The Use of Phosphodiesterase 5 Inhibitors Improves Survival in Men after Treatment for Rectal Cancer

The Use of Phosphodiesterase 5 Inhibitors Improves Survival in Men after Treatment for Rectal Cancer | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (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],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Use of Phosphodiesterase 5 Inhibitors Improves Survival in Men after Treatment for Rectal Cancer Myroslav Lutsyk, Jonathan Green, Igor Albitskiy, Gil Bar-Sela This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8123931/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Background/Objectives : Phosphodiesterase type 5 inhibitors (PDE5Is) are used to treat erectile dysfunction, as they increase blood flow to the penis during sexual stimulation, supporting erection maintenance. There is limited evidence that their use increases survival in various types of cancer. As treatment for rectal cancer often results in erectile dysfunction, many patients take PDE5Is. This study assessed the association between PDE5I use and survival in rectal cancer patients. Methods : Utilizing data from Clalit Health Services in Israel, the analysis included 1,552 patients, with 256 users of PDE5Is. Survival differences were evaluated using non-parametric tests, Cox proportional hazards models, and propensity score matching to control for confounding variables. Results : PDE5I use was found to be significantly associated with improved survival, with a hazard ratio of 0.455 (p<0.001). The survival benefit persisted after adjusting for covariates and implementing matching procedures. Conclusions : These findings suggest a potential protective effect of PDE5I use on survival in rectal cancer patients, warranting further investigation into underlying mechanisms and clinical implications. Rectal cancer phosphodiesterase type 5 inhibitors survival analysis mortality risk Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction According to the World Health Organization’s International Agency for Research on Cancer, rectal cancer is the tenth most common cause of cancer-related death and ranks eighth in terms of cancer incidence worldwide; in Europe and the USA, it ranks respectively third and fourth [ 1 ]. The survival rate for rectal cancer patients has significantly improved in recent years [ 2 ]. In Israel, the survival rate for male rectal cancer patients is approximately 70% [ 3 ]. Although the guidelines for rectal cancer treatment have changed over the years, the morbidity caused by surgery and chemoradiation remains a significant issue [ 4 , 5 ]. In addition to experiencing low anterior resection syndrome (fecal incontinence, frequency, urgency, or feelings of incomplete emptying), male patients also suffer from erectile dysfunction [ 6 – 8 ]. Over the past few decades, phosphodiesterase 5 (PDE5) inhibitors have revolutionized the treatment of erectile dysfunction, which is observed in about 52% of males between the ages of 40 and 70 [ 9 ]. PDE5 is present in various tissues and is responsible for hydrolysis of cyclic adenosine monophosphate (cAMP) and cyclic guanosine monophosphate (cGMP) [ 10 , 11 ]. PDE5 is the primary enzyme responsible for breaking down cGMP in the corpus cavernosum (erectile tissue of the penis). PDE5 inhibitors (PDE5Is) block the degradative action of PDE5, which prevents the breakdown of cGMP, prolonging the effect of cGMP, enhancing and sustaining erection in response to sexual stimulation [ 12 ]. PDE5 plays a crucial role in maintaining intracellular homeostasis and the PDE5 enzyme family is involved in inflammatory processes, immune responses, and tumor cell biology [ 13 – 16 ]. While PDE5Is were approved by the FDA decades ago for the treatment of erectile dysfunction, there is accumulating evidence of their anti-cancer/anti-tumoral activity. Colorectal tumorigenesis starts with the development of benign polyps. In vivo studies have shown that PDE5Is can reduce the rate of polyp formation by 50%. PDE5Is have been shown to induce cell cycle arrest in rectal tumor cells in vitro , ultimately leading to apoptosis. Moreover, high expression of PDE5 itself in tumors often correlates with worse prognosis [ 17 ]. In addition, PDE5Is increase the concentration of chemotherapeutic agents in tumor tissues [ 18 ]. As mentioned above, PDE5Is are widely prescribed to rectal cancer patients to manage treatment-related sexual dysfunction. This unique clinical context not only makes rectal cancer patients substantial real-world users of PDE5Is, but also presents an important opportunity to investigate whether these drugs confer additional survival benefits beyond symptomatic relief. Furthermore, since emerging preclinical and epidemiological evidence suggests that PDE5Is may have direct anti-tumor effects specific to colorectal neoplasms, including modulation of the tumor microenvironment and enhancement of immune responses, survival outcomes are particularly relevant and clinically meaningful endpoints to explore in rectal cancer patients using PDE5Is. Clalit Health Services (CHS) provides health care to over 52% of Israel’s 9.67 million citizens [ 19 ]. CHS data, managed via MDClone, integrates clinical information from community clinics, hospitals, and emergency departments, providing a comprehensive national dataset [ 20 ]. Access to this data enabled us to conduct a retrospective study to evaluate the potential correlations between the use of PDE5Is and survival improvements after completion of rectal cancer treatment. The aim of the study was to assess, in adults with rectal cancer treated within CHS, whether use of PDE5Is is associated with an overall survival advantage over patients who did not use PDE5Is during long-term follow-up, using multivariable and propensity-score–based analyses. 2. Materials and Methods 2.1.Study Sample In Israel, there are four primary healthcare providers, covering a significant portion of the Israeli population; CHS is the largest of these, in terms of insured members. CHS data, managed via MDClone, integrates clinical information from community clinics, hospitals, and emergency departments, providing a comprehensive national dataset [ 20 ]. According the National Insurance Agency, in 2024 CHS provided health care to over 52% of Israel’s 9.67 million citizens [ 19 ]. The CHS offers researchers access to a scientific platform called the "Research Room," which serves as a data source for the current study. This platform contains a comprehensive patient data, including information on ethnicity, socioeconomic status, medications purchased or prescribed, diagnoses, and treatments administered with optional anonymizing protocol. According to current regulations, all medical data have to be anonymized. The data had been pre-filtered according to predefined inclusion and exclusion criteria. The final sample was comprised of 1,552 patients, of whom 256 had purchased PDE5Is as sexual performance enhancement drugs at some point. Among participants, 83.4% (n = 1295) were Jewish, 13.6% (n = 211) were Arab, and the remaining 3.0% (n = 46) belonged to other ethnic minority groups. The patients' ages at diagnosis ranged from 26 to 95 years (mean = 65.12, SD = 12.80). 2.2.Data Collection and Processing The anonymizing level chosen for the current study required the removal of detailed descriptions, including the type and exact date of surgery, the place and date of radiotherapy, and the precise chemotherapy protocol, as well as the stage of disease at the time of diagnosis, from the database. Variables with no variation or many missing values were also removed. 2.3.Patient Selection In this retrospective study, we included individuals assigned male at birth who were diagnosed with non-metastatic rectal adenocarcinoma between January 2009 and October 2024. The treatment guidelines in Israel closely resemble those in the USA and European Community, with the recommendation of 5-FU-based chemotherapy and radiotherapy asneo-adjuvant and adjuvant therapy, according to clinical and/or pathological findings. Patients who were managed with a total neoadjuvant approach and did not undergo surgery were not enrolled due to the short follow-up time. The date of surgery was used as the initial time point for calculating PDE5I exposure time, as surgical resection is the primary curative treatment for rectal cancer. Patients were distributed into two groups: users and non-users of PDE5Is at the time of surgery. Patients who took the drug before surgery but did not continue after were combined with non-users, since we were assessing the effect of PDE5I on survival after surgery. Evaluating the impact of PDE5Is during pre-rectal cancer conditions is out of scope for the study. A study flow-diagram of cohort selection can be seen in Fig. 1 . 2.4.Ethnicity In Israel, the population consists of Jews, Arabs, and other minority ethnic groups, each with distinctive cultural and religious backgrounds that may influence healthcare practices, including the use of PDE5Is. Within the Jewish population, there are several subpopulations characterized or defined by their home languages, religious communities, and countries of origin. All these traits are stored in the database, but for this study’s purposes, they were combined under the single rubric “Jewish”. 2.5.PDE5I Use The use of PDE5Is was based on data on purchases and dosages obtained from the CHS database. Since various drugs with similar bioeffects are available on the Israeli market, the minimal effective dose of sildenafil (50 mg) was used as the “active unit” for comparing the consumption rates of similar medications in this class. 2.6.Covariates The dataset included both demographic and clinical features. Variables were either binary or categorical, with a few exceptions that were numeric in nature. Demographic variables include socio-economic status and ethnicity. Clinical covariates include diagnosis age, surgery year, PDE5I use (binary indicator based on purchase history), age of PDE5I use onset (set to 0 for non-users), Charlson Comorbidity Index (CCI) score, and individual (CCI) conditions. The AIDS indicator, which had no variance, was removed. An indicator for connective-tissue disease was also removed due to missing data in over 50% of patients. The final dataset consisted of a total of 26 covariates, a survival time variable (in years), and an event indicator (death = 1, censored = 0). 2.7.Statistical Methods 2.7.1 Non-parametric analyses Differences between users and non-users were examined with respect to demographic and clinical attributes. These were performed using non-parametric statistical tests: Chi-squared tests for the for categorical variables and Wilcoxon rank-sum tests for numeric variables for which normality could not be assumed. Normality of numeric variables within PDE5I use levels was assessed graphically using histograms and kernel density estimation (KDE) and via Shapiro-Wilks normality tests. 2.7.2.Initial Survival Analysis We began our analysis with a log-rank test comparing survival distributions between PDE5I users and non-users. Next, we fit a Cox proportional hazards (PH) model including all available covariates to assess: The variables that significantly influence survival; Whether the effect of PDE5I use remains significant after adjusting for other covariates. 2.7.3.Addressing Confounding with Propensity Score Matching To reduce the impact of potential confounding, we employed Propensity Score Matching (PSM). The covariates to be balanced were selected by extracting the most important variables using two variable selection methods: A standardized Cox PH model (with all numerical covariates set to have 0 mean and unit variance). A Random Survival Forest (RSF), using 10,000 trees, log-rank splitting criteria, and a minimum terminal node size of 10. Bootstrap sampling was used for observations, and model performance was assessed using out-of-bag (OOB) data at each RSF iteration. Variables were subsampled at each split by the default method (number of covariates divided by three). The RSF achieved a mean OOB C-index of 0.754 with SD = 0.0015. Variable importance was extracted from the RSF via the built-in variable importance measure “random”, which compares performance with splits over a specific variable with random splits over its values. For the Cox PH model, standardized coefficients were normalized to sum to one, and we selected those with the largest coefficients. We selected the top six variables from both models (accounting for a total of seven variables, due to overlap). The ordered importance of the top 6 variables/coefficients from each model can be found in the supplementary material (Table S1 ). We then used these for PSM, treating PDE5I use as the treatment indicator. We also added socioeconomic status to the PSM algorithm, as it exhibited significance in the Cox PH model. The covariates used for matching were as follows: ethnicity, age at diagnosis, recurrence (inferred from medical records), CCI score, comorbidity count, and socioeconomic status, as well as the presence of “liver disease” and “malignancy” in the CCI. We evaluated three matching ratios: 1:1, 1:2, and 1:3 and for calipers (0.05, 0.1, 0.15, and 0.2) and selected the one yielding optimal covariate balance, as evaluated by comparing mean standardized differences (for numeric variables) and differences in proportions (for categorical variables). Matching was performed using the nearest neighbor approach without replacement. The optimal balance was achieved with a 1:3 user-to-non-user ratio, with caliper value was 0.2. The final matched dataset included 253 PDE5I users (3 unmatched) and 630 non-users. All eight covariates used for matching achieved mean standardized differences < 0.1. unadjusted and adjusted balance diagnostics are displayed in Fig. 2 . To assess whether the effect of PDE5I use on survival persisted after covariate balancing, we re-ran the log-rank test on the matched dataset. 