Abstract: To investigate therapeutic activity and safety of alpha-interferon (alpha-IFN) in combination with chlorambucil (CLB) and prednisone (PDN), we treated 9 low-grade non-Hodgkin lymphoma patients with clinical evidence of relapsed (5 cases) or resistant (4 cases) disease with such an association. Methods In all instances, treatment consisted of alpha-2a IFN administered by subcutaneous route thrice weekly for 3 weeks, CLB, 5 mg/day for 21 days, and PDN, 30 mg three times a week for 3 weeks. Cycles were repeated every 28 days. Results A well-documented clinical response was observed in 6 (4 CRs+2 PRs) of 9 patients. Interestingly, 3 of 4 CRs were achieved in patients with histologically proven bone marrow involvement. Median duration of response was 18.5 months (range, 4-29 months). Myelosuppression was a common side effect. Two patients experienced grade 3 hematologic toxicity which did not preclude continuation of therapy. Conclusions As new purine analogues are not currently available, the combination of alpha-IFN, CLB, and PDN may represent, in our opinion, a valid therapy for patients not eligible for aggressive therapy such as autologous bone marrow transplantation.

Abstract: BACKGROUND: Clinical outcome of patients with chronic lymphocytic leukemia (CLL) is often poor due to the high prevalence of comorbidities as well as functional impairment that characterize this population. However, a consensus on the definition and measurement of frailty is lacking. The present analysis was designed with the aim to develop a simple and easily applicable frailty score to predict overall survival. PATIENTS: On a retrospective basis, a geriatric assessment (GA) has been performed in 113 CLL patients older than 65 years firstly diagnosed after January 2000 at our institution. GA included the Katz Activity of Daily Living (ADL), the Lawton Instrumental Activity of Daily Living (IADL) and the Cumulative Illness Rating Scale (CIRS). Median age of patients was 71 years (range,65-90) and 32.7% were older than 75 years. According to the Rai staging system 48 (42.4%) patients were in stage 0, 47 (41.6%) in stage I-II and 18 (16%)in stage III-IV. Eighteen patients (16%) had a CIRS score higher than 6, 17 (15%) an ADL score lower than 5 and 21 (18.5%) an IADL score lower than 6. RESULTS: After a median follow-up time of 66 months (range,3-330) 29 (25,6%) out of 113 patients have died and 58 (51.3%) received therapy (i.e., 24 at the diagnosis and 34 after a median follow-up time of 29 months [range, 6-136 months]). Advanced age (HR=3.40), functional decline on ADL (HR=2.90) and IADL (HR=2.70), presence of comorbidities as assessed by CIRS score (HR=2.09), ECOG performance status (HR=4.94) and Rai clinical staging (stage 0 vs I-II, HR=3.65; stage 0 vs III-IV, HR=9.09) were all variables significant in univariate analysis. In a multivariate analysis which did not included Rai clinical staging a higher risk of death was observed for patients older than 75 years (HR=3.11; 95% CI, 1.60-6.06; P=0.001), with ADL lower than 5 (HR 3.50; 95% CI: 1.50-8.40; P=0.02) and CIRS higher than 4 (HR=2.09; 95% CI,1.08-4.05;P=0.03). An additive frailty score based on the integer part of HRs (i.e., 1 point for HR 1.1-1.9; 2 points for HR 2.0-2.9) was then calculated. By combining the risk scores (range, 0-8) for these variables, patients were stratified according to a cutoff finder analysis into 3 distinctive risk groups for overall survival : fit (score = 0, 53,3%), intermediate-fit (score=1-5; 41.5%) and frail (score= 6-8,10%). Median overall survival of patients belonging to fit, intermediate-fit and frail group was as follows: fit, 174 months [95% CI:126-222]; intermediate-fit, 104 months [95% CI:82-127] ; frail, 37 months [95% CI:3-71] (P 〈 0.0001)(Fig. 1). The predictive accuracy of our score using Harrell c-index was 0.70 (95% CI:0.53-0.87). Finally, in a head-to-head comparison with Rai clinical staging, by Cox multivariate analysis, our frailty score retained its prognostic significance (fit vs intermediate-fit, HR,3.41 [95% CI,1.63-7.15], P=0.001; fit vs frail, HR, 12.06 [95% CI,3.33-43.67] , P 〈 0.0001). CONCLUSIONS: This study represents the first attempt to develop an additive scoring system for CLL based on functional status, comorbidities and age. GA is a sensitive predictor of clinical outcome and could be used for selecting patients to treat with novel therapies. Figure 1 Figure 1. Disclosures Molica: Gilead Sciences: Speakers Bureau; Roche Italy: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees; Jansen: Membership on an entity's Board of Directors or advisory committees.

