Study protocol for developing a patient-reported outcome measure for infection screening in hematological patients with secondary immunodeficiency.

Background

Patients with B-cell malignancies, such as chronic lymphocytic leukemia (CLL) and multiple myeloma (MM), frequently develop secondary immunodeficiencies (SID), significantly increasing their risk of infections [ 1 – 4 ]. Infections are a leading cause of morbidity and mortality in these patients, with studies reporting major infections in 36% of CLL patients over five years and a markedly higher infection risk in MM patients compared to matched controls [ 5 – 7 ]. Evidence from a recent real-world study confirms the high prevalence of infections post SID diagnosis in patients with B-cell malignancies: In a 2022 retrospective study, the mean annualized number of infections was 19.1 (and 1.5 for severe infections) for patients with SID [ 8 ]. Further real-world evidence supports the high prevalence of infections in these populations, highlighting the need for proactive monitoring [ 9 ]. Notably, even in the era of chemotherapy-free treatment strategies SID still commonly develops during therapy and remains a major concern. Some modern immunotherapies (e.g. bispecific anti-bodies) predispose patients to exceptionally high risks of infectious complications. As such, a meta-analysis of trial data from patients with MM demonstrated the risk of severe infection, pneumonia, and neutropenia in patients with MM not only in frontline and relapsed/refractory settings, but also during maintenance therapies [ 10 ].

Infections are among the leading causes of death in patients with B-cell malignancies like MM or CLL with SID [ 5 , 11 – 13 ], and thus, symptom monitoring is crucial for these patients during anticancer treatment. While inpatient monitoring allows for early infection detection, the lack of efficient and feasible approaches for monitoring outpatients presents a significant gap in care. Studies show that the time from symptom onset to diagnosis and starting subsequent treatment are important predictors of both developing pneumonia, as well as for mortality [ 14 , 15 ]. Key symptoms of infections (such as sore throat, fever, or cough) can be observed and reported by patients themselves. Consequently, one very promising monitoring approach is using so-called patient-reported outcomes (PROs). PROs refer to any health outcome (e.g., functional or symptom) which is reported directly by the patient without any interpretation by a third party [ 16 ]. Using standardized questionnaires, patients can self-report their symptoms via home monitoring portals or mobile apps [ 17 ]. This information can be fed back to the healthcare team and used to monitor patients’ symptoms even if they are not in the hospital. Such symptom monitoring systems have shown promising results for patients with hematologic malignancies, increasing their symptom management, health-related quality of life, reducing hospitalizations, and even prolonging overall survival [ 18 – 21 ].

Potentially, PRO monitoring systems could be used to remotely monitor patients with cancer and SID for infections and to automatically alert clinicians early. However, such monitoring systems are not yet widely established and it is currently unknown if PROs can be used to predict infections in susceptible patients. In conclusion, there is a need for high-quality research on PROs and quality of life in patients with cancer and SID. In our study, we aim to develop a PRO item list to detect infections in this population, which is a prerequisite to establishing PROs for effective infection monitoring. The secondary aim is to generate comprehensive data on HRQOL and its association with infections in this population.

Methods

Study design

This observational study follows a two-phase design. In the first phase, we developed an item list and an electronic app to assess it, testing the app in a feasibility study. In the second phase, we will conduct a prospective longitudinal cohort study with patients with MM or CLL and SID, using the app for daily symptom reporting to monitor infections. The study protocol is reported according to the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) and SPIRIT-PRO guidelines [ 22 , 23 ] (Supplementary 1). The study was approved by the ethics committee of the Medical University of Innsbruck (no. 1179/2024) and ethical approval will be obtained for all centers before starting the recruitment process. The study is conducted in accordance with the 1964 declaration of Helsinki.

Study development

The study development consisted of the creation of the item list and app both tested in a feasibility study with 12 CLL and MM patients to assess patients perceived comprehensibility of the item list and functionality of the app. Results were analyzed and respective adjustments were made to improve the final app and questionnaire. Results of the feasibility study will be reported separately.

