Pre-lung transplant monocyte counts predict post-lung transplant survival and adverse outcomes in IPF

Pre-lung transplant monocyte counts predict post-lung transplant survival and adverse outcomes in IPF | medRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-P4HH5NV'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search Pre-lung transplant monocyte counts predict post-lung transplant survival and adverse outcomes in IPF View ORCID Profile Theodoros Karampitsakos , Muhammad Raheel Qureshi , Jalen Hammonds , Christian Arce Guzman , Rebecca Albuquerque , Bochra Tourki , Zainab Fatima , Nicole Henriquez , Valeria Calderon , Tamer Fadli , Amanda McNamara , Ishna Poojary-Hohman , Brenda M Juan-Guardela , Debabrata Bandyopadhyay , Kapil Patel , Jose D. Herazo-Maya doi: https://doi.org/10.1101/2025.05.26.25328338 Theodoros Karampitsakos 1 Department of Internal Medicine, Morsani College of Medicine, University of South Florida , Tampa, FL; Division of Pulmonary , Critical Care and Sleep Medicine, Department of Medicine, Ubben Center for Pulmonary Fibrosis Research, Morsani College of Medicine, University of South Florida , Tampa, FL, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Theodoros Karampitsakos Muhammad Raheel Qureshi 1 Department of Internal Medicine, Morsani College of Medicine, University of South Florida , Tampa, FL; Division of Pulmonary , Critical Care and Sleep Medicine, Department of Medicine, Ubben Center for Pulmonary Fibrosis Research, Morsani College of Medicine, University of South Florida , Tampa, FL, USA 2 Center for Advanced Lung Disease and Lung Transplant Program, Tampa General Hospital , Tampa, FL, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Jalen Hammonds 1 Department of Internal Medicine, Morsani College of Medicine, University of South Florida , Tampa, FL; Division of Pulmonary , Critical Care and Sleep Medicine, Department of Medicine, Ubben Center for Pulmonary Fibrosis Research, Morsani College of Medicine, University of South Florida , Tampa, FL, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Christian Arce Guzman 1 Department of Internal Medicine, Morsani College of Medicine, University of South Florida , Tampa, FL; Division of Pulmonary , Critical Care and Sleep Medicine, Department of Medicine, Ubben Center for Pulmonary Fibrosis Research, Morsani College of Medicine, University of South Florida , Tampa, FL, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Rebecca Albuquerque 1 Department of Internal Medicine, Morsani College of Medicine, University of South Florida , Tampa, FL; Division of Pulmonary , Critical Care and Sleep Medicine, Department of Medicine, Ubben Center for Pulmonary Fibrosis Research, Morsani College of Medicine, University of South Florida , Tampa, FL, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Bochra Tourki 1 Department of Internal Medicine, Morsani College of Medicine, University of South Florida , Tampa, FL; Division of Pulmonary , Critical Care and Sleep Medicine, Department of Medicine, Ubben Center for Pulmonary Fibrosis Research, Morsani College of Medicine, University of South Florida , Tampa, FL, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Zainab Fatima 1 Department of Internal Medicine, Morsani College of Medicine, University of South Florida , Tampa, FL; Division of Pulmonary , Critical Care and Sleep Medicine, Department of Medicine, Ubben Center for Pulmonary Fibrosis Research, Morsani College of Medicine, University of South Florida , Tampa, FL, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Nicole Henriquez 1 Department of Internal Medicine, Morsani College of Medicine, University of South Florida , Tampa, FL; Division of Pulmonary , Critical Care and Sleep Medicine, Department of Medicine, Ubben Center for Pulmonary Fibrosis Research, Morsani College of Medicine, University of South Florida , Tampa, FL, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Valeria Calderon 1 Department of Internal Medicine, Morsani College of Medicine, University of South Florida , Tampa, FL; Division of Pulmonary , Critical Care and Sleep Medicine, Department of Medicine, Ubben Center for Pulmonary Fibrosis Research, Morsani College of Medicine, University of South Florida , Tampa, FL, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Tamer Fadli 1 Department of Internal