3. Additional Analyses In order to assess whether t he survival differences are consistent within subgroups of categorical variables and to examine potential interactions, we conducted stratified log-rank tests by dividing the full dataset into binary levels of ethnicity (Arab and Jewish) and disease recurrence (recurrence and no recurrence). P-values are reported for all statistical tests. Key findings are presented graphically. All analyses were conducted in R (version 4.2.3). 3. Results 3.1 Descriptive statistics of patient data The CHS database contained information on 1,552 patients diagnosed with non-metastatic rectal cancer at the time of their diagnosis. The patient characteristics are presented in Table 1 . The drug exposure mean time was 4.71years (95% CI 4.14–5.29). Our non-parametric analyses revealed significant associations between PDE5I use and ethnicity (Χ² = 19.778, 2 df, p < 0.001) and age at diagnosis (Wilcoxon rank-sum test: W = 239625, p < 0.001, effect size = 0.286). Users and non-users did not significantly differ in terms of socioeconomic status. Among the PDE5I users (n = 256), 204 (79.7%) were Jewish, while 54 (20.3%) were Arabs. This compared to 1091 Jews (84.2%), 159 Arabs (12.3%), and 46 (3.5%) belonging to some other ethnic minority, among non-PDE5I users. Users and non-users also significantly differed in terms of age at diagnosis, with users (mean = 57.42, SD = 10.63) tending to be younger than non-users (mean = 66.65, SD = 12.65). Regarding clinical attributes, we observed a significant effect for radiotherapy (RT) (Χ² = 10.6, p < 0.01), whereby 592 non-users (45.7%) received RT, compared to 146 (57%) of users. Users and non-users also differed significantly in terms of CCI scores. Non-users had a mean score of 5.11 (SD = 2.97), as opposed to 3.32 (SD = 2.42) among users (Wilcoxon rank-sum test: W = 228724, p < 0.001, effect size = 0.245). Users and non-users did not significantly differ in terms of recurrence rate or tumor location. Full statistical summaries of the comparison of patients’ demographic and clinical attributes, as well as Shapiro-Wilks normality assessments of numeric attributes, are provided in Tables 1 and 2 . Distributions of patients by age at diagnosis can be found in the supplementary material (Figure S1 ). Table 1 Summary of Analysis of Users versus Non-Users Demographic and Clinical Attributes Non-users Users Total Χ² test, (df) p-value Ethnicity Arabs 159 (84.2%) 52 (20.3%) 211 19.77, (2 df) p < 0.001 Jews 1091 (12.3%) 204 (79.7%) 1295 Other 46 (3.5%) 0 46 Socioeconomic Status High 400 (30.8%) 97 (37.9%) 497 4.849 (2 df) 0.088 Low 433 (35.8%) 77 (30.1%) 510 Mid 463 (33.4%) 82 (32.0%) 545 Age at Diagnosis Mean (SD) 66.6 (12.6) 57.4 (10.6) 65.1 (12.8) 239625 p < 0.001 Recurrence Yes 324 (25.0%) 59 (23.0%) 383 0.34, (1 df) 0.560 No 972 (75.0%) 197 (77.0%) 1169 Radiotherapy Yes 592 (45.7%) 146 (57.0%) 738 10.6, (1 df) p < 0.01 No 704 (54.3%) 110 (43.0%) 814 Tumor location Rectum 1041 (80.3%) 213 (83.2%) 1254 0.96, (1 df) 0.326 Rectosigmoid 255 (19.7%) 43 (16.8%) 298 CCI Score Mean (SD) (5.11, 2.9) (3.3, 2.4) (4.81, 2.9) 228724 p < 0.001 Surgery Year Mean (SD) 2014.97 (3.82) 2014.55 (3.85) 2014.90 (3.82) 176337 0.109 Table 2 Normality Assessments of Users’ and Non-Users’ Numeric Attributes by Shapiro-Wilk Test Group / Comparison Statistic p-value Interpretation Age – users 0.992 0.176 Normality not rejected Age – non-users 0.981 p < 0.001 Normality rejected CCI score – users 0.902 p < 0.001 Normality rejected CCI score – non-users 0.959 p < 0.001 Normality rejected Surgery year – users 0.947 p < 0.001 Normality rejected Surgery year – non-users 0.949 p < 0.001 Normality rejected 3.4 Initial Survival Analysis The initial log-rank test comparing survival between users and non-users revealed significantly better survival for users (22.66% deaths versus 53.94% among non-users). We obtained a Chi-squared test statistic value of 94.7, with p-value < 0.001. The Observed-Expected table is presented below (Table 3 A). A complete Cox PH model was fitted with all covariates. We obtained a Likelihood Ratio Test of 713.8 (32 df, n = 1552), with a p-value of < 0.001. The total number of deaths was 757. Table 3 Observed Versus Expected Deaths Among PDE5I Users and Non-Users, Whole population (A) and Post-matching analysis (B) PDE5I Use N Observed Expected Whole sample (A) Non-users 1296 699 (53.94%) 588.994 Users 256 58 (22.66%) 168.006 Post-matching analysis (B) Non-users 630 244 (38.7%) 198.478 Users 253 57 (22.5%) 102.522 Several covariates, including the use of PDE5Is, demonstrated statistically significant associations with survival. Ethnicity had a pronounced effect, with non-Jewish/Arab patients exhibiting markedly increased hazard (HR = 23.738, p < 0.001). Disease recurrence was also a strong predictor of poorer outcomes (HR = 2.94, p < 0.001). Older age at diagnosis was associated with a modest but significant increase in hazard (HR = 1.044 per year, p < 0.001), while lower socio-economic status was similarly linked to higher hazard (HR = 1.357, p < 0.01). Finally, PDE5I use was associated with a significantly reduced hazard compared to non-use (HR = 0.456, p < 0.001). Full model estimates are provided in Table 4 . 3.5 Post Matching Analysis To assess whether the effect of PDE5I use on patient survival remained significant after balancing the data concerning the most informative variables, we refit the log-rank test to the matched data. Indeed, this confirmed that PDE5I users continued to show significantly prolonged survival: χ² = 31.08973, p-value < 0.001. The Observed-Expected Table is presented below (Table 3 B). The Hazard Ratio was extracted from a Cox PH model, this time fitted post-PSM. We obtained HR = 0.361, p < 0.001. The Kaplan-Meier survival curves for pre- and post-PSM cohorts are shown in Figs. 3 and 4 . The median survival time for non-users, using the original data, was 7.3 years, whereas after balancing the data, it increased to 13.5 years. For users, the median survival time was not reached in either analysis. Table 4 Exponentiated Results of Full Cox PH model* Term Estimate S.E. Statistic p value Significance Ethnicity: Jewish 1.260 0.138 1.674 0.094 Ethnicity: Other 23.738 0.229 13.856 p < 0.001 *** Recurrence: positive 2.940 0.080 13.464 p < 0.001 *** Diagnosis Age 1.044 0.011 3.769 p < 0.001 *** Drug use onset age 1.000 0.002 0.143 0.886 Drug use: positive 0.456 0.167 -4.712 p < 0.001 *** Radio-therapy: positive 0.944 0.079 -0.734 0.463 Years of Drug Use 0.973 0.020 -1.413 0.158 Surgery Year 1.014 0.012 1.203 0.229 Socio-economic status: Low 1.357 0.099 3.095 p < 0.01 ** Socio-economic status: Mid 1.185 0.094 1.810 0.070 Tumor Location: Rectum 0.852 0.095 -1.679 0.0931 CCI Score 0.915 0.116 -0.763 0.445 Comorbidities Count 1.291 0.263 0.970 0.332 Cerebral-vascular disease: positive 0.962 0.264 -0.148 0.883 Chronic-pulmonary disease: positive 1.058 0.264 0.213 0.831 Congestive Heart Failure: positive 1.132 0.269 0.462 0.644 Dementia: positive 1.153 0.289 0.493 0.622 Diabetes Mellites: Uncomplicated 0.819 0.252 -0.792 0.428 Diabetes Mellites: End-organ Damage 1.347 0.300 0.992 0.321 Hemiplegia: positive 1.471 0.356 1.082 0.279 Leukemia: positive 0.730 0.511 -0.615 0.538 Liver disease: Mild 0.753 0.287 -0.989 0.322 Liver disease: Moderate-Severe 1.982 0.513 1.334 0.182 Lymphoma: positive 1.380 0.391 0.822 0.411 Solid Tumor: Localized 0.941 0.276 -0.222 0.824 Solid Tumor: Metastatic 2.985 0.643 1.700 0.089 Myocardial Infraction: positive 0.775 0.265 -0.963 0.335 Peptic-ulcer disease: positive 0.944 0.278 -0.206 0.837 Peripheral Vascular disease: positive 1.050 0.264 0.183 0.855 Chronic Kidney disease: positive 1.466 0.296 1.291 0.197 *The table displays the full Cox PH model. For each variable, the exponentiated coefficient, standard error, statistic and p-value are reported. The last column denotes levels of significance: * = <0.05, ** = <0.01 and *** = <0.001. Variables with significant effects include: ethnicity, recurrence, PDE5I use, age at diagnosis and socioeconomic status. 3.4 Additional Analyses All stratified log-rank tests conducted on subgroups, defined by ethnicity and disease recurrence status, showed significant differences between users and non-users, with better survival rates for PDE5I users. The results are summarized in Table 5 . Among patients with recurrence, we observed 259 events in non-users (79.9%) compared to 32 events in users (54.2%) (Chi-squared = 30.148, p < 0.001). Similarly, among patients without recurrence, the observed number of events was 440 (45.3%) for non-users and 26 (13.2%) among users (Χ² = 73.576, p < 0.001). For Jews, we identified 1091 events among non-users (54.4%) and 47 events (23%) among users (Chi-squared = 80.756, p < 0.001). Among the examined subsamples, the least significant effect was observed among Arab patients, with 59 (37.1%) and 11 (21.1%) events for non-users and users, respectively (Χ² = 4.869, p = 0.027). Table 5 Summary of Stratified Log-Rank Tests Performed for Ethnicity and Recurrence Subgroups Subgroup PDE5I Use N Observed Expected Chi-squared Statistic p-value Recurrence Non-users 324 259 (79.9%) 220.206 30.148 p < 0.001 Users 59 32 (54.2%) 70.794 No recurrence Non-users 972 440 (45.3%) 364.197 73.576 p < 0.001 Users 197 26 (13.2%) 101.802 Arabs Non-users 159 59 (37.1%) 50.787 4.869 0.027 Users 52 11 (21.1%) 19.213 Jews Non-users 1091 594 (54.4%) 501.4 80.756 p < 0.001 Users 204 47 (23%) 139.6 4. Discussion Our retrospective study used the CHS database in Israel to examine the outcomes of 1,552 patients with rectal cancer, 256 of whom had purchased PDE5Is as sexual performance enhancement drugs. Initial survival analysis indicated significantly better survival for users. The median survival time for non-users increased from 7.3 years to 13.5 years after balancing the data. Stratified log-rank tests on subgroups defined by ethnicity and recurrence status consistently showed better survival rates for users (p < 0.001), except among Arab patients, where the effect was less significant (p = 0.027). This is probably explained by the small sample size (only 14% of the patients were Arabs and of these only 20% were users), but it is also possible that differences in healthcare access, comorbidities, or cultural factors play a part. Our findings support those of several other studies into the possible anticancer effects of PDE5Is. A large Swedish nationwide observational study analyzed over 11,000 male patients with colorectal cancer, including > 1,100 PDE5I users after diagnosis [ 21 ]. It found a significantly lower risk of colorectal cancer-specific mortality (18% reduction) and reduced risk of distant metastases in PDE5I users versus non-users. The protective effect was notably stronger among patients who underwent open surgery, supporting a role for PDE5Is in counteracting surgery-induced immune suppression and improving oncologic outcomes. A retrospective, matched cohort study analyzing data from 5,545 prostate cancer patients who underwent prostatectomy found that PDE5I administration was associated with improved overall survival and reduced risk of death, suggesting routine use of PDE5I after prostatectomy may improve survival in prostate cancer patients[ 22 ]. Another population-based cohort study from Sweden focusing on gastric cancer patients showed that PDE5I use was linked to lower cancer-specific mortality particularly in early-stage cancers [ 23 ]. While direct randomized clinical trials of PDE5Is in rectal cancer are still lacking, these population-based studies coupled with preclinical evidence provide convergent support for the potential adjuvant value of PDE5Is in colorectal malignancies, including rectal cancer. Several potential mechanisms have been found for this survival benefit seen with PDE5I use. Emerging evidence indicates a duality in PDE5Is’ effects on tumorigenesis and oncoprotection in different sites and organs, as presented in a recent review [ 14 ]. Overall, the hypotheses regarding the contribution PDE5I to the survival of cancer patients can be divided into two approaches. The first is that the same mechanism that leads to improved erectile function is responsible for the positive effect on survival; increasing blood flow to the pelvis improves tissue oxygenation, reduces inflammation and improves healing after oncological surgeries and radiotherapy. This has been suggested as the cause of the anti-inflammatory effects observed in prostate tissue [ 15 ]. Increased blood flow to the tumor area also improves accessibility of anti-tumor drugs to their target, so improving the survival of those patients receiving chemotherapy [ 24 ]. Adequate oxygenation in the tumor microenvironment is a well-established factor in enhancing the cytotoxic efficacy of radiation as well as the response to cytotoxic drugs [ 25 ]. Other effects include inhibition of efflux pumps within tumor vasculature. Enhanced permeation retention (EPR) is the phenomenon whereby macromolecules, nanoparticles, or liposomes tend to accumulate more in tumor tissue than in normal tissues due to an increase in both permeability and retention. Tumors induce angiogenesis to support their rapid growth. The blood vessel walls are often defective or “leaky,” allowing large molecules and particles (like