Development of the item list

To develop a reliable item list to monitor and detect infections, it is necessary to establish a high-quality measurement of infections as criterion. We developed the item list based on items from the European Organisation for Research and Treatment of Cancer (EORTC) Item Library [ 24 ] and in line with international best-practice recommendations for item list development [ 25 ]. The development comprised a comprehensive review of the literature and existing measures measuring infection-related symptoms, as well as physician input on which symptoms were the most relevant to assess to monitor for infections in this population.

Based on literature on how other infections or influenza and symptom severity can be measured using PROMs [ 26 – 29 ] the following five domains were selected to be included in the item list: upper respiratory symptoms, lower respiratory symptoms, gastrointestinal symptoms, urinary symptoms, and systemic symptoms (head, sleep, fever). For each domain, potential symptoms were selected. Six physicians were approached to provide feedback on the symptoms. They were presented with a selection of 41 symptoms mapped to the 5 domains and asked to rate the importance of each symptom, as well as to select a single most-important symptom for each domain. Scores were averaged across physicians and used to select the most important symptoms for each domain. In the next step, we searched the EORTC Item Library for potential items for each selected symptom to create the provisional item list. See Supplementary 2 for more information on the item list creation. Finally, the comprehensibility and clarity of the provisional item list were evaluated during the feasibility study with patients.

App development

The app was developed based on the Computer-based Health Evaluation System (CHES) software platform, which allowed for real-time symptom tracking and data integration [ 30 ]. The software has been used extensively and also been tested with patients with hematological diseases in the past [ 31 , 32 ]. For the PRO-SID app, we developed study-specific content, which comprised information in lay language on the diseases (MM and CLL), information on infections and SID, and information on the study itself. The native app (iOS and Android) prompts patients to complete the item list once daily via push-reminders (up to two reminders).

Physician section of the app

Supplementary to the app for patients, a physician section was developed as an independent website. The physician section can be access by all participating physicians and study coordinators, providing access to data from all patients of the respective study center. On the website, physicians and study coordinators can review patients’ PRO results (see Fig. 1 for example screenshots) and enter all relevant study documentation like study visit documentation or infections that occurred during the study.

The PRO-SID study

The PRO-SID (patient-reported outcomes in secondary immunodeficiency) study is an observational cohort study that will recruit patients in academic and medical care centers in Austria (currently Innsbruck, Graz, Kufstein) and Germany (currently Garmisch-Partenkirchen, Berlin). The study is based on the original protocol version 3.0.9; potential modifications will be reviewed by the sponsor and funder, communicated to the relevant parties (investigators, ethical review committees, study participants, trial registry) and will be documented in any resulting publications. The trial is registered at clinicaltrials.gov ( NCT06821880 , registered on 11.02.2025).

We aim to recruit 120 patients (power calculation reported below), with data collected over an 18-month period. In line with the observational nature of the study, the study does not interfere with patients’ treatment and all patients will receive the normal standard of care as prescribed by their treating physician.

Patients and recruitment

The target population for this study are patients with MM or CLL who are at risk of infectious complications due to a SID. The inclusion and exclusion criteria for the PRO-SID study are listed in table 1 . Eligible patients will be approached by their treating physician in participating centers and asked to participate in the study. If they consent to participation and provide written informed consent, they will be briefed about the study by their treating physician and a study nurse will provide support as necessary to install the study app and provide further information on the study (see Supplementary 3).

Table 1 Inclusion and exclusion criteria for the study Inclusion Criteria • Adult patient (> = 18 years of age) • Written informed consent provided • Access to an internet device (e.g., personal computer or tablet to use a web-based platform, or smartphone where the study app can be installed - all common iOS and Android systems) • German-speaking (sufficient German language skills to complete questionnaires) • Diagnosis of multiple myeloma or chronic lymphocytic leukemia • Secondary immunodeficiency (defined as: recurrent infections, or infections requiring inpatient treatment, hypogammaglobulinemia (selective IgG deficiency of < 4 g/l), neutropenia and/or lymphopenia on differential blood cell counts, deficit in lymphocyte subsets as assessed by flow cytometry) • Having recently started new anticancer therapy (within 4 weeks of initiation of therapy; sooner is better) • Patient is not under active therapy for an active infection (i.e., if the patient is treated with antibiotics or antiviral treatment for a currently symptomatic infection); note that this does not refer to receiving herpes zoster prophylaxis • Patient has not received immunoglobulin replacement therapy in the last 6 months Exclusion Criteria • Patient with cognitive impairments that may hinder their ability to complete the PRO assessments • Patient is not expected to receive continued treatment at the center • Patient has a confirmed diagnosis of primary immunodeficiency or HIV • Patient has a currently active HBV or HCV infection