Medicine, Morsani College of Medicine, University of South Florida , Tampa, FL; Division of Pulmonary , Critical Care and Sleep Medicine, Department of Medicine, Ubben Center for Pulmonary Fibrosis Research, Morsani College of Medicine, University of South Florida , Tampa, FL, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Amanda McNamara 1 Department of Internal Medicine, Morsani College of Medicine, University of South Florida , Tampa, FL; Division of Pulmonary , Critical Care and Sleep Medicine, Department of Medicine, Ubben Center for Pulmonary Fibrosis Research, Morsani College of Medicine, University of South Florida , Tampa, FL, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ishna Poojary-Hohman 1 Department of Internal Medicine, Morsani College of Medicine, University of South Florida , Tampa, FL; Division of Pulmonary , Critical Care and Sleep Medicine, Department of Medicine, Ubben Center for Pulmonary Fibrosis Research, Morsani College of Medicine, University of South Florida , Tampa, FL, USA 2 Center for Advanced Lung Disease and Lung Transplant Program, Tampa General Hospital , Tampa, FL, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Brenda M Juan-Guardela 1 Department of Internal Medicine, Morsani College of Medicine, University of South Florida , Tampa, FL; Division of Pulmonary , Critical Care and Sleep Medicine, Department of Medicine, Ubben Center for Pulmonary Fibrosis Research, Morsani College of Medicine, University of South Florida , Tampa, FL, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Debabrata Bandyopadhyay 1 Department of Internal Medicine, Morsani College of Medicine, University of South Florida , Tampa, FL; Division of Pulmonary , Critical Care and Sleep Medicine, Department of Medicine, Ubben Center for Pulmonary Fibrosis Research, Morsani College of Medicine, University of South Florida , Tampa, FL, USA 2 Center for Advanced Lung Disease and Lung Transplant Program, Tampa General Hospital , Tampa, FL, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Kapil Patel 1 Department of Internal Medicine, Morsani College of Medicine, University of South Florida , Tampa, FL; Division of Pulmonary , Critical Care and Sleep Medicine, Department of Medicine, Ubben Center for Pulmonary Fibrosis Research, Morsani College of Medicine, University of South Florida , Tampa, FL, USA 2 Center for Advanced Lung Disease and Lung Transplant Program, Tampa General Hospital , Tampa, FL, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Jose D. Herazo-Maya 1 Department of Internal Medicine, Morsani College of Medicine, University of South Florida , Tampa, FL; Division of Pulmonary , Critical Care and Sleep Medicine, Department of Medicine, Ubben Center for Pulmonary Fibrosis Research, Morsani College of Medicine, University of South Florida , Tampa, FL, USA 2 Center for Advanced Lung Disease and Lung Transplant Program, Tampa General Hospital , Tampa, FL, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: jherazomaya{at}usf.edu Abstract Full Text Info/History Metrics Data/Code Preview PDF Abstract Introduction Accurate pre-lung transplant biomarkers of post-lung transplant survival are lacking in Idiopathic Pulmonary Fibrosis (IPF). Methods This was a retrospective, observational study including consecutive patients diagnosed with IPF at the University of South Florida/ Tampa General Hospital. First, we compared survival differences in patients with IPF that received lung transplant versus non- recipients, then we investigated whether pre-transplant monocyte counts could predict post- lung transplant survival, Primary Graft Dysfunction (PGD), Acute Cellular Rejection (ACR), Antibody-Mediated Rejection (AMR) and Chronic Lung Allograft Dysfunction (CLAD) using Cox Proportional Hazards (CoxPH) models adjusted to Gender, Age and Physiology index (GAP). Results A total of 201 patients with IPF were included in the analysis [lung transplant recipients: n=103, non-recipients of lung transplant: n=98]. Patients with IPF that did not undergo lung transplantation had significantly worse survival compared to patients with IPF that underwent lung transplantation [3.13 years (95% CI: 2.30 to 3.72) vs 7.05 years (95% CI: 5.41 to 8.48), HR: 2.95 (95% CI: 2.18 to 4.00), p700 K/μL had increased risk of post-lung transplant mortality [HR: 1.71 (95%CI: 1.10 