drug-loaded nanoparticles) to pass easily from the bloodstream into the tumor tissue. In addition, tumors typically have poor lymphatic drainage. Once these large particles enter the tumor, they are not efficiently removed, leading to prolonged retention. PDE5 inhibitors decrease efflux pump activity, enhancing the EPR effect, thereby increasing the concentration of the anticancer drug in tumor tissues [ 26 ]. The second approach explains the clinical findings through more direct anti-cancer effects via molecular pathways involving cGMP or other molecular mechanisms – such as PDL1 upregulation, cell cycle arrest, and induction of apoptosis [ 27 , 28 ]. One major mechanistic pathway involves immunomodulation after oncologic surgery. Preclinical and clinical data reveal that cancer surgery induces a state of immunosuppression, with a prominent expansion of myeloid-derived suppressor cells (MDSCs). These MDSCs inhibit cytotoxic T lymphocyte (CTL) and natural killer (NK) cell functions, impairing tumor clearance and promoting distant metastasis. PDE5Is such as sildenafil have been shown to block MDSC recruitment and restore CTL and NK cell activity, reducing surgery-induced immune paralysis and lowering metastasis rates. This immunomodulatory effect is supported by observations that PDE5I users experience significantly lower risks of post-operative metastasis and cancer-specific mortality [ 29 ]. PDE5Is also impact tumor cell biology at the molecular level. Zhang’s study mentioned above combined their population-based evidence with in vivo and in vitro experiments to investigate the mechanisms by which the PDE5I sildenafil suppresses gastric cancer growth [ 23 ]. They found that by inhibiting the hydrolytic activity of PDE5, sildenafil increases intracellular cGMP, which activates protein kinase G. This leads to cell cycle arrest, increased apoptosis, and degradation of oncogenic factors such as c-MYC via downstream suppression of IL-6/JAK/STAT3 signaling. Another possible mechanism for the effect on cell cycle is an increase in levels of reactive oxidative species, which in turn impairs the function of CDK and PARP proteins [ 30 ]. It is worth noting that some evidence suggests patients taking PDE5Is may have a higher risk of developing melanoma, which is linked to the activation of the RAS/RAF/ERK signaling pathway in melanoma cells [ 31 ]. However, a recent Mendelian XXXandomization analysis found little evidence to support associations between genetically proxied PDE5 inhibition and 20 cancers. They did identify a protective effect of genetically proxied PDE5 inhibition on colorectal and gastric cancer risk [ 32 ]. Preclinical studies corroborate these mechanisms in colorectal cancer models. In vitro, PDE5Is inhibit proliferation and trigger apoptosis in colorectal cancer cell lines with IC50 values within achievable pharmacologic ranges [ 33 ]. In vivo , oral PDE5Is reduce polyp formation and tumor growth by 50–60% in chemically-induced murine models through reduction of inflammation and MDSC infiltration [ 34 ]. Genetic data from The Cancer Genome Atlas (TCGA) indicates that high PDE5 expression in colorectal tumors correlates with poorer survival, underscoring PDE5 as a viable therapeutic target [ 35 ]. Together, these preclinical and translational data underscore the clinical relevance of PDE5Is’ direct molecular and immunomodulatory actions in colorectal and consequently rectal tumors. Overall, the findings of our study support the potential role of PDE5 inhibitors as adjunctive therapeutic agents in the management of rectal cancer. This option has been explored in silico with a novel, more potent PDE5 inhibitor, which had greater apoptotic effects and higher efficacy as an anti-tumor agent [ 36 ]. There is still a lack of consistent and extensive basic research to explain the clinical findings and provide a precise mechanism for the improved survival seen in cancer patients. This study has several important strengths that support the validity and clinical relevance of the findings. It utilized a large, nationally representative dataset from CHS, Israel’s largest healthcare provider, enabling robust statistical power and generalizability to diverse patient populations. The comprehensive linked data allowed detailed longitudinal follow-up and adjustment for numerous demographic, clinical, and treatment covariates, reducing confounding bias. The use of multiple advanced statistical approaches including propensity score matching and random survival forest modeling strengthens causal inference regarding the association between PDE5I use and survival outcomes, addressing potential imbalances in baseline characteristics. The study focused on rectal cancer patients, a population with high morbidity and mortality in which PDE5I use for postoperative erectile dysfunction is common. This real-world setting supports the clinical applicability of the findings. The consistent survival benefit seen across subgroups defined by ethnicity and disease recurrence status suggests a robust effect of PDE5Is in improving rectal cancer prognosis. This study has several limitations, including potential residual confounding despite the use of propensity score matching, which may not fully account for unmeasured variables influencing survival outcomes. The observational design precludes establishing causality between PDE5I use and improved survival, and there may be selection bias related to patients who purchase these medications, such as differences in health behavior or access to healthcare. One such concern is healthy user bias, where patients prescribed PDE5Is may represent a subgroup of healthier, more health-conscious men with better baseline health status and healthcare engagement. This could partially explain the survival differences observed, independent of the drug’s direct biological effects. Patients actively seeking treatment for erectile dysfunction might also have better overall postoperative recovery or adherence to oncologic follow-up and adjuvant therapies. Though our use of propensity score matching and multivariable adjustments aimed to minimize confounding, unmeasured factors such as lifestyle, frailty, and socioeconomic status may still influence the association. This selection bias is consistent with findings in other PDE5I studies, in which users generally exhibited different health-seeking behaviors than non-users. Additionally, reverse causation cannot be fully excluded, as healthier patients may be more likely to receive PDE5Is, while patients with advanced disease or comorbidities may be less likely to be prescribed these medications. Longitudinal randomized controlled trials are necessary to definitively test the causal impact of PDE5Is on rectal cancer survival and to differentiate drug effects from confounding behavioral factors. Furthermore, the data relies on medication purchase history, which does not confirm actual usage or adherence to PDE5I therapy. The heterogeneity of the patient population, particularly regarding ethnicity and comorbidities, may also affect generalizability. Lastly, anonymization necessitated the loss of important clinical data including tumor stage, type of surgery and specifics of chemotherapy/radiotherapy, which limited our ability to comprehensively adjust for all relevant prognostic factors. 5. Conclusion Here, we present evidence that the use of PDE5I is associated with improved survival outcomes in patients with rectal cancer. Initial unadjusted analyses revealed significant differences in survival distributions, favoring users, with a substantial reduction in hazard risk. To account for potential confounding factors such as ethnicity, age at diagnosis, comorbidities, and treatment variables, propensity score matching was employed, further reinforcing these findings. Post-matching analyses demonstrated that users continued to experience significantly prolonged survival, with median survival times markedly increased compared to non-users. Stratified analyses across subgroups, including ethnicity and recurrence status, consistently indicated a survival benefit associated with PDE5I use, underscoring its potential role as an adjunctive therapeutic agent in rectal cancer management. Abbreviations The following abbreviations are used in this manuscript: cAMP cyclic adenosine monophosphate cGMP cyclic guanosine monophosphate CCI Charlson Comorbidity Index CHS Clalit Health Services CTL cytotoxic T lymphocyte EPR enhanced permeation retention KDE kernel density estimation HR hazard ratio MDSC myeloid-derived suppressor cell NK natural killer OOB out-of-bag PDE5 phosphodiesterase 5 PDE5I phosphodiesterase 5 inhibitor PH proportional hazards PSM propensity score matching RSF random survival forest RT radiotherapy Declarations Supplementary Materials: The following supporting information can be downloaded at: https://www.mdpi.com/article/doi/s1, Figure S1: Age distribution at diagnosis of PDE5I users (right) and non-users (left); Table S1: Top 6 Variables/coefficients for Standardized Cox PH Model and Random Survival Forest. Author Contributions: Conceptualization, M.L. and G.B.-S.; Methodology, M.L.; Software, J.G.; Formal analysis, J.G.; Investigation, M.L.; Data curation, M.L. and I.A.; Writing – original draft, M.L.; Writing – review & editing, G.B.-S.; Supervision, G.B.-S.; Project administration, G.B.-S. All authors have read and agreed to the published version of the manuscript. Funding: This research did not receive any specific grant from funding agencies in the public, commercial, or non-profit sectors. Institutional Review Board Statement: The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board of Emek Medical Center (0121-24-EMC) and by CHS’s Committee For The Use Of Medical Data (protocol code 1658-24, approved 27/08/24). Informed Consent Statement: The need for informed consent from patients was waived by the IRB (approval 0121-24-EMC) since this was a retrospective anonymized study. Data Availability Statement: Restrictions apply to the availability of these data. Data were obtained from CHS’s Research Room platform and cannot be provided by the authors due to ethical restrictions. Conflicts of Interest: The authors declare no conflicts of interest. Acknowledgments : We want to thank Mrs. Snait Ayalon, data administration manager of Emek Medical Center, for her assistance in providing the essential data from the “Research room” and Dr. Gillian Kay for her language writing assistance. Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. 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Supplementary Files PDE5Iandrectalcancersupplementarymaterialbmc.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 26 Feb, 2026 Reviews received at journal 24 Feb, 2026 Reviewers agreed at journal 06 Feb, 2026 Reviewers agreed at journal 04 Feb, 2026 Reviews received at journal 25 Dec, 2025 Reviewers agreed at journal 14 Dec, 2025 Reviewers invited by journal 08 Dec, 2025 Editor assigned by journal 08 Dec, 2025 Editor invited by journal 03 Dec, 2025 Submission checks completed at journal 02 Dec, 2025 First submitted to journal 02 Dec, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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00:45:14","extension":"html","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":159167,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8123931/v1/c4106b61b7f7a65dd3f82fb2.html"},{"id":97932527,"identity":"0e37d792-0fd2-4616-be6d-7b6111a4afc3","added_by":"auto","created_at":"2025-12-11 00:45:14","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":98842,"visible":true,"origin":"","legend":"\u003cp\u003eStudy Flow – Cohort Selection and Exposure\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8123931/v1/828e82425960caf344904f3b.png"},{"id":98421611,"identity":"14e57d0d-3607-47fa-8c69-1027fdc559da","added_by":"auto","created_at":"2025-12-17 16:28:41","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":88948,"visible":true,"origin":"","legend":"\u003cp\u003eStandardized Mean Differences – unadjusted and adjusted using PSM with 1:3 User to Non-User Ratio and 0.2 Caliper. Standardized mean differences pre- and post-PSM, using our final PSM algorithm. The solid lines represent the 0.1 threshold. All matched standardized mean differences are below the 0.1 threshold (in absolute value).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8123931/v1/784078e1e2daf643507c5327.png"},{"id":97932531,"identity":"6d52c75f-4122-48dd-87b3-bd0388c0595c","added_by":"auto","created_at":"2025-12-11 00:45:14","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":80555,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKM Survival Estimates for PDE5I Users Versus Non-Users (unadjusted).\u003c/strong\u003e Green represents users, while blue represents non-users. The plot also displays the log-rank test p-value, which is significant given any reasonable significance level. The vertical and horizontal dashed lines in the graph represent the median survival for non-users. Median survival was not reached for PDE5I users.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8123931/v1/d42514577c737012decacaef.png"},{"id":97932543,"identity":"bcf9cc78-98ef-48a9-a723-2043ca79841c","added_by":"auto","created_at":"2025-12-11 00:45:14","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":84606,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKM Survival Estimates for PDE5I Users Versus Non-Users (adjusted with PSM). \u003c/strong\u003eGreen represents users, while blue represents non-users. The plot also displays the log-rank test p-value, which is significant given any reasonable significance level. The vertical and horizontal dashed lines in the graph represent the median survival for non-users. Median survival was not reached for PDE5I users. Although the effect was reduced after matching, a clear and significant difference remains.