Abstract: Background: In chronic phase (CP) chronic myeloid leukemia (CML) the disease characteristics at diagnosis, risk distribution, probability of transformation to accelerated/blast phase (AP/BP), and toxicities may vary according to age. Nilotinib has shown better efficacy compared to imatinib, but it has been associated to a higher incidence of arterial thrombotic events (ATEs). Little is known on the efficacy, safety and long-term outcome of nilotinib treated patients in different age groups. Aims: To investigate the efficacy and safety, particularly the cardiovascular safety, of first-line treatment with nilotinib according to age distribution. Methods: We analyzed 345 patients ≥ 18 years of age with CP CML enrolled in clinical trials of the GIMEMA CML WP investigating nilotinib as first-line treatment. Patients were treated with: nilotinib 400 mg BID (n=73); rotation of nilotinib 400 mg BID / imatinib 400 mg OD (3-month periods for each drug)(n=123); nilotinib 300 mg BID (n=149). The median follow-up was 58 months. We divided the patients in 3 groups of age (table): 18-49 years (group A, 147 pts, median age: 39 years); 50-64 years (group B, 109 pts, median age 58 years); and ≥ 65 years (group C, 89 pts, median age 71 years). We analyzed in detail the response rates, events and outcome. Definitions: Major molecular response (MMR): BCR-ABL≤0.1% (IS), with 〉 10.000 ABL copies; MR4: BCR-ABL≤0.01% (IS), with 〉 10.000 ABL copies. Events: permanent discontinuation of nilotinib for any reason, including adverse events, progression to AP/BP, or deaths. ATEs: peripheral arterial obstructive disease (PAOD), acute coronary syndrome, chronic ischemic heart disease, significant carotid stenosis and ischemic stroke, or other significant ischemic events. Results: EUTOS high risk patients were: 8.8, 5.5, 1.1% in group A, B, and C, respectively (p=0.048). We did not observe significant differences in molecular response rates (table), including BCR-ABL/ABL 〈 10% at 3 months, MMR and MR4 at 12 months, and cumulative incidences by 5 years of MR3 and MR4. Events leading to permanent nilotinib discontinuations occurred in 31%, 29%, and 42% of group A, B, and C, respectively (p=0.049). Overall, 29 ATEs were recorded, with higher rates, as expected, in elderly patients (group A: 2%; B: 11%; C: 15.7%; p=0.006); relative risk for ATEs in group B vs. A: 5; relative risk in group C vs. A: 6.7. ATEs were the reason for permanent nilotinib discontinuation in 2% of pts 18-49 years, 7.3% of pts 50-64 years, and 11.2% of pts 〉 65 years (p=0.015). Progressions to AP/BP were significantly more frequent in younger (18 - 49 years) patients (6.8%) compared to older ( 〉 50 years) patients (1.5%), p= 0.019. Overall, 19 patients died (group A: 4.8%; B: 2.8%; C: 10%). In patients 〈 65 years all deaths (10) were leukemia-related, while in patients 〉 65 years, all but one (8/9) deaths were leukemia-unrelated. The 6-year overall-survival was 94%, 97%, and 84% in pts 18-49 years, 50-64 years, and 〉 65 years of age (p=0.12) Summary/Conclusion: Nilotinib as first-line treatment of newly diagnosed CP CML patients showed high rates of molecular responses in all age groups. However, compared to older patients, significant more progressions occurred in younger (18-49 years) ones; the causes of death in this group were all leukemia-related. In contrast, in elderly patients ( 〉 65 years) the causes of death were almost all leukemia-unrelated. ATEs were rare (2%) in patients of 18-49 years, while high rates ( 〉 10%) of ATEs were recorded in those of 50-64 years; as expected, ATEs occurred even more frequently in patients 〉 65 years. These data suggest that while in patients 〉 50 years more attention should be focused on the prevention of ATEs, in younger ones more efforts are needed to avoid the progression of CML to accelerated/blast phase. Disclosures Gugliotta: Novartis: Consultancy, Honoraria; Bristol Myers Squibb: Consultancy, Honoraria. Castagnetti:Bristol-Myers Squibb: Consultancy, Honoraria; Novartis: Consultancy, Honoraria; ARIAD Pharmaceuticals: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria. Breccia:Novartis: Consultancy, Honoraria; Bristol Myers Squibb: Honoraria; Celgene: Honoraria; Ariad: Honoraria; Pfizer: Honoraria. Carella:Millenium: Speakers Bureau; Genentech: Speakers Bureau. Tiribelli:Ariad Pharmaceuticals: Consultancy, Speakers Bureau; Bristol-Myers