Introduction. Although we did add a clause indicating that voltage- protocols were used in the majority of experiments described in this study. To further address the reviewer’s concern, however, we have included the following sentence in the Results section after the demonstration in 2) To ensure that the prepulse subtraction procedure is kept in mind in interpreting the effects of the blockers, andWe have included this caveat in the discussion of results obtained.3) To limit or constrain claims that NaV1.7 is not the primary TTX-S current, as appropriate.We have attempted to present the data for and against this proposal as objectively as possible. The possibility that NaV1.7 may not be the primary TTX-S current is suggested as an alternative possibility. We hope we have left it to the reader to decide, acknowledging that even our attempt at a balanced consideration of the data still favors this possibility.Please also include a statement about informed consent (as appropriate) for collection of human tissue.This information was included in the original version of our manuscriptThe full comments pertaining to the requested revisions are below and have been agreed upon by all participants in the review.General assessment and major comments:The most important change in the manuscript is new data with the Pfizer Nav1.7 inhibitor PF-05089771, which the authors find inhibits the TTX-S current quite potently, with an IC50 of about 10 nM. In addition, the authors have clarified some the details of the voltage protocols and cell selection.I was very surprised that with the new data showing potent block of the TTX-S current by PF-05089771, the authors still end up concluding that Nav1.7 channels make little contribution to the TTX-S current in human DRG neurons. If it were my data, my interpretation of the overall set of the results the authors present would be the opposite, that the TTX-S current is likely to be primarily from Nav1.7 channels based on its sensitivity to PF-05089771, but that it is (interestingly) less sensitive to Protoxin-II than rat Nav1.7 channels. The observation that PF-05089771 also seems to inhibit TTX-R currents in human DRG neurons at higher concentrations is interesting and important. So, like most small molecules, the selectivity of PF-05089771 is imperfect. That is important to know, and constitutes another of the many interesting points in the manuscript about different pharmacology of the native currents in human DRG neurons compared to rat DRG neurons or heterologously-expressed human channels. However, it is still true that PF-05089771 inhibits the TTX-S current with significantly higher potency, and about what is expected from the effects on cloned human Nav1.7 channels. So my interpretation would be that the results with PF-05089771 imply that the TTX-S current is mostly from Nav1.7, but that the compound is less selective than previously realized and at higher concentrations also inhibits native human Nav1.8 channels – a very important point that adds to the significance of the results in the manuscript.We agree with the reviewer that one interpretation of our data is that NaV1.7 underlies the majority of TTX-S current in human DRG neurons. Our data with PF- 05089771 are indeed consistent with this interpretation. This is now clearly stated in the revised manuscript.However, several lines of data support an alternative possibility, which is that NaV1.7 is not the primary subunit underlying TTX-S currents. First, while PF-05089771 was an order of magnitude more potent in the block of NaV1.7 than NaV1.2 or NaV1.6 expressed in HEK293 cells, with IC50 values of 0.011 μM, 0.11 μM and 0.16 μM respectively, our data suggest this compound is less selective against channels expressed in their native environment. That is, PF-05089771 had no activity at NaV1.8 channels expressed in HEK cells at concentrations as high as 10 μM, while TTX-R currents in human DRG neurons were blocked with an IC50 of ~60 nM. A comparable loss of selectivity at other channel subtypes would not enable PF-05089771 to differentiate between NaV1.7, NaV1.2 or NaV1.6. Importantly, semiquantitative PCR analysis of NaV subunit expression levels in whole mouse DRG indicates that NaV1.2 is mRNA is the most highly expressed TTX-S subunit . RNAseq analysis of DRG neurons suggests that the number of copies of NaV1.6 (31.1) is comparable to that of NaV1.7 (54), at least in the subpopulation of neurons not in the TRPV1 lineage . Comparable results were obtained with a quantitative PCR analysis of single DRG neurons, where in those larger than 30 μm in diameter, NaV1.6 expression was comparable to that of NaV1.7 . Probably most importantly, there was only a 25% reduction in TTX-S current in DRG neurons from the NaV1.7 knock-out mouse . Second, there was no evidence of a low threshold ramp current in human DRG neurons suggesting that if NaV1.7 was the dominant subunit, it would have very different biophysical properties than the current observed in rodent sensory neurons or in heterologous expression systems . Third, there was no evidence of Protoxin II block of the TTX-S current in human DRG neurons suggesting that if NaV1.7 was the dominant subunit, it would also have very different toxin sensitivity than that of NaV1.7 expressed in heterologous expression systems  or in rodent sensory neurons . And fourth, inflammatory mediator-induced modulation of TTX-S currents was only observed in a subpopulation of neurons in which TTX-S currents were observed. While this could be explained by differences in second messenger signaling between neurons, it may also reflect a differential expression of TTX-S channel subtypes.To me, the flow of the revised manuscript now seems strange in that final set of experimental results in Results showing potent block by PF-05089771 gives the reader the impression that the TTX-S current is likely mainly Nav1.7, but then in the