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8123931/v1/78a48e5b472266ec21c86c19.png"},{"id":98622408,"identity":"b1e43fbe-2f76-4ad8-af33-2f3bb8cfeed3","added_by":"auto","created_at":"2025-12-19 16:54:27","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1565480,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8123931/v1/3df99111-c996-48a3-b275-2b97ab1e1248.pdf"},{"id":98421934,"identity":"91b1bc08-1052-4730-be51-ab030d119819","added_by":"auto","created_at":"2025-12-17 16:29:57","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":100625,"visible":true,"origin":"","legend":"","description":"","filename":"PDE5Iandrectalcancersupplementarymaterialbmc.docx","url":"https://assets-eu.researchsquare.com/files/rs-8123931/v1/24e62c93e129809d62645183.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Use of Phosphodiesterase 5 Inhibitors Improves Survival in Men after Treatment for Rectal Cancer","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eAccording to the World Health Organization\u0026rsquo;s International Agency for Research on Cancer, rectal cancer is the tenth most common cause of cancer-related death and ranks eighth in terms of cancer incidence worldwide; in Europe and the USA, it ranks respectively third and fourth [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The survival rate for rectal cancer patients has significantly improved in recent years [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In Israel, the survival rate for male rectal cancer patients is approximately 70% [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Although the guidelines for rectal cancer treatment have changed over the years, the morbidity caused by surgery and chemoradiation remains a significant issue [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. In addition to experiencing low anterior resection syndrome (fecal incontinence, frequency, urgency, or feelings of incomplete emptying), male patients also suffer from erectile dysfunction [\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eOver the past few decades, phosphodiesterase 5 (PDE5) inhibitors have revolutionized the treatment of erectile dysfunction, which is observed in about 52% of males between the ages of 40 and 70 [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. PDE5 is present in various tissues and is responsible for hydrolysis of cyclic adenosine monophosphate (cAMP) and cyclic guanosine monophosphate (cGMP) [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. PDE5 is the primary enzyme responsible for breaking down cGMP in the corpus cavernosum (erectile tissue of the penis). PDE5 inhibitors (PDE5Is) block the degradative action of PDE5, which prevents the breakdown of cGMP, prolonging the effect of cGMP, enhancing and sustaining erection in response to sexual stimulation [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. PDE5 plays a crucial role in maintaining intracellular homeostasis and the PDE5 enzyme family is involved in inflammatory processes, immune responses, and tumor cell biology [\u003cspan additionalcitationids=\"CR14 CR15\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eWhile PDE5Is were approved by the FDA decades ago for the treatment of erectile dysfunction, there is accumulating evidence of their anti-cancer/anti-tumoral activity. Colorectal tumorigenesis starts with the development of benign polyps. \u003cem\u003eIn vivo\u003c/em\u003e studies have shown that PDE5Is can reduce the rate of polyp formation by 50%. PDE5Is have been shown to induce cell cycle arrest in rectal tumor cells \u003cem\u003ein vitro\u003c/em\u003e, ultimately leading to apoptosis. Moreover, high expression of PDE5 itself in tumors often correlates with worse prognosis [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. In addition, PDE5Is increase the concentration of chemotherapeutic agents in tumor tissues [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAs mentioned above, PDE5Is are widely prescribed to rectal cancer patients to manage treatment-related sexual dysfunction. This unique clinical context not only makes rectal cancer patients substantial real-world users of PDE5Is, but also presents an important opportunity to investigate whether these drugs confer additional survival benefits beyond symptomatic relief. Furthermore, since emerging preclinical and epidemiological evidence suggests that PDE5Is may have direct anti-tumor effects specific to colorectal neoplasms, including modulation of the tumor microenvironment and enhancement of immune responses, survival outcomes are particularly relevant and clinically meaningful endpoints to explore in rectal cancer patients using PDE5Is.\u003c/p\u003e\u003cp\u003eClalit Health Services (CHS) provides health care to over 52% of Israel\u0026rsquo;s 9.67\u0026nbsp;million citizens [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. CHS data, managed via MDClone, integrates clinical information from community clinics, hospitals, and emergency departments, providing a comprehensive national dataset [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Access to this data enabled us to conduct a retrospective study to evaluate the potential correlations between the use of PDE5Is and survival improvements after completion of rectal cancer treatment.\u003c/p\u003e\u003cp\u003eThe aim of the study was to assess, in adults with rectal cancer treated within CHS, whether use of PDE5Is is associated with an overall survival advantage over patients who did not use PDE5Is during long-term follow-up, using multivariable and propensity-score\u0026ndash;based analyses.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1.Study Sample\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eIn Israel, there are four primary healthcare providers, covering a significant portion of the Israeli population; CHS is the largest of these, in terms of insured members. CHS data, managed via MDClone, integrates clinical information from community clinics, hospitals, and emergency departments, providing a comprehensive national dataset [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. According the National Insurance Agency, in 2024 CHS provided health care to over 52% of Israel\u0026rsquo;s 9.67\u0026nbsp;million citizens [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. The CHS offers researchers access to a scientific platform called the \"Research Room,\" which serves as a data source for the current study. This platform contains a comprehensive patient data, including information on ethnicity, socioeconomic status, medications purchased or prescribed, diagnoses, and treatments administered with optional anonymizing protocol. According to current regulations, all medical data have to be anonymized. The data had been pre-filtered according to predefined inclusion and exclusion criteria. The final sample was comprised of 1,552 patients, of whom 256 had purchased PDE5Is as sexual performance enhancement drugs at some point. Among participants, 83.4% (n\u0026thinsp;=\u0026thinsp;1295) were Jewish, 13.6% (n\u0026thinsp;=\u0026thinsp;211) were Arab, and the remaining 3.0% (n\u0026thinsp;=\u0026thinsp;46) belonged to other ethnic minority groups. The patients' ages at diagnosis ranged from 26 to 95 years (mean\u0026thinsp;=\u0026thinsp;65.12, SD\u0026thinsp;=\u0026thinsp;12.80).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2.Data Collection and Processing\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe anonymizing level chosen for the current study required the removal of detailed descriptions, including the type and exact date of surgery, the place and date of radiotherapy, and the precise chemotherapy protocol, as well as the stage of disease at the time of diagnosis, from the database. Variables with no variation or many missing values were also removed.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3.Patient Selection\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eIn this retrospective study, we included individuals assigned male at birth who were diagnosed with non-metastatic rectal adenocarcinoma between January 2009 and October 2024. The treatment guidelines in Israel closely resemble those in the USA and European Community, with the recommendation of 5-FU-based chemotherapy and radiotherapy asneo-adjuvant and adjuvant therapy, according to clinical and/or pathological findings. Patients who were managed with a total neoadjuvant approach and did not undergo surgery were not enrolled due to the short follow-up time. The date of surgery was used as the initial time point for calculating PDE5I exposure time, as surgical resection is the primary curative treatment for rectal cancer.\u003c/p\u003e\u003cp\u003ePatients were distributed into two groups: users and non-users of PDE5Is at the time of surgery. Patients who took the drug before surgery but did not continue after were combined with non-users, since we were assessing the effect of PDE5I on survival after surgery. Evaluating the impact of PDE5Is during pre-rectal cancer conditions is out of scope for the study. A study flow-diagram of cohort selection can be seen in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4.Ethnicity\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eIn Israel, the population consists of Jews, Arabs, and other minority ethnic groups, each with distinctive cultural and religious backgrounds that may influence healthcare practices, including the use of PDE5Is. Within the Jewish population, there are several subpopulations characterized or defined by their home languages, religious communities, and countries of origin. All these traits are stored in the database, but for this study\u0026rsquo;s purposes, they were combined under the single rubric \u0026ldquo;Jewish\u0026rdquo;.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5.PDE5I Use\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe use of PDE5Is was based on data on purchases and dosages obtained from the CHS database. Since various drugs with similar bioeffects are available on the Israeli market, the minimal effective dose of sildenafil (50 mg) was used as the \u0026ldquo;active unit\u0026rdquo; for comparing the consumption rates of similar medications in this class.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.6.Covariates\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe dataset included both demographic and clinical features. Variables were either binary or categorical, with a few exceptions that were numeric in nature. Demographic variables include socio-economic status and ethnicity. Clinical covariates include diagnosis age, surgery year, PDE5I use (binary indicator based on purchase history), age of PDE5I use onset (set to 0 for non-users), Charlson Comorbidity Index (CCI) score, and individual (CCI) conditions. The AIDS indicator, which had no variance, was removed. An indicator for connective-tissue disease was also removed due to missing data in over 50% of patients. The final dataset consisted of a total of 26 covariates, a survival time variable (in years), and an event indicator (death\u0026thinsp;=\u0026thinsp;1, censored\u0026thinsp;=\u0026thinsp;0).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e2.7.Statistical Methods\u003c/h2\u003e\u003cdiv id=\"Sec10\" class=\"Section3\"\u003e\u003ch2\u003e2.7.1 Non-parametric analyses\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eDifferences between users and non-users were examined with respect to demographic and clinical attributes. These were performed using non-parametric statistical tests: Chi-squared tests for the for categorical variables and Wilcoxon rank-sum tests for numeric variables for which normality could not be assumed. Normality of numeric variables within PDE5I use levels was assessed graphically using histograms and kernel density estimation (KDE) and via Shapiro-Wilks normality tests.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section3\"\u003e\u003ch2\u003e2.7.2.Initial Survival Analysis\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eWe began our analysis with a log-rank test comparing survival distributions between PDE5I users and non-users. Next, we fit a Cox proportional hazards (PH) model including all available covariates to assess:\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eThe variables that significantly influence survival;\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eWhether the effect of PDE5I use remains significant after adjusting for other covariates.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section3\"\u003e\u003ch2\u003e2.7.3.Addressing Confounding with Propensity Score Matching\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eTo reduce the impact of potential confounding, we employed Propensity Score Matching (PSM). The covariates to be balanced were selected by extracting the most important variables using two variable selection methods:\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eA standardized Cox PH model (with all numerical covariates set to have 0 mean and unit variance).\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eA Random Survival Forest (RSF), using 10,000 trees, log-rank splitting criteria, and a minimum terminal node size of 10. Bootstrap sampling was used for observations, and model performance was assessed using out-of-bag (OOB) data at each RSF iteration. Variables were subsampled at each split by the default method (number of covariates divided by three). The RSF achieved a mean OOB C-index of 0.754 with SD\u0026thinsp;=\u0026thinsp;0.0015.