Data collection and measures

Patients will be in the study for one year, starting on the day of inclusion in the study. They are instructed to complete the item list (see below) daily. Up to two reminders can be configured in the app, scheduled according to patient preferences, to prompt patients to complete. If patients do not complete any assessment for several days, the study nurse will call them to inquire the reasons for noncompletion and to potentially motivate the patient to complete it again. Additionally, patients complete the EORTC Core Quality of Life questionnaire (EORTC QLQ-C30), and respective disease-specific modules (QLQ-MY20 or QLQ-CLL17) at selected study time points. Clinical data is collected at baseline and subsequent study visits. Clinical data comprises ECOG status, cancer staging, age, sex, information on current and past cancer-related treatment, and documentation of infections that occur during the study period. Infections will be assessed following the Common Criteria for Adverse Events (CTCAE v5.0) terminology.

After completing the baseline assessment (i.e., study visit 1), 4 additional study visits are conducted in 3-month intervals. These intervals were based on usual patient care schedules for CLL and MM to minimize additional burden for patients and the healthcare team. Moreover, comprehensive quality of life assessments which also comprise the EORTC QLQ-C30 and the respective disease-specific module will be conducted in 1.5-monthly intervals. See Table 2 for the study schedule and overview of assessments. Patients can withdraw from the study at any time, the study team will record the date and reason for withdrawal.

Table 2 Study schedule and overview of assessments Baseline (study visit 1) Monitoring Comprehensive HRQOL assessment 1 Study visit 2 and comprehensive HRQOL assessment 2 Comprehensive HRQOL assessment 3 Study visit 3 and comprehensive HRQOL assessment 4 Comprehensive HRQOL assessment 5 Study visit 4 and comprehensive HRQOL assessment 6 Comprehensive HRQOL assessment 1 Study visit 5 and comprehensive HRQOL assessment When? At day of inclusion (tolerance of + 7 days) After completion of baseline prompted daily until end of study 46 days after baseline visit (tolerance of + 14 days) PROMs 91 days after baseline visit (tolerance of ± 14 days) 137 days after baseline visit (tolerance of + 14 days) PROMs 183 days after baseline visit (tolerance of ± 14 days) 228 days after baseline visit (tolerance of + 14 days) PROMs 274 days after baseline visit (tolerance of ± 14 days) 319 days after baseline visit (tolerance of + 14 days) PROMs 365 days after baseline visit (tolerance of ± 14 days Includes clinical in-person visit Yes, conducted in-person at baseline & inclusion No No Yes, clinical visit and documentation may be done between day 77 and 121 to allow for flexibility in schedule No Yes, clinical visit and documentation may be done between day 169 and 197 to allow for flexibility in schedule No Yes, clinical visit and documentation may be done between day 260 and 288 to allow for flexibility in schedule No Yes, clinical visit and documentation may be done between day 351 and 395 to allow for flexibility in schedule Assessment type Single assessment Continued assessment (prompted daily) Single assessment Single assessment Single assessment Single assessment Single assessment Single assessment Single assessment Single assessment Informed consent X PROMs completed by patient (completed in this order) EORTC QLQ-C30 X X X X X X X X X EORTC disease-specific module b X X X X X X X X X SID Item List X X a X X X X X X X X Clinical documentation (done by physician) ECOG status X X X X X Current treatment status X X X X X Documentation of current or past infections b X X c X X X X a Patients will receive daily prompts as push messages in the app asking them if they experienced any new infection-related symptoms since the last assessment; if the patient confirms, they will be prompted to complete the SID Item list b The respective EORTC disease-specific module will be automatically selected based on patient disease (i.e., EORTC QLQ-MY20 or EORTC QLQ-CLL17) c Current or past infections may also be documented by the physician during the study but outside of a planned clinical visit if prompted by a patient symptom report and followed up by the physician (i.e., if the physician conducts a screening following a patient symptom report in the app)

All study-related data and documents will be archived and retained in accordance with regulatory requirements and good clinical practice standards. The principal investigator will ensure the secure storage of all records according to local standard operating procedures by the Medical University of Innsbruck following the conclusion of the study. Participants will be informed of the measures taken to protect their data during the informed consent process.