Discussion the first mention of this issue suggests the opposite without explaining why. The first part of the Discussion summarizing the pharmacology is very reasonable and straightforward . However, the suggestion that the contribution of NaV1.7 varies across subpopulations of human sensory neurons is also consistent with the suggestion that NaV1.7 is not the dominant, let alone only VGSC subtype in human sensory neurons." In the original version, this sentence referred to a stated conclusion in Results based on the protoxin-II results that Nav1.7 was not the dominant current. But in the revised version, there has been no explanation yet of why the authors would conclude this, and it seems to come out of nowhere.We have reworked the Discussion to address the reviewers concerns. The suggestion that NaV1.7 might not be the dominant subunit in human DRG neurons is now only raised in the context of a Discussion of the possibility that NaV1.7 may not be the dominant subunit underlying the TTX-S currents in human DRG neurons. And this possibility is only raised after a Discussion of the possibility that NaV1.7 does underlie the TTX-S current.The authors' argument about Nav1.7 comes later, in the paragraph starting "The possibility that NaV1.7 may not be the dominant subunit underlying TTX-S currents, let alone significantly contribute to these currents in human DRG neurons, as suggested by our inflammatory mediator results, was further supported by our results with Pro-Tx II and PF-05089771." This is where the authors argue that the block by PF-05089771 is not good evidence for Nav1.7 mediating the TTX-S because they find that PF-05089771 at higher concentrations also inhibits the TTX-R current. To me, the argument in this paragraph was not convincing, as it essentially argues that the lack of effect of protoxin-II is more convincing than the potent block by PF-05089771. .We appreciate the reviewers concerns and agree that this argument could and should have been made better on the one hand, and that the possibility that NaV1.7 could still be the dominant subunit made more clearly on the other. With respect to the reviewers primary concern about the selectivity of PF-05089771, we acknowledge that it is possible that the compound retained its selectivity for NaV1.7 over NaV1.2 and NaV1.6 (as well as the rest of the TTX-S subunits present in sensory neurons), while dramatically losing selectivity for NaV1.8 in human DRG neurons. However, a greater than three orders of magnitude increase in potency would at least raise the possibility that the compound loses all selectivity against human channels in their native environment.There is a reason to be cautious about interpreting the results with PF-05089771 and Protoxin-II, because both interact with their target channels in a state-dependent manner. The authors did not study the effects of the blockers on isolated currents from TTX-R or TTX-S channels, but rather used a prepulse procedure to distinguish them by inactivation. They show that this protocol works in the absence of drugs, but obviously it may not in the presence of drugs that can modify the voltage-dependence of inactivation. In my view, that should introduce a lot of caution in interpreting these results.We completely agree with the reviewer that it is important to consider the potential implications of state-dependent block. However, we disagree with the implication that the voltage protocol used to isolate TTX-R from TTX-S could account for the observation that TTX-R currents were blocked by PF-05089771. This compound blocks inactivated channels more potently that channels in a resting or closed state. The protocol used to evoke TTX-R currents should have minimized any inactivated-state block of these channels, and consequently any detectable block of these channels.Furthermore, the TTX-R currents remaining in the presence of PF-05089771 had biophysical properties comparable to the TTX-R currents recorded in the absence of the compound, with a comparable voltage-dependence of inactivation, as well as kinetics of activation and inactivation. Conversely, any contamination of TTX-R currents observed in the presence of PF-05089771 by TTX-S currents whose gating properties were somehow modified by the presence of the compound would suggest that the potency of the compound was lower in human DRG neurons than in HEK cells.In fact, in reading the paper quickly, it would be very easy for a reader to miss the important point that when the authors refer to "TTX-S" and "TTX-R" currents, this is really shorthand for "currents available from -80 but inactivated by a prepulse to -40 mv" and "currents remaining after a prepulse to -40 mV". Although the authors clearly state this in the course of Results, I think it is an important point to reiterate in the Discussion, because it is an important qualification for interpreting the pharmacological results .We completely agree with the reviewer and have reiterated this point in the Introduction, Results, and Discussion as suggested.Because of these issues, I did not find the authors' suggestion that Nav1.7 accounts for little if any of the TTX-S current convincing and it would not be my interpretation. Of course, the authors should be free to interpret their own data, but they should probably consider at least qualifying their conclusion.As noted above, we have tried to lay out the evidence both for and against the contribution of NaV1.7 to the TTX-S currents in human DRG neurons more clearly.Whatever the interpretation given, the experimental results are very interesting and leave no doubt that the detailed pharmacology of the channels in human cells is quantitatively different in interesting ways compared to the currents in rat neurons, probably most importantly in the relative lack of use-dependence with lidocaine and the apparent significant sensitivity of TTX-R channels to PF-05089771.We appreciate the supportive comments.I did not see a statement about informed consent for the collection of the human tissue, which seems important. Presumably this is the authors' 2015 paper that is cited for the Methods, but it seems that it should be here also.We agree with the reviewer that this is an important point. This information was in the first sentence of Materials and methods section of this manuscript.