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eVariable importance was extracted from the RSF via the built-in variable importance measure \u0026ldquo;random\u0026rdquo;, which compares performance with splits over a specific variable with random splits over its values. For the Cox PH model, standardized coefficients were normalized to sum to one, and we selected those with the largest coefficients.\u003c/p\u003e\u003cp\u003eWe selected the top six variables from both models (accounting for a total of seven variables, due to overlap). The ordered importance of the top 6 variables/coefficients from each model can be found in the supplementary material (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). We then used these for PSM, treating PDE5I use as the treatment indicator. We also added socioeconomic status to the PSM algorithm, as it exhibited significance in the Cox PH model. The covariates used for matching were as follows: ethnicity, age at diagnosis, recurrence (inferred from medical records), CCI score, comorbidity count, and socioeconomic status, as well as the presence of \u0026ldquo;liver disease\u0026rdquo; and \u0026ldquo;malignancy\u0026rdquo; in the CCI.\u003c/p\u003e\u003cp\u003eWe evaluated three matching ratios: 1:1, 1:2, and 1:3 and for calipers (0.05, 0.1, 0.15, and 0.2) and selected the one yielding optimal covariate balance, as evaluated by comparing mean standardized differences (for numeric variables) and differences in proportions (for categorical variables). Matching was performed using the nearest neighbor approach without replacement. The optimal balance was achieved with a 1:3 user-to-non-user ratio, with caliper value was 0.2.\u003c/p\u003e\u003cp\u003eThe final matched dataset included 253 PDE5I users (3 unmatched) and 630 non-users. All eight covariates used for matching achieved mean standardized differences\u0026thinsp;\u0026lt;\u0026thinsp;0.1. unadjusted and adjusted balance diagnostics are displayed in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eTo assess whether the effect of PDE5I use on survival persisted after covariate balancing, we re-ran the log-rank test on the matched dataset.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\n\u003ch3\u003e3. Additional Analyses\u003c/h3\u003e\n\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eIn order to assess whether \u003cb\u003et\u003c/b\u003ehe survival differences are consistent within subgroups of categorical variables and to examine potential interactions, we conducted stratified log-rank tests by dividing the full dataset into binary levels of ethnicity (Arab and Jewish) and disease recurrence (recurrence and no recurrence).\u003c/p\u003e\u003cp\u003eP-values are reported for all statistical tests. Key findings are presented graphically. All analyses were conducted in R (version 4.2.3).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Descriptive statistics of patient data\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe CHS database contained information on 1,552 patients diagnosed with non-metastatic rectal cancer at the time of their diagnosis. The patient characteristics are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The drug exposure mean time was 4.71years (95% CI 4.14\u0026ndash;5.29).\u003c/p\u003e\u003cp\u003eOur non-parametric analyses revealed significant associations between PDE5I use and ethnicity (Χ\u0026sup2; = 19.778, 2 df, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and age at diagnosis (Wilcoxon rank-sum test: W\u0026thinsp;=\u0026thinsp;239625, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, effect size\u0026thinsp;=\u0026thinsp;0.286). Users and non-users did not significantly differ in terms of socioeconomic status. Among the PDE5I users (n\u0026thinsp;=\u0026thinsp;256), 204 (79.7%) were Jewish, while 54 (20.3%) were Arabs. This compared to 1091 Jews (84.2%), 159 Arabs (12.3%), and 46 (3.5%) belonging to some other ethnic minority, among non-PDE5I users. Users and non-users also significantly differed in terms of age at diagnosis, with users (mean\u0026thinsp;=\u0026thinsp;57.42, SD\u0026thinsp;=\u0026thinsp;10.63) tending to be younger than non-users (mean\u0026thinsp;=\u0026thinsp;66.65, SD\u0026thinsp;=\u0026thinsp;12.65).\u003c/p\u003e\u003cp\u003eRegarding clinical attributes, we observed a significant effect for radiotherapy (RT) (Χ\u0026sup2; = 10.6, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), whereby 592 non-users (45.7%) received RT, compared to 146 (57%) of users. Users and non-users also differed significantly in terms of CCI scores. Non-users had a mean score of 5.11 (SD\u0026thinsp;=\u0026thinsp;2.97), as opposed to 3.32 (SD\u0026thinsp;=\u0026thinsp;2.42) among users (Wilcoxon rank-sum test: W\u0026thinsp;=\u0026thinsp;228724, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, effect size\u0026thinsp;=\u0026thinsp;0.245). Users and non-users did not significantly differ in terms of recurrence rate or tumor location. Full statistical summaries of the comparison of patients\u0026rsquo; demographic and clinical attributes, as well as Shapiro-Wilks normality assessments of numeric attributes, are provided in Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Distributions of patients by age at diagnosis can be found in the supplementary material (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSummary of Analysis of Users versus Non-Users Demographic and Clinical Attributes\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNon-users\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUsers\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eΧ\u0026sup2; test, (df)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eEthnicity\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eArabs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e159 (84.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e52 (20.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e211\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e19.77, (2 df)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eJews\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1091 (12.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e204 (79.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1295\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOther\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e46 (3.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e46\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eSocioeconomic Status\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e400 (30.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e97 (37.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e497\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e4.849 (2 df)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.088\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLow\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e433 (35.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e77 (30.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e510\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e463 (33.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e82 (32.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e545\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge at Diagnosis\u003c/b\u003e Mean (SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e66.6 (12.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e57.4 (10.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e65.1 (12.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e239625\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eRecurrence\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e324 (25.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e59 (23.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e383\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.34, (1 df)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.560\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e972 (75.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e197 (77.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1169\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eRadiotherapy\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e592 (45.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e146 (57.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e738\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e10.6, (1 df)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e704 (54.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e110 (43.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e814\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eTumor location\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRectum\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1041 (80.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e213 (83.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1254\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.96, (1 df)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.326\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRectosigmoid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e255 (19.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e43 (16.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e298\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCCI Score\u003c/b\u003e Mean (SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(5.11, 2.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(3.3, 2.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(4.81, 2.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e228724\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSurgery Year\u003c/b\u003e Mean (SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2014.97 (3.82)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2014.55 (3.85)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2014.90 (3.82)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e176337\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.109\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eNormality Assessments of Users\u0026rsquo; and Non-Users\u0026rsquo; Numeric Attributes by Shapiro-Wilk Test\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGroup / Comparison\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStatistic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eInterpretation\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge \u0026ndash; users\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.992\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.176\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNormality not rejected\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge \u0026ndash; non-users\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.981\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNormality rejected\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCCI score \u0026ndash; users\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.902\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNormality rejected\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCCI score \u0026ndash; non-users\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.959\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNormality rejected\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSurgery year \u0026ndash; users\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.947\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNormality rejected\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSurgery year \u0026ndash; non-users\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.949\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNormality rejected\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e3.4 Initial Survival Analysis\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe initial log-rank test comparing survival between users and non-users revealed significantly better survival for users (22.66% deaths versus 53.94% among non-users). We obtained a Chi-squared test statistic value of 94.7, with p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.001. The Observed-Expected table is presented below (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). A complete Cox PH model was fitted with all covariates. We obtained a Likelihood Ratio Test of 713.8 (32 df, n\u0026thinsp;=\u0026thinsp;1552), with a p-value of \u0026lt;\u0026thinsp;0.001. The total number of deaths was 757.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eObserved Versus Expected Deaths Among PDE5I Users and Non-Users, Whole population (A) and Post-matching analysis (B)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePDE5I Use\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eObserved\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eExpected\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cem\u003eWhole sample\u003c/em\u003e \u003cb\u003e(A)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNon-users\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1296\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e699 (53.94%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e588.994\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUsers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e256\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e58 (22.66%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e168.006\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cem\u003ePost-matching analysis\u003c/em\u003e \u003cb\u003e(B)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNon-users\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e630\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e244 (38.