We did not implement a data monitoring committee for this study, as the study poses minimal risk to patients. The study focuses on the collection of PRO data and does not include any interventions, invasive procedures, or alterations to participants’ standard medical care. Furthermore, we do not plan for interim analyses that could impact its conduct or outcomes.

EORTC QLQ-C30 and disease specific modules

To assess HRQOL in the study, we use the EORTC QLQ-C30, EORTC QLQ-MY20, and EORTC QLQ-CLL17 questionnaires. The QLQ-C30 is a widely used cancer-specific HRQOL instrument developed by the EORTC [ 33 ]. It includes 30 items across five functional scales (physical, role, cognitive, emotional, and social), three symptom scales (fatigue, pain, and nausea/vomiting), a global health status/quality-of-life scale, and six single items assessing additional symptoms (diarrhea, constipation, sleep disturbances, dyspnea, appetite loss, constipation, financial impact). A summary score can be calculated and has been validated in patients with hematologic malignancies [ 34 , 35 ]. The EORTC QLQ-MY20 is a 20-item module designed for patients with MM and evaluates disease-specific domains. It comprises four domains: disease symptoms, side effects of treatment, future perspectives, and body image [ 36 ]. The EORTC QLQ-CLL17 is a 17-item module designed for patients with CLL. It comprises the three domains physical condition/fatigue, symptom burden due to disease and/or treatment, treatment side effects, and worries/fears about health and functioning [ 37 ]. All EORTC questionnaires have a 7-day recall period and will be used according to the EORTC’s scoring guidelines. All questionnaires will be distributed in German. The questionnaires have been used and validated extensively in patients with MM or CLL respectively [ 38 , 39 ].

Item list to measure infection-related symptoms

The item list was developed for the study based on 12 items from the EORTC Item Library and supplemented with 5 self-developed items. Due to the daily assessment schedule, we use a recall period of the day of the assessment. For some of the symptom questions, conditional questions were selected that are only shown if patients report at least “a little” impairment in the previous symptom question. This branching logic was implemented following patient input in the feasibility study. The item list covers problems with nose (e.g., runny or dry nose, 1 item), painful throat (2 items), shortness of breath (2 items), cough (2 items), headache (1 item), chills/shivering (2 items), urinary pain (1 item), vomiting (1 item), diarrhea (1 item), as well as additional items to assess if patients had fever and their temperature (if measured), as well as an open text item to report additional symptoms not covered by the questions. Every seven days, the questionnaire also includes a question about the general feeling of sickness (“Have you felt sick?”) and whether the patient had an infection that was confirmed by a physician who is not their study physician (e.g., their general practitioner). See Supplementary Material 2 for further information on the item list.

Use of PRO data during the study

PRO data is intended to supplement, not replace, clinical care in this observational study. Patients can view their daily responses and overall results from the PRO item list directly within the app. This includes a summary of their reported symptoms and trends over time, allowing them to better understand their health status and track changes. The treating physician and designated study nurses have access to the PRO results for their assigned patients through the physician portal within the app. Optionally, physicians can document the clinical action they took in response to reviewing PRO results in the physician part of the software. However, as this is a non-interventional study, we do not dictate the physician’s response. Patients are informed during the consent process about how their PRO data will be used and that it will not be reviewed on an ongoing basis by the clinical team during the study. In urgent cases, patients are advised to proactively contact the clinical team.