Cancer is a collection of diseases that involves growing abnormal cells with the potential to invade or spread to the body. Breast cancer is the second leading cause of cancer death among women. A method for 5-year breast cancer recurrence prediction is presented in this manuscript. Clinicopathologic characteristics of 579 breast cancer patients  were analyzed and discriminative features were selected using statistical feature selection methods. They were further refined by Particle Swarm Optimization (PSO) as the inputs of the classification system with ensemble learning (Bagged Decision Tree: BDT). The proper combination of selected categorical features and also the weight (importance) of the selected interval-measurement-scale features were identified by the PSO algorithm. The performance of HPBCR (hybrid predictor of breast cancer recurrence) was assessed using the holdout and 4-fold cross-validation. Three other classifiers namely as supported vector machines, DT, and multilayer perceptron neural network were used for comparison. The selected features were diagnosis age, tumor size, lymph node involvement ratio, number of involved axillary lymph nodes, progesterone receptor expression, having hormone therapy and type of surgery. The minimum sensitivity, specificity, precision and accuracy of HPBCR were 77%, 93%, 95% and 85%, respectively in the entire cross-validation folds and the hold-out test fold. HPBCR outperformed the other tested classifiers. It showed excellent agreement with the gold standard . This algorithm is thus a promising online tool for the prediction of breast cancer recurrence. •Breast cancer is the second leading cause of cancer death among women.•Recurrence prediction could be used by clinicians to make proper treatment plan.•A hybrid prognosis tool with optimized ensemble learning is proposed in this paper.•579 breast cancer patients  were analyzed.•The average accuracy and precision were 89.2 ± 0.6% and 96.5 ± 1.0%, respectively. The purpose of CAD is to improve the diagnosis accuracy. In fact, CAD is used as a second opinion by the physicians to make the final diagnosis decision Nowadays, CAD is used in many different fields in medicine including, but not limited to, early detection of breast cancer Cancer is a collection of diseases that involves growing abnormal cells with the potential to spread to other parts of the body Cancer is the leading cause of death worldwide, accounting for 8.2 million deaths in 2012 In Iran, cancer is the third cause of death after coronary heart disease, and accidents Breast cancer, a complex heterogeneous disease, occurs with a set of different clinical symptoms. It is usually diagnosed using blood tests, MRI, mammography, and CT scan and biopsy. The pathology results from biopsy samples indicate whether the suspicious area is cancerous. Cancer patients, then, undergo a systematic treatment procedure dependent on the cancer stage and additional lab tests such as hormone receptor status Cancer staging  is in fact the process to determine the extent to which a cancer has been spread and is based on the following four characteristics: 1) the tumor size, 2) whether the cancer is invasive or non-invasive, 3) the spread of the tumor into the lymph nodes, and 4) the spread of the tumor into other parts of the body (i.e. metastasis). Stage I is an isolated cancer (tumor size ≤ 20 mm in greatest dimension) while stage IV is a metastasis cancer. Most cancer deaths are due to cancer that has spread from its primary site to other organs Breast cancer is usually treated with surgery, which may be followed by chemotherapy, radiation, and hormone therapies An important issue is whether we can optimize the treatments to increase the therapeutic efficacy. In fact, 5-year recurrence-free survival is an important treatment quality measure. In principle, it is possible to predict 5-year cancer recurrence using clinicopathologic characteristics of cancer patients The prediction systems were used for cancer diagnosis in the literature Zeng suggested a mixture classification model containing a two-layer structure called mixture of rough set and support vector machine (SVM) for breast cancer prognosis with the average accuracy of 91% The Nottingham prognostic index (NPI) is a prognostic regression model proposed by Galea et al. Kim et al. Ahmad et al. reliably and accurately predict breast cancer recurrence using pathological and demographics features of the patients. In the proposed CAD system, HPBCR (hybrid predictor of breast cancer recurrence), a hybrid technique including statistical features selection, meta-heuristic population-based optimization and ensemble learning were used to predict breast cancer recurrence in the first 5 years after the diagnosis.The discriminative prognosis predictors vary regionally in different studies The rest of the paper is organized as follows: in the next section, information about the experimental protocol and the pattern recognition methods used in this study is presented. 