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e198.478\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUsers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e253\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e57 (22.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e102.522\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eSeveral covariates, including the use of PDE5Is, demonstrated statistically significant associations with survival. Ethnicity had a pronounced effect, with non-Jewish/Arab patients exhibiting markedly increased hazard (HR\u0026thinsp;=\u0026thinsp;23.738, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Disease recurrence was also a strong predictor of poorer outcomes (HR\u0026thinsp;=\u0026thinsp;2.94, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Older age at diagnosis was associated with a modest but significant increase in hazard (HR\u0026thinsp;=\u0026thinsp;1.044 per year, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), while lower socio-economic status was similarly linked to higher hazard (HR\u0026thinsp;=\u0026thinsp;1.357, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Finally, PDE5I use was associated with a significantly reduced hazard compared to non-use (HR\u0026thinsp;=\u0026thinsp;0.456, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Full model estimates are provided in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003e3.5 Post Matching Analysis\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eTo assess whether the effect of PDE5I use on patient survival remained significant after balancing the data concerning the most informative variables, we refit the log-rank test to the matched data. Indeed, this confirmed that PDE5I users continued to show significantly prolonged survival: χ\u0026sup2; = 31.08973, p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.001. The Observed-Expected Table is presented below (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). The Hazard Ratio was extracted from a Cox PH model, this time fitted post-PSM. We obtained HR\u0026thinsp;=\u0026thinsp;0.361, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001. The Kaplan-Meier survival curves for pre- and post-PSM cohorts are shown in Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. The median survival time for non-users, using the original data, was 7.3 years, whereas after balancing the data, it increased to 13.5 years. For users, the median survival time was not reached in either analysis.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eExponentiated Results of Full Cox PH model*\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTerm\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEstimate\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eS.E.\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eStatistic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eSignificance\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEthnicity: Jewish\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.260\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.138\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.674\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.094\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEthnicity: Other\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e23.738\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.229\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13.856\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRecurrence: positive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.940\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.080\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13.464\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiagnosis Age\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.044\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.011\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.769\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDrug use onset age\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.143\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.886\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDrug use: positive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.456\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.167\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-4.712\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRadio-therapy: positive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.944\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.079\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.734\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.463\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYears of Drug Use\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.973\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-1.413\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.158\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSurgery Year\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.014\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.203\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.229\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSocio-economic status: Low\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.357\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.099\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.095\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSocio-economic status: Mid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.185\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.094\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.810\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.070\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTumor Location: Rectum\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.852\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.095\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-1.679\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0931\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCCI Score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.915\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.116\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.763\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.445\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eComorbidities Count\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.291\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.263\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.970\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.332\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCerebral-vascular disease: positive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.962\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.264\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.148\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.883\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChronic-pulmonary disease: positive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.058\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.264\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.213\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.831\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCongestive Heart Failure: positive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.132\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.269\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.462\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.644\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDementia: positive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.153\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.289\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.493\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.622\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiabetes Mellites: Uncomplicated\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.819\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.252\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.792\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.428\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiabetes Mellites: End-organ Damage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.347\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.300\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.992\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.321\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHemiplegia: positive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.471\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.356\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.082\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.279\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLeukemia: positive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.730\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.511\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.615\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.538\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLiver disease: Mild\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.753\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.287\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.989\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.322\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLiver disease: Moderate-Severe\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.982\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.513\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.334\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.182\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLymphoma: positive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.380\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.391\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.822\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.411\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSolid Tumor: Localized\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.941\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.276\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.222\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.824\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSolid Tumor: Metastatic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.985\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.643\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.700\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.089\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMyocardial Infraction: positive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.775\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.265\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.963\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.335\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePeptic-ulcer disease: positive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.944\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.278\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.206\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.837\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePeripheral Vascular disease: positive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.050\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.264\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.183\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.855\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChronic Kidney disease: positive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.466\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.296\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.291\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.197\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e*The table displays the full Cox PH model. For each variable, the exponentiated coefficient, standard error, statistic and p-value are reported. The last column denotes levels of significance: * = \u0026lt;0.05, ** = \u0026lt;0.01 and *** = \u0026lt;0.001. Variables with significant effects include: ethnicity, recurrence, PDE5I use, age at diagnosis and socioeconomic status.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003e3.4 Additional Analyses\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eAll stratified log-rank tests conducted on subgroups, defined by ethnicity and disease recurrence status, showed significant differences between users and non-users, with better survival rates for PDE5I users. The results are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. Among patients with recurrence, we observed 259 events in non-users (79.9%) compared to 32 events in users (54.2%) (Chi-squared\u0026thinsp;=\u0026thinsp;30.148, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Similarly, among patients without recurrence, the observed number of events was 440 (45.3%) for non-users and 26 (13.2%) among users (Χ\u0026sup2; = 73.576, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). For Jews, we identified 1091 events among non-users (54.4%) and 47 events (23%) among users (Chi-squared\u0026thinsp;=\u0026thinsp;80.756, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Among the examined subsamples, the least significant effect was observed among Arab patients, with 59 (37.1%) and 11 (21.1%) events for non-users and users, respectively (Χ\u0026sup2; = 4.869, p\u0026thinsp;=\u0026thinsp;0.027).