While the study is observational and healthcare teams are not required to act on the PRO results, the feedback provided serves as an additional resource to patient care. Treating physicians are encouraged to use the PRO results as a discussion point during consultations, helping to encourage continued patient participation. See Fig. 1 for screenshots from the patient and physician applications.

Fig. 1 Screenshots of the app and physician portal. Screenshots from the app for patients (top) and from the healthcare professional interface (bottom). To make interpretation of PRO results easier, we provide color coding as follows: answering “not at all” or “a little” for an item is shown in green color, while “quite a bit” is shown in orange and “very much” in red color

Outcomes

The primary outcome is the diagnostic accuracy of the PRO item list in identifying infections as diagnosed by a physician. The current gold standard for infection diagnosis is clinician documentation using the CTCAE. Diagnostic accuracy will be evaluated by analyzing whether the PRO item list or specific items from the list (either as single items or summary scores) can predict the presence of an infection. Infections will be identified using two complementary criteria: (1) documentation of infections by the study team using the CTCAE v5.0 criteria in the physician section of the app, or (2) the single-item question at the end of the weekly PRO item list that asks patients whether they were diagnosed with an infection by a doctor that is not their study physician (this rating will have to be confirmed by the study physician in one of the study visits).

Secondary outcome is a descriptive analysis of HRQOL changes over the study period using the EORTC QLQ-C30, with a focus on mean changes from baseline to six months. Supplementary analyses will evaluate the proportion of patients with clinically meaningful HRQOL changes, based on established thresholds for clinical importance, at baseline compared to six-month follow-up.

Exploratory outcomes are the incidence rate of infections, as reported by patients and clinicians, over the one-year observation period, changes in HRQOL before and after IgRT initiation, and completion rates (and average time it took patients to complete questionnaires) of the daily scheduled PRO assessments.

Sample size considerations

Since evidence of excellent diagnostic accuracy is crucial for any screening scale, power analysis was done to determine the sample size necessary (based on assumptions of positive and negative cases and, to be more conservative based on the number of study visits and not the number of days in the study). Even though no well-defined best-practices exist for power calculations of longitudinal data using mixed-effect regression analyses with repeated measurements from the same patient (and when multiple events can occur at the patient level), we have conducted approximate calculations based the following assumptions: To show a predictive accuracy AUC ≥ 0.80 using traditional diagnostic test methods, with a sample size of 120 patients providing an estimated 480 total assessments (3–5 study visits per patient over the 12-month observation period). Based on an estimated incidence rate of 1.5 infections per patient per year [ 8 ], this design results in approximately 180 infection-positive and approximately 300 infection-negative time points. For example, a sample of 140 from the positive group and 240 from the negative group, assuming an AUC of 0.85 results in a 95% confidence interval of 0.81–0.89. A larger number of 180 positive time points and 300 negative time points assuming an AUC of 0.85 results in a 95% confidence interval of 0.81–0.89. While the hierarchical nature of repeated measures introduces dependence between observations, which may affect precision, we estimate that a sample of 120 patients is sufficient to demonstrate a diagnostic accuracy of an AUC of 0.80 or higher. Power analysis was performed using PASS 11.0.

Planned statistical analysis

Patients will be considered in all analyses up until completing the study, or until study discontinuation (if early), or death. Infections are defined as days where an infection CTCAE rating ≥ 1 is recorded.

For the primary outcome, we will use mixed-effect regression analysis to evaluate the diagnostic accuracy of the PRO item list in identifying infections. Mixed-effect models allow to account for repeated observations of the same patient by including the variable “patient” as a random factor. We will evaluate the PRO item list answers as predictors in the model with the presence of an infection as diagnosed by a doctor as criterion. We will assess whether PRO item responses can accurately distinguish between infection and non-infection days. Model performance will be evaluated using the area under the curve (AUC) to correctly predict infections based on the PRO scores as the key metric for diagnostic accuracy. We aim to achieve an AUC of at least 0.80 or higher to demonstrate sufficient sensitivity and specificity [ 40 ].

For missing PRO data, we will explore imputation methods and compare these with complete case analyses. In cases where infections are diagnosed but PRO data for that day are missing for the same day, we will evaluate the feasibility of time-lagged prediction by considering PRO data from one to three days before or after the infection diagnosis.