22.1In this study we used a 16-year registry cohort database (1998–2014) on 1085 women who diagnosed with breast cancer in Isfahan Sayed-o-Shohada cancer research center. History of clinical conditions and therapy of patients was continued until death or lost to follow up. Characteristics of variables and tumor have been recorded by interview and reported as pathology results. Time to recurrence was based on the physicians' opinion. The following information was extracted from each patient: age at diagnosis of breast cancer, lymph node involvement ratio (NR) defined as ratio of involved to dissected lymph nodes Eighty nine subjects were excluded from the analysis because of primary metastasis, a metastasis diagnosed at the time of registry The structure of HPBCR is depicted in 2.2Feature selection (FS), the process of selecting a subset of relevant features, is divided into wrapper, embedded and filter methods. Filter method selects subsets of variables as a pre-processing step, independently from the chosen classifier while the other two methods, are used during machine learning procedure In fact, Filter FS also known as Statistical FS (SFS) applies a statistical measure to assign a score to each feature Chi-square test was used to check whether a nominal-measurement-scale feature was discriminative. The discriminative features were selected and further refined as the inputs of the classification system (BDT), next discussed.2.3Decision tree builds classification models in the form of a tree structure. It divides a dataset into small subsets to incrementally develop an associated decision tree with decision and leaf nodes Decision tree has been applied to many fields; for example in prediction of breast cancer relapse after surgery Bagging is a method for improving results of machine learning classification algorithms. This method was formulated by Breiman and its name was deduced from the phrase “bootstrap aggregating”. The details of bagging could be found in The proper combination of categorical selected features and also the weight (importance) of the selected interval-measurement-scale features were identified using a meta-heuristics population-based stochastic optimization method entitled as Particle Swarm Optimization (PSO) , discuss2.4PSO is an evolutionary computational method inspired by flocking birds w is the inertia weight; c1, c2 are the cognitive and social acceleration coefficients; i is the particle number, r1 and r2 are independent random numbers whose elements are uniformly distributed in ; n denotes the iteration number, pi is the personal best of the ith particle and pg is the neighborhood best.where Each particle records its best position  so far and the best position achieved in the group (neighborhood best) among all personal bests. Then, the new position of a particle is determined based on its previous position information and its current velocity Eq. .(3)xin+1The objective is to find the particle that best maximizes the target fitness function Eq. . Moreovec1 and c2 were set to 2. A large value of inertia weight supports global search (“exploration”), while a small value favors local search (“exploitation”). A suitable strategy is to first motivate exploration, and then exploitation max = 4) was used.In HPBCR, the acceleration coefficients PSO algorithm was used to filter categorical features and to estimate the weights of interval features . In cate2.5In our study, other classification methods namely as MLP, SVM and DT were used for comparison. Such methods were proposed in similar studies in the literature MLP is a feed-forward artificial neural network model that maps sets of input data onto a set of appropriate outputs. It consists of multiple fully connected layers of nodes in which learning happens by changing connection weights through back propagation. It is a modification of the standard linear perceptron and can be used for classification of data that are not linearly separable SVM constructs a hyper plane or set of hyper planes in a high or infinite-dimensional space, which can be used for classification 2.62.6.1The performance of the classifiers was assessed using the holdout method, an approach to out-of-sample evaluation, where the dataset was split into two mutually exclusive sets (70% training and 30% test sets). The classifiers were then trained on the first set and tested on the other set +) greater than 10 or negative likelihood ratio (LR−) less than 0.1 are preferred Along with such indices, the agreement rate between the output of the classifier and the gold standard was assessed using Cohen's kappa coefficient 2.6.2McNemar's test, also known as the Gillick test, was used to compare different classifiers to identify whether one classifier statistically significantly outperforms the other or not z statistics is estimated as:To compare two classifiers A and B, x is the number of samples misclassified by A but not B and y is number of samples misclassified by B but not A. The null hypothesis (that the classifiers have the same error) can be rejected (with probability of incorrect rejection of 0.05) if | z | > 1.96 where All data processing was performed off-line using Matlab version 8.6 . All statistical analysis and calculations were performed using the SPSS statistical package, version 18.0 .2.7http://www.Prognosis.ir). A snapshot of the developed online program is shown in the Ten extracted rules were obtained from BDT whose feature weights were optimized using PSO. The prognosis system was written in C# language and used in ASP.net5 which is an open-source framework from Microsoft Corporation. The prediction model is freely available in the website  as less than 40 years and more than 40 years The value of the fitness function (F-score on the training set) and the test set performance (F-score on the test set) at some iteration were shown in The performance of the classifiers on the test set (when trained on the training set) using the hold-out validation method was shown in 44.1In our study, the following risk factors were selected by HPBCR to predict breast cancer recurrence: Age at diagnosis, TS, NR, I. Node, PR, HRT and type of surgery. Approximately 7% of women with breast cancer are diagnosed before the age of 40 years. It has been shown in the literature that younger age is not only an independent predictor of adverse outcome in survival rate TS is an independent prognostic