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSummary of Stratified Log-Rank Tests Performed for Ethnicity and Recurrence Subgroups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSubgroup\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePDE5I Use\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eObserved\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eExpected\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eChi-squared Statistic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eRecurrence\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNon-users\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e324\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e259 (79.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e220.206\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e30.148\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUsers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e32 (54.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e70.794\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eNo recurrence\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNon-users\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e972\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e440 (45.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e364.197\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e73.576\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUsers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e197\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e26 (13.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e101.802\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eArabs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNon-users\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e159\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e59 (37.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e50.787\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e4.869\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.027\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUsers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11 (21.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e19.213\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eJews\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNon-users\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1091\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e594 (54.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e501.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e80.756\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUsers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e204\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e47 (23%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e139.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eOur retrospective study used the CHS database in Israel to examine the outcomes of 1,552 patients with rectal cancer, 256 of whom had purchased PDE5Is as sexual performance enhancement drugs. Initial survival analysis indicated significantly better survival for users. The median survival time for non-users increased from 7.3 years to 13.5 years after balancing the data. Stratified log-rank tests on subgroups defined by ethnicity and recurrence status consistently showed better survival rates for users (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), except among Arab patients, where the effect was less significant (p\u0026thinsp;=\u0026thinsp;0.027). This is probably explained by the small sample size (only 14% of the patients were Arabs and of these only 20% were users), but it is also possible that differences in healthcare access, comorbidities, or cultural factors play a part.\u003c/p\u003e\u003cp\u003eOur findings support those of several other studies into the possible anticancer effects of PDE5Is. A large Swedish nationwide observational study analyzed over 11,000 male patients with colorectal cancer, including\u0026thinsp;\u0026gt;\u0026thinsp;1,100 PDE5I users after diagnosis [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. It found a significantly lower risk of colorectal cancer-specific mortality (18% reduction) and reduced risk of distant metastases in PDE5I users versus non-users. The protective effect was notably stronger among patients who underwent open surgery, supporting a role for PDE5Is in counteracting surgery-induced immune suppression and improving oncologic outcomes. A retrospective, matched cohort study analyzing data from 5,545 prostate cancer patients who underwent prostatectomy found that PDE5I administration was associated with improved overall survival and reduced risk of death, suggesting routine use of PDE5I after prostatectomy may improve survival in prostate cancer patients[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Another population-based cohort study from Sweden focusing on gastric cancer patients showed that PDE5I use was linked to lower cancer-specific mortality particularly in early-stage cancers [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. While direct randomized clinical trials of PDE5Is in rectal cancer are still lacking, these population-based studies coupled with preclinical evidence provide convergent support for the potential adjuvant value of PDE5Is in colorectal malignancies, including rectal cancer.\u003c/p\u003e\u003cp\u003eSeveral potential mechanisms have been found for this survival benefit seen with PDE5I use. Emerging evidence indicates a duality in PDE5Is\u0026rsquo; effects on tumorigenesis and oncoprotection in different sites and organs, as presented in a recent review [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eOverall, the hypotheses regarding the contribution PDE5I to the survival of cancer patients can be divided into two approaches. The first is that the same mechanism that leads to improved erectile function is responsible for the positive effect on survival; increasing blood flow to the pelvis improves tissue oxygenation, reduces inflammation and improves healing after oncological surgeries and radiotherapy. This has been suggested as the cause of the anti-inflammatory effects observed in prostate tissue [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Increased blood flow to the tumor area also improves accessibility of anti-tumor drugs to their target, so improving the survival of those patients receiving chemotherapy [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Adequate oxygenation in the tumor microenvironment is a well-established factor in enhancing the cytotoxic efficacy of radiation as well as the response to cytotoxic drugs [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Other effects include inhibition of efflux pumps within tumor vasculature. Enhanced permeation retention (EPR) is the phenomenon whereby macromolecules, nanoparticles, or liposomes tend to accumulate more in tumor tissue than in normal tissues due to an increase in both permeability and retention. Tumors induce angiogenesis to support their rapid growth. The blood vessel walls are often defective or \u0026ldquo;leaky,\u0026rdquo; allowing large molecules and particles (like drug-loaded nanoparticles) to pass easily from the bloodstream into the tumor tissue. In addition, tumors typically have poor lymphatic drainage. Once these large particles enter the tumor, they are not efficiently removed, leading to prolonged retention. PDE5 inhibitors decrease efflux pump activity, enhancing the EPR effect, thereby increasing the concentration of the anticancer drug in tumor tissues [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The second approach explains the clinical findings through more direct anti-cancer effects via molecular pathways involving cGMP or other molecular mechanisms \u0026ndash; such as PDL1 upregulation, cell cycle arrest, and induction of apoptosis [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. One major mechanistic pathway involves immunomodulation after oncologic surgery. Preclinical and clinical data reveal that cancer surgery induces a state of immunosuppression, with a prominent expansion of myeloid-derived suppressor cells (MDSCs). These MDSCs inhibit cytotoxic T lymphocyte (CTL) and natural killer (NK) cell functions, impairing tumor clearance and promoting distant metastasis. PDE5Is such as sildenafil have been shown to block MDSC recruitment and restore CTL and NK cell activity, reducing surgery-induced immune paralysis and lowering metastasis rates. This immunomodulatory effect is supported by observations that PDE5I users experience significantly lower risks of post-operative metastasis and cancer-specific mortality [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e\u003cp\u003ePDE5Is also impact tumor cell biology at the molecular level. Zhang\u0026rsquo;s study mentioned above combined their population-based evidence with \u003cem\u003ein vivo\u003c/em\u003e and \u003cem\u003ein vitro\u003c/em\u003e experiments to investigate the mechanisms by which the PDE5I sildenafil suppresses gastric cancer growth [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. They found that by inhibiting the hydrolytic activity of PDE5, sildenafil increases intracellular cGMP, which activates protein kinase G. This leads to cell cycle arrest, increased apoptosis, and degradation of oncogenic factors such as c-MYC via downstream suppression of IL-6/JAK/STAT3 signaling. Another possible mechanism for the effect on cell cycle is an increase in levels of reactive oxidative species, which in turn impairs the function of CDK and PARP proteins [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. It is worth noting that some evidence suggests patients taking PDE5Is may have a higher risk of developing melanoma, which is linked to the activation of the RAS/RAF/ERK signaling pathway in melanoma cells [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. However, a recent Mendelian XXXandomization analysis found little evidence to support associations between genetically proxied PDE5 inhibition and 20 cancers. They did identify a protective effect of genetically proxied PDE5 inhibition on colorectal and gastric cancer risk [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e\u003cp\u003ePreclinical studies corroborate these mechanisms in colorectal cancer models. In vitro, PDE5Is inhibit proliferation and trigger apoptosis in colorectal cancer cell lines with IC50 values within achievable pharmacologic ranges [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. \u003cem\u003eIn vivo\u003c/em\u003e, oral PDE5Is reduce polyp formation and tumor growth by 50\u0026ndash;60% in chemically-induced murine models through reduction of inflammation and MDSC infiltration [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Genetic data from The Cancer Genome Atlas (TCGA) indicates that high PDE5 expression in colorectal tumors correlates with poorer survival, underscoring PDE5 as a viable therapeutic target [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Together, these preclinical and translational data underscore the clinical relevance of PDE5Is\u0026rsquo; direct molecular and immunomodulatory actions in colorectal and consequently rectal tumors.\u003c/p\u003e\u003cp\u003eOverall, the findings of our study support the potential role of PDE5 inhibitors as adjunctive therapeutic agents in the management of rectal cancer. This option has been explored \u003cem\u003ein silico\u003c/em\u003e with a novel, more potent PDE5 inhibitor, which had greater apoptotic effects and higher efficacy as an anti-tumor agent [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. There is still a lack of consistent and extensive basic research to explain the clinical findings and provide a precise mechanism for the improved survival seen in cancer patients.\u003c/p\u003e\u003cp\u003eThis study has several important strengths that support the validity and clinical relevance of the findings. It utilized a large, nationally representative dataset from CHS, Israel\u0026rsquo;s largest healthcare provider, enabling robust statistical power and generalizability to diverse patient populations. The comprehensive linked data allowed detailed longitudinal follow-up and adjustment for numerous demographic, clinical, and treatment covariates, reducing confounding bias. The use of multiple advanced statistical approaches including propensity score matching and random survival forest modeling strengthens causal inference regarding the association between PDE5I use and survival outcomes, addressing potential imbalances in baseline characteristics.\u003c/p\u003e\u003cp\u003eThe study focused on rectal cancer patients, a population with high morbidity and mortality in which PDE5I use for postoperative erectile dysfunction is common. This real-world setting supports the clinical applicability of the findings. The consistent survival benefit seen across subgroups defined by ethnicity and disease recurrence status suggests a robust effect of PDE5Is in improving rectal cancer prognosis.