Squibb: Consultancy, Speakers Bureau; Novartis: Consultancy, Speakers Bureau. Soverini:Ariad: Consultancy; Bristol-Myers Squibb: Consultancy; Novartis: Consultancy. Cavo:Janssen-Cilag: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Millennium: Consultancy, Honoraria; Bristol-Myers Squibb: Consultancy, Honoraria; Celgene: Consultancy, Honoraria. Martinelli:Pfizer: Consultancy, Speakers Bureau; ARIAD: Consultancy; Roche: Consultancy; MSD: Consultancy; Novartis: Speakers Bureau; Amgen: Consultancy; Genentech: Consultancy; BMS: Speakers Bureau; Pfizer: Consultancy, Speakers Bureau; ARIAD: Consultancy; Roche: Consultancy; MSD: Consultancy; Amgen: Consultancy; Genentech: Consultancy. Saglio:Ariad: Consultancy; Pfizer: Consultancy; Bristol Myers Squibb: Consultancy. Baccarani:Bristol Myers Squibb: Consultancy, Honoraria, Speakers Bureau; Pfizer: Honoraria, Other: personal fees, Speakers Bureau; Ariad: Honoraria, Other: personal fees, Speakers Bureau; Novartis: Honoraria, Speakers Bureau. Rosti:Roche: Honoraria, Research Funding, Speakers Bureau; Pfizer: Honoraria, Research Funding, Speakers Bureau; Incyte: Honoraria, Research Funding, Speakers Bureau; BMS: Honoraria, Research Funding, Speakers Bureau; Novartis: Honoraria, Research Funding, Speakers Bureau.

Abstract: Several papers authored by international experts have proposed recommendations on the management of BCR-ABL1+ chronic myeloid leukemia (CML). Following these recommendations, survival of CML patients has become very close to normal. The next, ambitious, step is to bring as many patients as possible into a condition of treatment-free remission (TFR). The Gruppo Italiano Malattie EMatologiche dell’Adulto (GIMEMA; Italian Group for Hematologic Diseases of the Adult) CML Working Party (WP) has developed a project aimed at selecting the treatment policies that may increase the probability of TFR, taking into account 4 variables: the need for TFR, the tyrosine kinase inhibitors (TKIs), the characteristics of leukemia, and the patient. A Delphi-like method was used to reach a consensus among the representatives of 50 centers of the CML WP. A consensus was reached on the assessment of disease risk (EUTOS Long Term Survival [ELTS] score), on the definition of the most appropriate age boundaries for the choice of first-line treatment, on the choice of the TKI for first-line treatment, and on the definition of the responses that do not require a change of the TKI (BCR-ABL1 ≤10% at 3 months, ≤1% at 6 months, ≤0.1% at 12 months, ≤0.01% at 24 months), and of the responses that require a change of the TKI, when the goal is TFR (BCR-ABL1 & gt;10% at 3 and 6 months, & gt;1% at 12 months, and & gt;0.1% at 24 months). These suggestions may help optimize the treatment strategy for TFR.

Abstract: Background: Successful tyrosine-kinase inhibitors (TKIs) discontinuation has been obtained in some patients (pts) with chronic-phase chronic myeloid leukemia (CP-CML). Careful molecular monitoring after discontinuation is the key to guarantee the safety, in terms of prompt resumption of therapy according to retreatment threshold criteria. It was observed that the majority of relapses usually occur during the first 6 months after TKI discontinuation [Saussele S, Lancet Oncol 2018; Etienne G, JCO 2017], accounting for the monthly quantitative PCR (qPCR) that all prospective protocols included in the trial design at least during the first half-year. Two studies [Kong HJ, Cancer 2017; Shanmuganathan N, Blood 2019] investigated if performing molecular analysis with a different and less "cautious" timeframe yields comparable efficacy with logistical issues reduction. Here we retrospectively evaluated how molecular monitoring has been conducted in Italy on a cohort of patients not included in any prospective trial with follow-up visits. Methods: The outcome of Italian patients with CP-CML who discontinued TKIs per clinical practice has recently been reported [Fava C, Haematologica 2019]. For the purpose of the present study, all the 32 participating centers were required to provide dates and molecular results available for each enrolled patient in the first 24 months after TKI stop. Descriptive analysis was carried out. The average time to the loss of major molecular response (MMR), the frequency of the visits (monitoring) and the occurrence of loss of MMR within the first 6 months, between 6-12 months, and 