factor, with distant recurrence rates increasing with larger tumor size NR was shown to be a prognosis factor for cancer recurrence in the literature It was shown in the literature that I. Node is an important predictive factor for recurrence risk PR expression was shown to be an independent recurrence prognostic variable in breast cancer in the literature It was shown that HRT reduces the risk of breast cancer recurrence in the literature 4.2In our study, among 1085 breast cancer patients, only 579 subjects with complete information and without primary metastasis were included in the prediction. Thus, subjects with missing data were excluded from the analysis. Missing data can introduce bias and reduce efficiency In our algorithm, SFS was first used to identify the discriminative features. Such a selection was then refined by PSO and also the importance of the interval features, represented by the estimated weights, was identified. Overall, the embedded FS was used in our study where FS is performed as part of the learning procedure. PSO is a meta-heuristics population-based stochastic optimization method. In principle, it is possible to use any other method in this category that could deal with continuous (feature weights) and discreet (feature selection) problems. We also tested genetic algorithm (GA) An alternative FS method is using multivariate FS namely as multiple logistic regression (MLR), taking into account the relationship between different features. MLR, known as feature vector machine in machine learning, can be used to select statistically significant features In HPBCR, F-score was used as the fitness function. When the dataset is imbalanced, for example in our case where the recurrence prevalence was 19.3, overall accuracy is not a suitable fitness measure. In fact, choosing the wrong objective function while developing a classification model can introduce bias towards majority The average sensitivity and specificity of HPBCR are estimated as 80% and 96% . Also, cThe performance of HPBCR was further compared with the state-of-the-art. Kim et al. NPI method proposed by Galea et al. 4.3The contribution of BDT and PSO to the overall classification performance was also considered. PSO was excluded from the algorithm flowchart and the resulting hold-out performance was reported in Moreover, SVM (Scenario 2) and MLP (Scenario 3) classifiers were used instead of BDT whose features were tuned using PSO. The performance of these two modified prognosis systems was comparable to what obtained in HPBCR .However, the performance of SVM or MLP when PSO is used for embedded feature selection  was sign4.4This study was a validation of the prognostic performance of HPBCR. The limitation of the current study is that it was a retrospective, single-institution study. The results might have been biased on the basis of available specimen and patterns of referral to the hospital. The sample size must be increased as to improve the statistical power in our prognosis system 5We proposed a computer-aided prognosis system to identify breast cancer recurrence within 5 years after diagnosis. This method is accurate and precise and could be possibly used by clinicians to make proper treatment plan.Publications relevant to cancer recurrence prediction.Supplementary material S1The input features (risk factor) used in the proposed breast cancer recurrence prediction system along with their definition and references.Supplementary material S2The pseudo code of the proposed algorithm.Supplementary material S3Statistical analysis of the validation measures.Supplementary material S4The following are the supplementary data related to this article.


The objective of this article was to compare the costs and cost-effectiveness of the two most prominent types of case management in the Netherlands (intensive case management and linkage models) against no access to case management (control group) for people with already diagnosed dementia and their informal caregivers.The economic evaluation was conducted from a societal perspective embedded within a two year prospective, observational, controlled, cohort study with 521 informal caregivers and community-dwelling persons with dementia. Case management provided within one care organization , case management where care was provided by different care organizations within one region , and a group with no access to case management (control) were compared. The economic evaluation related incremental costs to incremental effects regarding neuropsychiatric symptoms (NPI), psychological health of the informal caregiver (GHQ-12), and quality adjusted life years (QALY) of the person with dementia and informal caregiver.Inverse-propensity-score-weighted models showed no significant differences in clinical or total cost outcomes between the three groups. Informal care costs were significantly lower in the ICMM group compared to both other groups. Day center costs were significantly lower in the ICMM group compared to the control group. For all outcomes, the probability that the ICMM was cost-effective in comparison with LM and the control group was larger than 0.97 at a threshold ratio of 0 €/incremental unit of effect.This study provides preliminary evidence that the ICMM is cost-effective compared to the control group and the LM. However, the findings should be interpreted with caution since this study was not a randomized controlled trial. Dementia is a chronic disorder marked by memory loss, cognitive impairment and behavioral lapses resulting in pronounced consequences for the people with dementia, their families and society. The global prevalence of dementia is estimated at 48.1 million in 2020 and is expected to rise to approximately 90.3 million in 2040 [Although there is a variety of community and care services available for community-dwelling people with dementia and their informal caregivers, people often lack information