to 2.65), p=0.016] or adverse outcomes defined as either PGD, ACR, AMR or CLAD, [HR: 2.05 (95% CI: 1.11 to 3.78), p=0.02] compared to patients with monocyte counts≤700 K/μL. Conclusion Lung transplantation substantially prolongs survival of patients with IPF. Incorporation of pre-lung transplant monocyte counts in the pre-transplant evaluation of patients with IPF could optimize the selection of ideal lung transplant candidates with increased probability of survival. Introduction Idiopathic Pulmonary Fibrosis (IPF) remains a chronic lung disease with dismal prognosis despite the advent of antifibrotic compounds( 1 ). The dismal prognosis of IPF and the concomitant advent of life-extending options in other chronic lung diseases, such as cystic fibrosis( 2 ), is leading to a constantly increasing proportion of adult lung transplants performed for IPF( 3 – 5 ). In fact, lung transplantation for various end-stage forms of fibrotic interstitial lung diseases has emerged as the most common indication for lung transplantation( 3 , 4 , 6 ). In the context of IPF, some reports with moderate sample size, showed that lung transplantation can improve survival, mainly through comparison of transplanted patients versus those on waiting list( 7 – 9 ). However, estimation of survival benefit in larger IPF cohorts and identification of accurate pre-transplant biomarkers of post- transplant survival in IPF represent unmet needs. With donor pool being too small to meet demand and with mortality on transplant waiting lists remaining high, accurate pre- transplant biomarkers might revolutionize the management of such patients and reduce disparities( 5 , 10 ). IPF is thought to be a lung limited disease that does not recur after lung transplantation, however, the fact that circulating, myeloid-derived monocytes and monocyte-expressed genes predict IPF mortality and disease progression, suggests that a systemic component cannot be entirely excluded in IPF( 11 – 15 ). Since the myeloid compartment remains unchanged after lung transplantation in IPF and since most immunosuppressive agents used after lung transplant do not target monocytes directly, we hypothesized that increased monocyte counts pre-lung transplant in IPF could be associated with increased mortality risk and other adverse outcomes after lung transplant and serve as a potential biomarker to identify optimal candidates for lung transplantation. Our single-center study confirmed that lung transplantation substantially prolongs survival of patients with IPF and identified a pre-lung transplant absolute monocyte count of 700 K/μL as the ideal cutoff to stratify patients with increased risk of mortality and adverse outcomes post-lung transplantation in IPF. Methods Study design and participants This was a retrospective, observational study including consecutive, patients with IPF. Patients with IPF referred to Tampa General Hospital/ University of South Florida between 8/2/2011 and 10/22/2020 were included in the analysis. Diagnosis of IPF was based on American Thoracic Society/ European Respiratory Society/ Japanese Respiratory Society/ Latin American Thoracic Association guidelines ( 16 , 17 ). Pre-lung transplant and post-lung transplant assessment Following pharmacological and non-pharmacological treatment for IPF, patients were referred for pre-transplant evaluation, typically at the time point that they were in need of 2 liters per minute supplemental oxygen at rest or if Modified Medical Research Council Dyspnea Scale was 3 or 4. Patients underwent pre-transplant assessment at Tampa General Hospital and in case of no absolute contraindication (and preferably if Body-Mass Index<32 kg/m ) received single lung or bilateral lung transplantation. When the organs were available, organ allocation was decided by a senior member of the transplant team. Routine medical management was offered to all patients during the waiting period under the supervision of a senior transplant physician. Following lung transplantation, patients were examined at regular intervals at the outpatient clinic of Tampa General Hospital and were closely monitored for unusual symptoms or functional impairment. Data collection Data for patients including time of IPF diagnosis, age, gender, forced vital capacity (FVC) %predicted, diffusing capacity of the lung for carbon