Secondary and exploratory outcomes

For secondary outcomes, descriptive analyses will be performed to evaluate changes in health-related quality of life (HRQoL) over time using the EORTC QLQ-C30. Mean HRQoL scores at baseline, six months, and 12 months will be summarized, and changes from baseline to six months will be analyzed using paired t-tests or Wilcoxon signed-rank tests, depending on data distribution. The percentage of patients exceeding thresholds for clinical importance will also be assessed at baseline and six months.

For exploratory analyses, we will calculate infection incidence rates as events per person-year. Further, we will evaluate trends in PRO scores in days prior to clinician-diagnosed infections. This will include assessing whether symptom escalation in the days leading up to an infection can be identified. Additionally, subgroup analyses may explore whether predictive accuracy varies by demographic or clinical characteristics, such as age or diagnosis.

Dissemination plan

The results from this PRO-SID project will be communicated to participating patients via the study app and disseminated via publications to the medical community. Co-authorship on publications resulting from the project can be obtained by recruiting at least 10 patients as investigator, participating in the study coordination, or substantially contributing to manuscript preparation. Further, we plan to make the dataset from the study available open access in anonymized form.

Current trial status and outlook

As of the submission of this manuscript, recruitment for the PRO-SID study has begun. The first patient was enrolled on 03.02.2025, and as of 31.03.2025, 9 patients have been included in the study.

The PRO-SID study will evaluate whether remote symptom monitoring for infections can help detect infections in patients with hematological malignancies with secondary immunodeficiency, a population where early detection is critical for reducing morbidity and mortality. By potentially improving infection detection in outpatient settings, our study has the potential to make treatment safer and more effective for patients, ultimately enhancing clinical outcomes and reducing the risk of severe infection-related complications.

Supplementary Information

Supplementary Material 1.

Supplementary Material 2.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Bernhard Holzner and Markus Schuler have shared-senior authorship.

Acknowledgements

We thank all patients that participated in the feasibility study for their valuable time and input on this research project. We thank Mr. Joshua Hohenegg for help with setting up the app and assessment of data during the feasibility study. We thank Professor Johannes Giesinger for support with the planned analyses. The use of EORTC measures for this study is licensed by the EORTC.

Role of study sponsor and funder

The Medical University of Innsbruck is the sponsor of this study (contact information Medical University of Innsbruck, Innrain 52, AT-6020, mui-sponsor@i-med.ac.at ). The study was developed and is conducted by the sponsor. The funders (Takeda Pharma Ges.m.b.H and Takeda Pharma Vertrieb GmbH & Co. KG) were not involved in the study design, data collection, analysis, or interpretation, the writing of the article, or the decision to submit for publication.

Authors’ contributions

JL: Conceptualization, Methodology, Writing - Original Draft, Writing - Review & Editing, Supervision, Project Administration, Funding AcquisitionJPB: Conceptualization, Methodology, Investigation, Writing - Review & Editing CS: Investigation, Data Curation, Writing - Review & Editing, Project AdministrationBH: Conceptualization, Methodology, Software, Writing - Review & Editing, SupervisionSVM: Investigation, Writing - Review & Editing WW: Methodology, Investigation, Writing - Review & Editing MK: Conceptualization, Methodology, Investigation, Writing - Review & Editing, Funding Acquisition.

Funding information

The study is funded by Takeda Pharma Ges.m.b.H and Takeda Pharma Vertrieb GmbH & Co. KG as Investigator Initiated Research (grant IISR-2022-200331).

Data availability

No datasets were generated or analysed during the current study (i.e., this protocol).

Declarations

Ethics approval and consent to participate

The study was approved by the ethics committee of the Medical University of Innsbruck (no. 1179/2024) and ethical approval will be obtained for all centers before starting the recruitment process. The study is conducted in accordance with the 1964 declaration of Helsinki.