regarding available support that may address their care needs , 5. ManyCase management has been proposed as an instrument to delay institutionalization of the person with dementia and improve the mental health of informal caregivers. Case management is defined as a “collaborative process of assessment, planning, facilitation, care coordination, evaluation, and advocacy for options and services to meet an individual’s and family’s comprehensive health needs through communication and available resources to promote quality and cost-effective outcomes”. ReviewsThe objective of this article was to compare the costs and cost-effectiveness of the two most prominent types of case management in the Netherlands (intensive case management and linkage models) against no access to case management (control group) for people with already diagnosed dementia and their informal caregivers.The COMPAS (Case management of persons with dementia and their caregivers) project was a prospective, observational, controlled, cohort study. The study protocol was registered with the Dutch Trials Registry (NTR3268) and published elsewhere , 17. ThiThe primary informal caregivers (n = 521) and persons with dementia were recruited from various regions of the Netherlands from April 2011 to November 2012. The last follow-up interview was done at the end of June 2014. Recruitment areas included rural areas in the north of Netherlands, semi-rural areas outside of Amsterdam, and urban areas such as Amsterdam. In case management regions, case managers of the participating organizations provided lists of their clients who already receiving care and met the inclusion criteria. In the control group, recruitment took place via outpatient geriatric or neurologic (memory) clinics, Alzheimer centers and general medical practices. Persons with dementia were eligible for this study if they lived at home, had an established/formal diagnosis of dementia, were not terminally-ill, were not anticipated to be admitted to a long term care facility within 6 months, and had an informal caregiver. The informal caregivers were eligible if they were the primary informal caregiver responsible for caring for the person with dementia, had sufficient language proficiency and were not severely ill.The case management models that were evaluated in this study and the content of care in regions without case management were described in detail elsewhere and summarized here , 18. AlsCase managers in the Intensive Case Management Model (ICMM) are appointed at one organization which is specialized in dementia care. They guide and support people with dementia for long periods of time usually starting after diagnosis, and offer medical and psychosocial services from within their own organization . The casThe Linkage Model (LM) is a collaboration between multiple care providers  who were already providing health care services in the region and were given the mandate to initiate case management services. After a formal diagnosis, persons with dementia are assigned to a case manager who provides educational, emotional and practical support such as advice on disease-related issues, and gives recommendations on the availability of supportive health and social services until time of nursing home admission or death of the persons with dementia. In general, informal caregivers are involved in this process whenever possible. Expert advice can be sought through multidisciplinary meetings held regularly with experts from the various collaborating organizations..In these regions, no central coordination of dementia care is provided by a dedicated, trained and educated health care professional. Care is usually initiated by the person with dementia, his /her informal caregiver or an involved health care provider. In some cases, care may be monitored by a registered nurse working in the general practice in addition to the general practitioner. Access to home or respite care did not differ across regions.The control group was recruited in areas without access to a case manager ..In thesData were collected through interviews and questionnaires administered by trained interviewers at baseline and every six months for 24 months. The informal caregiver filled in cost diaries that were collected at each interview.The primary outcome in the person with dementia was the presence of neuropsychiatric symptoms as measured with the Neuropsychiatric Inventory (NPI) which assesses twelve neuropsychiatric domains in persons with dementia . The NPIThe primary outcome in the informal caregiver was psychological or mental health as measured by the general health questionnaire (GHQ-12) . The sco5) possible health states are weighted using a valuation set from a sample of the Dutch general population known as the Dutch EQ-5D-3L tariff resulting in a utility score [Secondary outcomes included Quality-Adjusted Life-Years (QALYs) based on the EuroQol (EQ-5D-3L). EQ-5D-3ty score . This utSubsequently, combined QALY scores for the pairs were calculated by summing the QALYs for the person with dementia and the caregiver. The rationale was that case management can influence outcomes at the level of both the informal caregiver and the person with dementia, which we tried to account for by calculating a combined QALY score.Resource utilization and associated costs were measured from a societal perspective. Cost diaries were used to collect data on use of care and support by persons with dementia and the informal caregiver? to estimate costs from a societal perspective. Direct healthcare costs included formal care such as general practitioner visits and medication use. Direct non-healthcare costs consisted of time spent on care by informal carers. We limited the maximum number of informal care hours per day to 18 hours. Indirect non-healthcare costs included days absent from paid work or unable to do daily activities such as housekeeping or voluntary work