monoxide (DLCO) %predicted, monocyte counts within 2 months pre-lung transplant, comorbidities, medications prescribed, post-lung transplant treatment-related adverse events, Primary Graft Dysfunction (PGD), Antibody-Mediated Rejection (AMR), Acute Cellular Rejection (ACR) or Chronic Lung Allograft Dysfunction (CLAD), time and type of lung transplantation, time of death were extracted from EPIC. Monocyte counts selected for analysis were the closest to lung transplant. Objectives The objectives of the study were: To investigate survival differences between patients with IPF that were recipients and non-recipients of lung transplant. To investigate if pre-lung transplant monocyte counts can predict post-lung transplant survival. To investigate if pre-lung transplant monocyte counts can predict post-lung transplant adverse outcomes including PGD, AMR, ACR and CLAD. Statistical analysis Summary descriptive statistics were generated with categorical data displayed as absolute numbers and relative frequencies. Continuous data were denoted as mean ± standard deviation (SD) or medians with 95% confidence interval (95% CI) based on presence or absence of normality following the Kolmogorov-Smirnov test. We investigated survival differences from the time point of IPF diagnosis between recipients and non-recipients of lung transplant. We performed both univariate analysis and multivariate Cox-regression models adjusted to IPF-Gender, Age, Physiology (GAP) score at diagnosis ( 18 ). We also performed a subgroup analysis in the recipients of lung-transplant and investigated differences in post-lung transplant survival based on the pre-lung transplant monocyte counts. In particular, we extracted monocyte counts from the complete blood count obtained within the last 2 months before lung transplantation. Receiver operating characteristic (ROC) curve was used to identify the optimal threshold of the pre-transplant monocyte counts for 5-year post-lung transplant mortality prediction. Patients were split into two groups based on that threshold. Except overall survival, we studied 5-year survival because it’s a widely used metric for the evaluation of post-lung transplant outcomes( 19 – 21 ). Survival differences were presented based on the Kaplan-Meier method. We performed both univariate analysis and multivariate Cox-regression models adjusted to pre-lung transplant GAP score( 18 ). Similarly, we investigated if patients with pre-transplant monocyte counts above this threshold had increased risk for the composite endpoint of PGD, AMR, ACR or CLAD. Ethics approval Ethical approval for this study was given by the Institutional Review Boards / Research Integrity & Compliance of University of South Florida (STUDY: 008038). Results Baseline characteristics A total of 201 patients with IPF were included in the analysis [lung transplant recipients: n=103, non-recipients of lung transplantation: n=98]. Overall, most patients were males (n=141, 70.1%) and median age at the time point of referral was 64.51 years (95% CI: 63.57 to 65.70). Baseline characteristics for recipients and non-recipients of lung transplant are presented in Table 1 . Functional indices at referral were comparable between groups. Median FVC% predicted was 61.0 (53.90 to 73.0) and 64.0 (54.0 to 69.24) in recipients and non-recipients of lung transplant, respectively (p=0.37). Median DLCO% predicted was 41.0 (34.0 to 48.0) and 38.0 (36.0 to 41.62) in patients that underwent and did not undergo lung transplantation, respectively (p=0.59). Mean GAP at the time point of diagnosis was 4.3±1.4 and 4.5±1.3 in recipients and non-recipients of lung transplant, respectively (p=0.21). View this table: View inline View popup Download powerpoint Table 1. Demographics and characteristics of patients. Lung transplantation improves survival in patients with IPF A total of 103 patients with IPF underwent lung transplantation [bilateral lung transplantation: 65/103 (63.1%), single: 38 (36.9%)]. Patients with IPF that did not undergo lung transplantation had significantly worse overall survival compared to patients with IPF that underwent lung transplantation [median survival from diagnosis: 3.13 years (95% CI: 2.30 to 3.72) vs 7.05 years (95% CI: 5.41 to 8.48), HR: 3.26 (95% CI: 2.36 to 4.50), p<0.0001], ( Figure 1A ) . Increased mortality risk for