\u003c/p\u003e\u003cp\u003eThis study has several limitations, including potential residual confounding despite the use of propensity score matching, which may not fully account for unmeasured variables influencing survival outcomes. The observational design precludes establishing causality between PDE5I use and improved survival, and there may be selection bias related to patients who purchase these medications, such as differences in health behavior or access to healthcare. One such concern is healthy user bias, where patients prescribed PDE5Is may represent a subgroup of healthier, more health-conscious men with better baseline health status and healthcare engagement. This could partially explain the survival differences observed, independent of the drug\u0026rsquo;s direct biological effects. Patients actively seeking treatment for erectile dysfunction might also have better overall postoperative recovery or adherence to oncologic follow-up and adjuvant therapies. Though our use of propensity score matching and multivariable adjustments aimed to minimize confounding, unmeasured factors such as lifestyle, frailty, and socioeconomic status may still influence the association. This selection bias is consistent with findings in other PDE5I studies, in which users generally exhibited different health-seeking behaviors than non-users. Additionally, reverse causation cannot be fully excluded, as healthier patients may be more likely to receive PDE5Is, while patients with advanced disease or comorbidities may be less likely to be prescribed these medications. Longitudinal randomized controlled trials are necessary to definitively test the causal impact of PDE5Is on rectal cancer survival and to differentiate drug effects from confounding behavioral factors. Furthermore, the data relies on medication purchase history, which does not confirm actual usage or adherence to PDE5I therapy. The heterogeneity of the patient population, particularly regarding ethnicity and comorbidities, may also affect generalizability. Lastly, anonymization necessitated the loss of important clinical data including tumor stage, type of surgery and specifics of chemotherapy/radiotherapy, which limited our ability to comprehensively adjust for all relevant prognostic factors.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eHere, we present evidence that the use of PDE5I is associated with improved survival outcomes in patients with rectal cancer. Initial unadjusted analyses revealed significant differences in survival distributions, favoring users, with a substantial reduction in hazard risk. To account for potential confounding factors such as ethnicity, age at diagnosis, comorbidities, and treatment variables, propensity score matching was employed, further reinforcing these findings. Post-matching analyses demonstrated that users continued to experience significantly prolonged survival, with median survival times markedly increased compared to non-users. Stratified analyses across subgroups, including ethnicity and recurrence status, consistently indicated a survival benefit associated with PDE5I use, underscoring its potential role as an adjunctive therapeutic agent in rectal cancer management.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eThe following abbreviations are used in this manuscript:\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"524\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ecAMP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ecyclic adenosine monophosphate\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ecGMP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ecyclic guanosine monophosphate\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCharlson Comorbidity Index\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCHS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eClalit Health Services\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCTL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ecytotoxic T lymphocyte\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eEPR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eenhanced permeation retention\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eKDE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ekernel density estimation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ehazard ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMDSC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003emyeloid-derived suppressor cell\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNK\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003enatural killer\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eOOB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eout-of-bag\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePDE5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ephosphodiesterase 5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePDE5I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ephosphodiesterase 5 inhibitor\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eproportional hazards\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePSM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003epropensity score matching\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRSF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003erandom survival forest\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eradiotherapy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eSupplementary Materials:\u003c/strong\u003e The following supporting information can be downloaded at: https://www.mdpi.com/article/doi/s1, Figure S1: Age distribution at diagnosis of PDE5I users (right) and non-users (left); Table S1: Top 6 Variables/coefficients for Standardized Cox PH Model and Random Survival Forest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u0026nbsp;\u003c/strong\u003eConceptualization, M.L. and G.B.-S.; Methodology, M.L.; Software, J.G.; Formal analysis, J.G.; Investigation, M.L.; Data curation, M.L. and I.A.; Writing – original draft, M.L.; Writing – review \u0026amp; editing, G.B.-S.; Supervision, G.B.-S.; Project administration, G.B.-S.\u0026nbsp;All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This research did not receive any specific grant from funding agencies in the public, commercial, or non-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInstitutional Review Board Statement:\u003c/strong\u003e The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board of Emek Medical Center (0121-24-EMC) and by CHS’s Committee For The Use Of Medical Data (protocol code 1658-24, approved 27/08/24).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed Consent Statement:\u003c/strong\u003e The need for informed consent from patients was waived by the IRB (approval 0121-24-EMC) since this was a retrospective anonymized study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u003c/strong\u003e Restrictions apply to the availability of these data. Data were obtained from CHS’s Research Room platform and cannot be provided by the authors due to ethical restrictions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest:\u003c/strong\u003e The authors declare no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e We want to thank Mrs. Snait Ayalon, data administration manager of Emek Medical Center, for her assistance in providing the essential data from the “Research room” and Dr. Gillian Kay for her language writing assistance.\u003c/p\u003e\n\u003cp dir=\"LTR\"\u003e\u003cstrong\u003eDisclaimer/Publisher’s Note:\u003c/strong\u003e The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.\u003c/p\u003e\n\u003cp dir=\"LTR\"\u003e\u003cstrong\u003eDisclaimer/Publisher’s Note:\u003c/strong\u003e The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSung, H.; Ferlay, J.; Siegel, R.L.; Laversanne, M.; Soerjomataram, I.; Jemal, A.; Bray, F. 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Phosphodiesterase-5 Inhibitors Use and Risk for Mortality and Metastases among Male Patients with Colorectal Cancer. \u003cem\u003eNat Commun\u003c/em\u003e \u003cstrong\u003e2020\u003c/strong\u003e, \u003cem\u003e11\u003c/em\u003e, 3191, doi:10.1038/s41467-020-17028-4.\u003c/li\u003e\n\u003cli\u003eMei, X.L.; Yang, Y.; Zhang, Y.J.; Li, Y.; Zhao, J.M.; Qiu, J.G.; Zhang, W.J.; Jiang, Q.W.; Xue, Y.Q.; Zheng, D.W.; et al. Sildenafil Inhibits the Growth of Human Colorectal Cancer in Vitro and in Vivo. \u003cem\u003eAmerican Journal of Cancer Research\u003c/em\u003e \u003cstrong\u003e2015\u003c/strong\u003e, \u003cem\u003e5\u003c/em\u003e, 3311.\u003c/li\u003e\n\u003cli\u003eLi, W.Q.; Qureshi, A.A.; Robinson, K.C.; Han, J. Sildenafil Use and Increased Risk of Incident Melanoma in US Men: A Prospective Cohort Study. \u003cem\u003eJAMA internal medicine\u003c/em\u003e \u003cstrong\u003e2014\u003c/strong\u003e, \u003cem\u003e174\u003c/em\u003e, 964, doi:10.1001/JAMAINTERNMED.2014.594.\u003c/li\u003e\n\u003cli\u003eTang, K.; Li, B.; Wu, X.; Wang, M. Genetically Proxied Inhibition of Phosphodiesterase-5 and Cancer Risks: A Drug-Target Mendelian Randomization Analysis. \u003cem\u003eSci Rep\u003c/em\u003e \u003cstrong\u003e2025\u003c/strong\u003e, \u003cem\u003e15\u003c/em\u003e, 26716, doi:10.1038/s41598-025-12788-9.\u003c/li\u003e\n\u003cli\u003eMei, X.-L.; Yang, Y.; Zhang, Y.-J.; Li, Y.; Zhao, J.-M.; Qiu, J.-G.; Zhang, W.-J.; Jiang, Q.-W.; Xue, Y.-Q.; Zheng, D.-W.; et al. Sildenafil Inhibits the Growth of Human Colorectal Cancer in Vitro and in Vivo. \u003cem\u003eAm J Cancer Res\u003c/em\u003e \u003cstrong\u003e2015\u003c/strong\u003e, \u003cem\u003e5\u003c/em\u003e, 3311\u0026ndash;3324.\u003c/li\u003e\n\u003cli\u003eIslam, B.N.; Sharman, S.; Hou, Y.; Bridges, A.; Singh, N.; Kim, S.; Kolhe, R.; Trillo-Tinoco, J.; Rodriguez, P.C.; Berger, F.G.; et al. Sildenafil Suppresses Inflammation-Driven Colorectal Cancer in Mice. \u003cem\u003eCancer Prev Res (Phila)\u003c/em\u003e \u003cstrong\u003e2017\u003c/strong\u003e, \u003cem\u003e10\u003c/em\u003e, 377\u0026ndash;388, doi:10.1158/1940-6207.CAPR-17-0015.\u003c/li\u003e\n\u003cli\u003eHuang, W.; Sundquist, J.; Sundquist, K.; Ji, J. Phosphodiesterase-5 Inhibitors Use and Risk for Mortality and Metastases among Male Patients with Colorectal Cancer. \u003cem\u003eNat Commun\u003c/em\u003e \u003cstrong\u003e2020\u003c/strong\u003e, \u003cem\u003e11\u003c/em\u003e, 3191, doi:10.1038/s41467-020-17028-4.\u003c/li\u003e\n\u003cli\u003eOladeji, S.M.; Conteh, D.N.; Bello, L.A.; Adegboyega, A.E.; Shokunbi, O.S. Rational Design and Optimization of Novel PDE5 Inhibitors for Targeted Colorectal Cancer Therapy: An In Silico Approach. \u003cem\u003eInternational Journal of Molecular Sciences\u003c/em\u003e \u003cstrong\u003e2025\u003c/strong\u003e, \u003cem\u003e26\u003c/em\u003e, 1\u0026ndash;16, doi:10.3390/ijms26051937.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Rectal cancer, phosphodiesterase type 5 inhibitors, survival analysis, mortality risk","lastPublishedDoi":"10.21203/rs.3.rs-8123931/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8123931/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground/Objectives\u003c/strong\u003e: Phosphodiesterase type 5 inhibitors (PDE5Is) are used to treat erectile dysfunction, as they increase blood flow to the penis during sexual stimulation, supporting erection maintenance. There is limited evidence that their use increases survival in various types of cancer. As treatment for rectal cancer often results in erectile dysfunction, many patients take PDE5Is. This study assessed the association between PDE5I use and survival in rectal cancer patients. \u003cstrong\u003eMethods\u003c/strong\u003e: Utilizing data from Clalit Health Services in Israel, the analysis included 1,552 patients, with 256 users of PDE5Is. Survival differences were evaluated using non-parametric tests, Cox proportional hazards models, and propensity score matching to control for confounding variables.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: PDE5I use was found to be significantly associated with improved survival, with a hazard ratio of 0.455 (p\u0026lt;0.001). The survival benefit persisted after adjusting for covariates and implementing matching procedures.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: These findings suggest a potential protective effect of PDE5I use on survival in rectal cancer patients, warranting further investigation into underlying mechanisms and clinical implications.\u003c/p\u003e","manuscriptTitle":"The Use of Phosphodiesterase 5 Inhibitors Improves Survival in Men after Treatment for Rectal Cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-11 00:45:09","doi":"10.21203/rs.3.rs-8123931/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-02-26T09:55:34+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-25T04:48:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"210127241825766453865981730724118054442","date":"2026-02-06T14:31:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"227734361691100797789167297485958740551","date":"2026-02-04T21:25:20+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-25T08:36:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"315665339572457438288683435571274257917","date":"2025-12-14T07:35:36+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-08T06:57:14+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-08T06:56:00+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-12-03T19:44:41+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-02T17:59:03+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cancer","date":"2025-12-02T17:52:48+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d73b4e17-341c-4b98-819f-b6cca4d97d57","owner":[],"postedDate":"December 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-30T18:53:48+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-11 00:45:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8123931","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8123931","identity":"rs-8123931","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}