13-24 months were computed. When appropriate non-parametric tests were used to test for differences. Results: 227 chronic phase CML pts were included in this sub-analysis. Median age at TKI discontinuation was 58.73 years and median follow up since TFR was 2.03 years. In this timeframe every patient had a mean of 7.95 appointments for molecular evaluation. Overall, 1804 analysis were performed, of which 18.2% happened in the first three months and 38.2% in the first six months. During the first three months of TKI discontinuation, 40 pts (17.6%) didn't have any molecular assessment; 78 pts (34.4%) had only 1 qPCR performed, 77 pts (33.9%) 2 qPCR, 31 pts (13.7%) 3 qPCR and 1 pt (0.4%) 4 qPCR. For the first six months after TKI stop, 7 pts (3.1%) didn't undergo any BCR-ABL1 evaluation; 37 pts (16.3%) had only 1 analysis, 60 pts (26.4%) 2 analysis, 37 pts (16.3%) 3 analysis, 28 pts (12.3%) were evaluated 4 times, 40 pts (17.6%) 5 times, 17 pts (7.5%) 6 times and only 1 pt (0.4%) 7 times. The majority of visits fell between the 3rd and the 7th month after TKI interruption (Figure 1) with 84 pts (52.2%) being evaluated at month 3, 96 pts (59.6%) at month 4, 80 pts (49.7%) at month 5, 89 pts (55.3%) at month 6, 101 pts (62.7%) at month 7. In the first six months the visits occurred with a mean interval of 1.44 months; between months 7-12 molecular evaluations were performed every 1.94 months; during the second year of discontinuation (months 13-24) every 2.89 months (p 〈 0.001). Seventy-one pts lost major molecular response (MMR) in a mean time of 5.56 months. As expected, 55 pts (77.5%) lost MMR during the first six months whereas 16 pts (22.6%) relapsed later on: 3 pts (4.2) relapsed during the first month, 7 pts (9.9%) after two months, 13 pts (18.3%) after three, 19 pts (26.8%) after four, 8 pts (11.3%) after five months and 5 pts (7%) at six months. Only 6 patients lost MMR after 12 months of follow-up in TFR. All patients regained at least MMR after TKI resumption, and no progression occurred. Finally, we evaluated the number of patients who would experience a delay in the diagnosis of MMR loss if a three-months monitoring schedule was adopted. In the first 6 months, 15 pts (27.3%) would have a one month delay, 22 (40%) a 2 months delay; 18 pts (32.7%) would have a right timing. Very few patients would experience a delay in the following months (Figure 2). Discussion: The safety of TFR relies consistently on the management of patients off-therapy especially during the first 6 months, when molecular relapses more often occur. Our retrospective analysis showed that a less intense frequency of monitoring did not affect the success of TFR nor put pts at risk of progression. However, these data confirm that the first 6 months off-treatment require a more stringent follow-up for early detection of MMR loss. Disclosures Rosti: BMS: Speakers Bureau; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Pfizer: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Incyte: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Castagnetti:Novartis: Honoraria; Incyte: Honoraria; Pfizer: Honoraria; Bristol Myers Squiib: Consultancy, Honoraria. Capodanno:Novartis: Honoraria; Incyte: Honoraria. Ferrero:Novartis: Honoraria. Crugnola:Novartis: Honoraria; Incyte: Honoraria. Elena:Pfizer: Consultancy; Novartis: Consultancy. Breccia:Pfizer: Honoraria; Celgene: Honoraria; Novartis: Honoraria; BMS: Honoraria; Incyte: Honoraria. Iurlo:Novartis: Other: Speaker Honoraria; Pfizer: Other: Speaker Honoraria; Incyte: Other: Speaker Honoraria. Bocchia:BMS: Honoraria; Incyte: Honoraria; Novartis: Honoraria. Lunghi:Pfizer: Honoraria; Novartis: Honoraria; Incyte: Honoraria. Cedrone:BMS: Honoraria; Novartis: Honoraria. Sgherza:Pfizer: Honoraria; Novartis: Honoraria; BMS: Honoraria; Incyte: Honoraria. Santoro:Pfizer: Honoraria; Novartis: Honoraria; Incyte: Honoraria. Giai:Pfizer: Honoraria; Novartis: Honoraria; BMS: Honoraria. Caocci:Novartis: Honoraria; Celgene: Honoraria. Levato:Incyte: Honoraria; BMS: Honoraria; Novartis: Honoraria; Pfizer: Honoraria. Abruzzese:BMS: Consultancy; Incyte: Consultancy; Pfizer: Consultancy; Novartis: Consultancy. Saglio:Pfizer: Consultancy; Celgene: Consultancy; Incyte: Consultancy; Jansen: Consultancy; Ariad: Consultancy; Novartis: Consultancy; BMS: Consultancy. Fava:Pfizer: Honoraria; Novartis: Honoraria; BMS: Honoraria; Incyte: Honoraria.