non-recipients of lung transplant was also observed following Cox regression adjusted to GAP [HR: 2.95 (95% CI: 2.18 to 4.00), p<0.0001], ( Figure 1B ) . Download figure Open in new tab Figure 1. Survival is significantly different in patients with IPF that underwent lung transplantation compared to those that did not both in the univariate analysis (Panel A) and in the Cox-regression adjusted to GAP (Panel B). Pre-lung transplant monocyte counts predict post-lung transplant survival Pre-lung transplant monocyte counts were available in EPIC for 85 patients with IPF that underwent lung transplantation (85/103, 82.5%). Mean value of pre-lung transplant monocyte counts was 776 K/μL ± 270. We performed ROC for the 5-year post-lung transplant mortality prediction based on existing literature using this metric( 19 – 21 ) and identified the value>700 K/μL as the optimal threshold of pre-lung transplant monocyte count for this endpoint. Patients with IPF and pre-lung transplant monocyte counts>700 K/μL had increased risk for 5-year post-lung transplant mortality compared to patients with monocyte counts≤700 K/μL [univariate analysis – HR: 1.91 (95%CI: 1.16 to 3.14), p=0.011, Cox regression adjusted to GAP - HR: 1.94 (95%CI: 1.15 to 3.25), p=0.012], ( Figure 2A , B) . The prognostic accuracy was reproducible in overall mortality. Patients with IPF and pre-lung transplant monocyte counts>700 K/μL had increased risk for post-lung transplant all-cause mortality [univariate analysis – HR: 1.72 (95%CI: 1.11 to 2.66), p=0.015, Cox regression adjusted to GAP - HR: 1.71 (95%CI: 1.10 to 2.65), p=0.016], ( Figure 2C , D) . Download figure Open in new tab Figure 2. Post-lung transplant 5-year survival is significantly different in patients with IPF and pre-lung transplant monocyte counts>700 K/μL compared to those with ≤ 700 K/μL both in the univariate analysis (Panel A) and in the Cox-regression adjusted to GAP (Panel B). Similarly, post-lung transplant overall survival is significantly different in patients with IPF and pre-lung transplant monocyte counts>700 K/μL compared to those with ≤ 700 K/μL both in the univariate analysis (Panel C) and in the Cox-regression adjusted to GAP (Panel D). Pre-lung transplant monocyte counts predict post-lung transplant adverse outcomes Treatment following lung transplantation is presented in Table2 . Proportions represent the percentage of patients that received this compound at any time point after lung transplantation. Most patients received corticosteroids (103/103, 100%), tacrolimus (99/103, 96.1%) and mycophenolate mofetil (95/103, 92.2%). Adverse events are presented in Table 3 , with most common being hyperglycemia (90/103, 87.4%). Data for lung transplant rejection are presented in Figure 3A . PGD occurred in 17.5% of the cohort (18/103), AMR in 10.7 % of patients (11/103), ACR in 33.0% of patients (34/103), CLAD in 35.0% of patients (36/103), while any of the aforementioned occurred in 62.1% of the patients (64/103). Importantly, the same threshold of pre-lung transplant monocyte counts that split patients into two groups with significant differences in post-lung transplant survival, split also patients into two groups with significant differences in the risk for PGD, AMR, ACR or CLAD development [Cox regression adjusted to GAP - HR: 2.05 (95% CI: 1.11 to 3.78), p=0.02, Figure 3B ]. Download figure Open in new tab Figure 3. Proportion of patients that experience PGD, AMR, ACR or CLAD (Panel A). Of note, the same threshold of pre-lung transplant monocyte counts that split patients into two groups with significant differences in post-lung transplant survival, split also patients into two groups with significant differences in the risk for PGD, AMR, ACR or CLAD development [Cox regression adjusted to GAP - HR: 2.05 (95% CI: 1.11 to 3.78), p=0.02, (Panel B)]. View this table: View inline View popup Download powerpoint Table 2. Post-lung transplant treatment. View this table: View inline View popup Table 3. Post-lung transplant treatment related adverse events. Discussion This study highlights the survival benefit that lung transplantation confers to patients with IPF and provides a potential novel biomarker for the pre-lung transplant evaluation of patients with IPF. We analyzed survival data of patients with IPF and demonstrated that recipients of