because of caregiver responsibilities. To estimate the costs of case management, 73 case managers  were interviewed about their caseloads and the number of hours they worked per week. Based on this information we calculated the time spent per client including travel time, and valued this using the median hourly wage for a case manager.Costs and effects in the second year were discounted at 4% and 1.5% respectively based on Dutch guidelines for economic evaluations .As this was a non-randomized controlled study, advanced statistical methods were needed to control for any baseline imbalances between the different treatment groups . TherefoSeveral studies showed that using complete case analysis is likely to result in bias in economic evaluations –35. TherWe created 100 imputed datasets. We included the propensity weight as one of the predictor variables in the imputation model . The anaWe used a generalized linear regression model with a gamma distribution and an identity link to estimate mean differences in total costs while accounting for the right skew of the cost data. The incremental effect in quality adjusted life years (QALYs) was estimated using a using a generalized linear regression model adjusted for baseline utility scores with a Gaussian distribution and an identity link . A generWe estimated the correlation between the incremental total costs and the different outcome measures in the imputed datasets. In the multiple imputation procedure, the covariance between total costs and effect outcomes measures were calculated based on the Fisher z transformation and were then pooled using Rubin’s rules , 39.Incremental Cost-Effectiveness Ratios (ICERs) were calculated using the pooled cost and effect estimates. The ICER is calculated as ia et al .λ is the willingness to pay, and λ), x-axis). In this way, CEACs quantify the uncertainty due to sampling and measurement errors while taking into account that λ is generally unknown [λ of around 30,000 €/QALY [λ were presented as part of the cost-effectiveness outcomes.Incremental net benefit (INB) estimates were calculated using the following formula: Δ^eλ−Δ^c , 41 whernd QALYs , 41. The unknown , 41. The0 €/QALY . Therefo2 = 11 df = 1, p<0.001).Participant characteristics and differences between groups are shown in The CE plane  shows thThe ICER for LM versus control was 460,135 indicating that the loss of 1 QALY in the LM is associated with cost savings of €460,135 in comparison with control. The majority of the bootstrapped cost-effect pairs were in the Southern quadrants (0.369 in the Southeastern quadrant and 0.499 in the Southwestern quadrant) and few pairs were in the Northern quadrants (0.055 in Northeastern quadrant and 0.077 in Northwestern quadrant). The CEAC showed that the probability that the LM model was cost-effective in comparison to the control group was 0.853 at a WTP value of 0 and this slightly decreased to 0.81 at a WTP value of 30,000 €/QALY, and to 0.5 at WTP of €3.24 million per QALY.The ICER for the ICMM group versus the LM was -549,962 which indicated that there is a saving of €-549,962 per additional QALY in the ICMM as compared to the LM. The comparison between ICMM and LM showed that the cost-effect pairs were again mostly in the Southern quadrants (0.556 in southeast quadrant and 0.421 in Southwest quadrant) and a minority of pairs in the Northern quadrants (0.014 in Northeastern quadrant and 0.009 in the Northwestern quadrant). The CEAC showed that for the QALY for the person with dementia the probability that the ICMM was cost-effective in comparison to the LM model was 0.977 at a WTP value of 0 €/QALY and 0.977 at a WTP of 30,000 €/QALY.The ICER for the ICMM versus the control group was 9,495.671 indicating that the loss of one combined  QALY there would be a cost-saving of €9,495,671. Based on the CE planes the majority of the bootstrapped cost-effect pairs were in the Southern section (0.472 in Southwestern and 0.52 in Southeastern quadrant) for the comparison between ICMM compared to the control group . The CEAC showed that for combined-QALYs the probability of cost-effectiveness for ICMM versus LM was 0.977 at WTP values of 0 and 30,000 €/QALY and that this probability decreased with increasing ceiling ratios.The ICER for NPI was 26,345 indicating that a 1 point improvement on the NPI in the ICMM is associated with cost savings of €26,345 compared to the control group. For the LM versus the control group, the ICER indicated that there were savings of €78,356 per one point improvement in NPI score. For ICMM versus LM, the ICER indicates that there were savings of €7,932 per one point improvement in NPI score. For all comparisons, the CEAC was a decreasing function with increasing WTP values.The ICER for GHQ-12 was 361,012 indicating that a 1 point improvement on the GHQ-12 in the ICMM group was associated with cost-savings of €361,012 as compared to the control group. The ICER for the LM in comparison with control is 288,562 indicating that 1 point improvement on the GHQ-12 in the LM was associated with cost-savings of €288,562 as compared to the control group. For ICMM versus LM, the ICER was 640,340 indicating that 1 point decrease on the GHQ-12 in the ICMM was associated with cost-savings of €640,340 as compared to the LM. For all comparisons, the CEAC decreased as the WTP value increases.This study evaluated the cost-effectiveness of two case management models and no access to case management (control). Informal care costs were significantly lower in the ICMM than the control and LM group. Daycare costs were also significantly lower in the ICMM group than the control group. For all outcomes, the probability that the ICMM was cost-effective in comparison with LM and the control group was larger than 0.97 at a threshold ratio of 0 €/incremental unit of effect. Cost savings were accompanied by a small non-significant negative effect on quality of life for