Abstract: Abstract 4234 Background: Whilst recent data indicates that survival of chronic myeloid leukemia (CML) patients, who are in complete cytogenetic response (CCyR) with Imatinib therapy, is not statistically significantly different from that of the general population, health-related quality of life (HRQOL) differences do exist. However, to date no study has investigated the predictive factors of long-term HRQOL outcomes of CML patients treated with TKIs. Aim: The main objective of this study was to investigate potential key factors associated with long-term HRQOL outcomes of CML patients in CCyR treated with first line Imatinib therapy. A secondary objective was to investigate the relationships between fatigue and other treatment related symptoms and describe how fatigue relates to socio-demographic and clinical data. Patients and Methods: Analysis was performed on 422 CML patients recruited in an observational multicenter study. Median time in treatment with Imatinib was five years (range: 3 to 9.3 years). HRQOL was assessed with the Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36). This questionnaire consists of 36 items covering eight generic HRQOL domains: physical functioning (PF), role limitations due to physical health (RP), bodily pain (BP), general health perceptions (GH), vitality (VT), social functioning (SF), role limitations due to emotional problems (RE), and mental health (MH). Predictor variables investigated included, fatigue and social support, measured with two psychometrically robust questionnaires, that is the Functional Assessment of Chronic Illness Therapy (FACIT)-Fatigue scale and the multidimensional scale of perceived social support (MSPSS) scale. Other CML treatment related symptoms were measures with an ad hoc CML symptom checklist. Key socio-demographic and clinical data including, age, gender, education, Sokal risk, response to therapy and duration of treatment, were also considered. Univariate and multivariate regression analyses were used to identify a set of independent predictors for each SF-36 scale, via a stepwise selection procedure. Results: In the multivariate analysis the following factors independently predicted a better PF: younger age (P 〈 0.001), being male (P 〈 0.001), higher education (P=0.002), and less fatigue(P 〈 0.001). Together, this set of variables explained 56% of the variance in the PF scale. Fatigue was the only variable showing an independent and consistent association across all HRQOL domains measured by the SF-36. Role physical (RP) and role emotional (RE) scales (SF-36) were found to be the two mostly compromised aspects by fatigue severity. As fatigue was found to be the main predictor variable, for descriptive purposes in figure 1 we report mean scores of the SF-36 scales by levels of fatigue. Mean score differences, between patients reporting low versus high fatigue levels, were respectively 70 and 63 points for the RP and RE scales. Higher perceived social support independently predicted better social functioning (P 〈 .001) and mental health (P 〈 .001). Hb levels, measured at the most recent follow-up visit (mean time 2.9 weeks), showed a weak correlation (r=.187) with fatigue. Higher levels of fatigue were more common in those patients who already had comorbidity at diagnosis and in female patients. Patients who reported higher levels of fatigue also reported a higher severity of other CML symptoms. Conclusion: To our knowledge, this was the first investigation to date of factors associated with long-term HRQOL in CML patients being treated with an oral anticancer-targeted therapy. Our findings suggest that although responding to Imatinib therapy, long-term patient's HRQOL is greatly affected by fatigue levels. Also, our results suggest that symptom management is crucial to the possible improvement of HRQOL outcomes. Legend: Low, Low-Medium, Medium-High and High correspond respectively to the 4th (75th to 100th percentile), 3rd, 2nd and 1st (0th to 25th percentile) quartile of FACIT-Fatigue scale. On this scale, the higher the score the lower is the level of fatigue. Disclosures: Efficace: Bristol Myers Squibb: Consultancy; Novartis: Research Funding. Baccarani:Novartis : Consultancy, Honoraria; Bristol Myers Squibb: Consultancy, Honoraria; Pfizer and Ariad: Honoraria. Breccia:Bristol Myers Squibb: Consultancy; Novartis: Consultancy. Rosti:Novartis: Consultancy, Honoraria, Research Funding; Bristol Myers Squibb: Consultancy, Honoraria. Alimena:Novartis: Honoraria; Bristol Myers Squibb: Honoraria. Turri:Novartis: Consultancy, Novartis Other; Bristol Myers Squibb: Bristol Myers Squibb, Bristol Myers Squibb Other, Consultancy.