lung transplant exhibited a significant survival benefit compared to non- recipients. Importantly, we identified pre-lung transplant monocyte counts as a biomarker able to predict post-lung transplant survival. Pre-lung transplant monocyte counts were also able to predict the risk for the adverse outcome composite endpoint of PGD, AMR, ACR or CLAD, implying that monocytes might have a key role in either acute or chronic transplant rejection. These findings could optimize the selection of ideal lung transplant candidates with increased probability of survival. These data also might imply that IPF is not a ‘’lung- limited’’ disease given that even after lung transplantation patients with higher monocyte counts have worse prognosis. The main attributes of this work are discussed in detail below. First, a main attribute of this work is that we present survival differences between recipients and non-recipients of lung transplant from the time point of IPF diagnosis in a relatively large cohort compared to existing literature. That was an unmet need and might unveil the ‘’true’’ benefit from lung transplantation in IPF. In particular, a previous study included 46 patients with IPF that were accepted for lung transplantation and used Cox proportional-hazards models to compare those that underwent lung transplantation with those on a waiting list ( 7 ). This analysis showed a survival benefit for the patients that underwent lung transplantation( 7 ). A more recent study with a similar approach also demonstrated survival benefit following lung transplantation and suggested that the benefit is sustained for patients with more than 65 years of age( 9 ). Despite that these data were promising, comparison of patients that underwent lung transplantation versus those on the waiting list might not be totally representative, because these groups of patients might not be really comparable due to differences in factors such as frailty and life expectancy. Similarly, comparison of survival between patients with IPF that underwent lung transplantation and a historical cohort has limitations( 22 ). Other multivariate models using lung transplantation as a time-dependent covariate, multiphase hazard models or studies analyzing various interstitial lung diseases (ILDs) have also been reported( 6 , 8 , 23 – 26 ). However, given that a randomized controlled trial between recipients and non-recipients does not seem ethical, our approach seems to be an important addition to the literature. Patients of this cohort were followed up from the time point of diagnosis, were treated using a homogeneous algorithm after the referral to our Hospital and our analysis suggested that patients with IPF that undergo lung transplantation have an overall median survival of over 7 years. Second, another very important attribute of this work is the identification of a biomarker that is tied to the pathogenesis of IPF, as a biomarker able to contribute in the pre-lung transplant evaluation of patients with IPF. Pre-lung transplant monocyte counts predicted post-lung transplant survival even after adjustment to GAP score. We tested both 5-year survival and overall survival post-lung transplant, given that 5-year post-transplant mortality is a widely used metric in post-lung transplant follow-up( 19 – 21 ). Our findings couple with previous findings for monocyte-specific genes and monocytes in stable IPF( 27 , 28 ). In particular, a 52-gene signature in peripheral blood was able to predict mortality in IPF in six independent cohorts ( 11 , 12 ). Cellular deconvolution of gene expression data showed that monocytes were the cellular source of the upregulated genes( 13 , 29 , 30 ). This fueled large- scale studies which demonstrated that increased monocyte counts were associated with increased risk of disease progression, hospitalization and mortality in IPF( 13 – 15 ). Extensive research effort suggested that monocytes do not serve only as biomarkers, but also participate in the pathogenesis of IPF( 31 – 33 ). The finding that pre-lung transplant monocyte counts predict outcomes even after lung transplant leads to an open question for a potential systemic component as a driver of lung fibrosis progression. Moreover, the findings of the current work extend the prognostic role of monocytes in the pre-lung transplant evaluation