the person with dementia in both case management groups compared to the control group. Health policy makers will have to decide whether this small negative effect on QALYs is acceptable based on the generated cost savings that the ICMM model appeared to provide.In the clinical paper, the ICMM model appeared to have a positive impact on caregiver’s utility scores measured by the EQ-5D compared to the LM model but the differences could not be considered clinically relevant . HoweverA recent Cochrane review showed that case management participants used more social care services and general practitioner consultations than control group participants but used similar amounts of health care services . This reThis study has several strengths. Persons with dementia and their informal caregivers were followed over a period of 2 years. This is a relatively long period of time and provides good insight into resource utilization, quality of life, NPI scores of persons with dementia and mental health of informal caregivers. Although 36 percent of persons with dementia died during this study, we included them in our analysis and, thus, the high costs that are associated with care just before death. Another strength is that the case management models were implemented for many years previous to the start of this study. Therefore, the results have high external validity. The economic evaluation was performed from a societal perspective and also included informal care costs, thereby providing detailed insight into the economic consequences of dementia care in the community.There are also some limitations that should be considered. The observational design of the study led to baseline differences as well as possible selection bias. By using propensity scores, we tried to overcome this limitation in the analyses. There was potentially more heterogeneity in the people recruited into this study compared to a randomized control trial which may have resulted in greater uncertainty around outcomes.Another possible limitation is the use of the EQ-5D to measure quality of life, as it may not be sensitive enough to pick up relevant changes. Furthermore, the EQ 5D for the person with dementia was completed by a proxy . Approximately 263 persons with dementia also filled in EQ 5Ds themselves, but these were not used in the economic evaluations because the data was not sufficiently complete and prone to bias. Based on the paper of McPhail et al  we carefBased on this study, we are not able to identify specific components of case management that drive the cost-savings associated with case management as compared to control. Although we did publish a process analysis on the barriers and implementation of case management  and inteOur results show that the savings in informal care costs are the main contributor to societal cost savings. It is possible that the case manager is effective in helping informal caregivers to find alternatives to informal care for their loved one, although this was not reflected by our cost estimates since daycare costs increased in the ICMM group compared to the control group. However, the costs of home care were increased in the case management groups as compared to control which may indicate a shift from informal care to home care.Future research should evaluate what the case manager actually does and which components of case management are effective. Moreover, since informal care time is notoriously hard to measure, future studies should find more reliable methods to measure informal care time accurately.Another potential limitation is that we used cost diaries to measure costs. We tried to limit recall bias in the assessment of healthcare utilization rates by collecting these data prospectively. We collected the cost diaries at each follow up visit during which the diaries were checked for completeness.Moreover, because cost-effectiveness was not the primary outcome of the original study our results may be under-powered. However, it is for this reason that in economic evaluations the focus is on estimation of intervention effects instead of on hypothesis testing so that they can still provide useful information even when they are underpowered .This study provides preliminary evidence that the intensive case management model is cost-effective compared to a control group and the LM model as it appears to decrease total costs. However, further research is still needed, since this was not a randomized controlled trial. Therefore, all results should be interpreted with caution. Despite this methodological limitation, results of the study are quite robust in showing that ICMM is cost-effective as compared to LM and control.S1 Appendix(PDF)Click here for additional data file.S2 Appendix(PDF)Click here for additional data file.S1 Case Record FormInterview with informal caregiver (in Dutch).(DOC)Click here for additional data file.S2 Case Record FormInterview with the person with dementia (in Dutch).(DOC)Click here for additional data file.S3 Case Record FormQuestionnaire filled in by informal caregiver (in Dutch).(DOC)Click here for additional data file.S4 Case Record FormCost diary filled in by the informal caregiver (in Dutch).(DOC)Click here for additional data file.S1 Dataset(DTA)Click here for additional data file.S2 Dataset(DTA)Click here for additional data file.S3 Dataset(DTA)Click here for additional data file.S4 Dataset(DTA)Click here for additional data file.S5 Dataset(DTA)Click here for additional data file.S6 Dataset(DTA)Click here for additional data file.S7 Dataset(DTA)Click here for additional data file.S1 Fig(TIF)Click here for additional data file.S2 Fig(TIF)Click here for additional data file.S1 Stata Syntax(DO)Click here for additional data file.S1 TableUnit costs used for economic evaluation. All prices were adjusted for the year 2010 using consumer price index figures . Healthc(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.