and could fuel mechanistic studies aiming to address whether monocytes have a role in lung transplant rejection. Besides, the fact that pre-lung transplant monocyte counts predicted the risk for PGD, AMR, ACR or CLAD suggests that monocytes might have a key role in transplant rejection. Currently, prognostication of post-lung transplant IPF survival is largely based on non-disease specific factors including Lung Allocation Score, comorbidities such as pulmonary hypertension, esophageal dysmotility and Body Mass Index( 6 , 25 , 34 , 35 ). While the aforementioned have a cardinal role in the pre-transplant evaluation of patients with IPF, coupling them with disease-specific biomarkers such as pre-transplant monocyte counts might revolutionize pre-transplant evaluation by optimizing the selection of ideal lung transplant candidates or by highlighting the need of meticulous evaluation is some recipients of lung transplant. With an increasing proportion of transplants being used for patients ILD, it is important to increase the awareness for the complexities related particularly to this population and shift towards a personalized management approach( 6 , 27 , 28 ). Towards this direction, other biomarkers, tied to the pathogenesis of pulmonary fibrosis, such as telomere length have been investigated as potential prognosticators of post-lung-transplant outcomes in IPF( 8 , 36 , 37 ). Despite the importance of our findings, we need to recognize some of the limitations of our study. First, this was a single-center study. While validation of the absolute monocyte count cut-off identified by us in an additional cohort would be required before using monocyte counts in the pre-transplant evaluation of IPF patients, we strongly believe that a cohort of more than 100 transplanted patients with IPF such as ours, is an adequate sample size given the existing literature for lung transplantation in IPF. Second, our study has the inherent weakness of a retrospective study. In conclusion, this was a relatively, large study compared to existing literature highlighting the survival benefit that lung transplantation confers to patients with IPF and providing a potential novel biomarker for the pre-lung transplant evaluation of patients with IPF. Lung transplantation substantially prolongs survival of patients with IPF. Incorporation of pre-lung transplant monocyte counts in the pre-transplant evaluation of patients with IPF could optimize the selection of ideal lung transplant candidates with increased probability of survival and identify patients with increased risk of adverse events post lung transplantation. Future prospective studies and larger cohorts of patients will be required before translating our findings into clinical practice. Declarations Competing interests: None to declare. Funding: This study was funded by the Ubben Family Fund (JHM). Data availability: Data are available upon request to the corresponding author. Ethics approval: Ethical approval for this study was given by the Institutional Review Boards / Research Integrity & Compliance of University of South Florida (STUDY: 008038). Authors approval: All authors approved this form of the manuscript. Data Availability Data are available upon request to the corresponding author. 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Share Pre-lung transplant monocyte counts predict post-lung transplant survival and adverse outcomes in IPF Theodoros Karampitsakos , Muhammad Raheel Qureshi , Jalen Hammonds , Christian Arce Guzman , Rebecca Albuquerque , Bochra Tourki , Zainab Fatima , Nicole Henriquez , Valeria Calderon , Tamer Fadli , Amanda McNamara , Ishna Poojary-Hohman , Brenda M Juan-Guardela , Debabrata Bandyopadhyay , Kapil Patel , Jose D. Herazo-Maya medRxiv 2025.05.26.25328338; doi: https://doi.org/10.1101/2025.05.26.25328338 Share This Article: Copy Citation Tools Pre-lung transplant monocyte counts predict post-lung transplant survival and adverse outcomes in IPF Theodoros Karampitsakos , Muhammad Raheel Qureshi , Jalen Hammonds , Christian Arce Guzman , Rebecca Albuquerque , Bochra Tourki , Zainab Fatima , Nicole Henriquez , Valeria Calderon , Tamer Fadli , Amanda McNamara , Ishna Poojary-Hohman , Brenda M Juan-Guardela , Debabrata Bandyopadhyay , Kapil Patel , Jose D. 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