Competing interests

BH reports Intellectual Property Rights to the Software CHES used in the study. JL reports consultation for Evaluation Software Development GmbH. WW is an employee of syndena GmbH and received research funding from Amgen, Takeda, BMS-Celgene, Janssen-Cilag, Novartis, Roche, Sanofi, and oncotyrol and received honoraria for participation in steering and safety committees from Amgen, BMS-Celgene, and Morphosys and received honoraria for consultancy from Amgen, Takeda, BMS-Celgene, EUSA Pharma, Gilead, AbbVie, Janssen-Cilag, GSK, Incyte, Kite, Novartis, Morphosys, Merck, Pfizer, Roche, Sandoz, and Sanofi, and received honoraria from Fujimoto and Myelom- und Lymphomselbsthilfe. MKS received institutional research grants and travel expenses from PharmaMar. All other authors report no conflicts of interest.

References

1. Chinen J Shearer WT Secondary immunodeficiencies, including HIV infection J Allergy Clin Immunol 2010 125 2 Suppl 2 S195 203 10.1016/j.jaci.2009.08.040 20042227 PMC6151868 Chinen J, Shearer WT. Secondary immunodeficiencies, including HIV infection. J Allergy Clin Immunol. 2010;125(2 Suppl 2):S195–203. 20042227 10.1016/j.jaci.2009.08.040 PMC6151868

2. Patel SY Carbone J Jolles S The expanding field of secondary antibody deficiency: causes, diagnosis, and management Front Immunol 2019 10 33 10.3389/fimmu.2019.00033 30800120 PMC6376447 Patel SY, Carbone J, Jolles S. The expanding field of secondary antibody deficiency: causes, diagnosis, and management. Front Immunol. 2019;10:33. 30800120 10.3389/fimmu.2019.00033 PMC6376447

3. Tuano KS Seth N Chinen J Secondary immunodeficiencies: an overview Ann Allergy Asthma Immunol 2021 127 6 617 26 10.1016/j.anai.2021.08.413 34481993 Tuano KS, Seth N, Chinen J. Secondary immunodeficiencies: an overview. Ann Allergy Asthma Immunol. 2021;127(6):617–26. 34481993 10.1016/j.anai.2021.08.413

4. Compagno N Malipiero G Cinetto F Agostini C Immunoglobulin replacement therapy in secondary hypogammaglobulinemia Front Immunol 2014 5 626 10.3389/fimmu.2014.00626 25538710 PMC4259107 Compagno N, Malipiero G, Cinetto F, Agostini C. Immunoglobulin replacement therapy in secondary hypogammaglobulinemia. Front Immunol. 2014;5:626. 25538710 10.3389/fimmu.2014.00626 PMC4259107

5. Francis S Karanth M Pratt G Starczynski J Hooper L Fegan C The effect of immunoglobulin VH gene mutation status and other prognostic factors on the incidence of major infections in patients with chronic lymphocytic leukemia Cancer 2006 107 5 1023 33 10.1002/cncr.22094 16862572 Francis S, Karanth M, Pratt G, Starczynski J, Hooper L, Fegan C, et al. The effect of immunoglobulin VH gene mutation status and other prognostic factors on the incidence of major infections in patients with chronic lymphocytic leukemia. Cancer. 2006;107(5):1023–33. 16862572 10.1002/cncr.22094

6. Blimark C Holmberg E Mellqvist UH Landgren O Björkholm M Hultcrantz M Multiple myeloma and infections: a population-based study on 9253 multiple myeloma patients Haematologica 2015 100 1 107 13 10.3324/haematol.2014.107714 25344526 PMC4281323 Blimark C, Holmberg E, Mellqvist UH, Landgren O, Björkholm M, Hultcrantz M, et al. Multiple myeloma and infections: a population-based study on 9253 multiple myeloma patients. Haematologica. 2015;100(1):107–13. 25344526 10.3324/haematol.2014.107714 PMC4281323

7. Blimark CH Carlson K Day C Einarsdottir S Juliusson G Karma M Risk of infections in multiple myeloma. A populationbased study on 8,672 multiple myeloma patients diagnosed 2008–2021 from the Swedish myeloma registry Haematologica 2025 110 1 163 72 39021214 10.3324/haematol.2024.285645 PMC11694133 Blimark CH, Carlson K, Day C, Einarsdottir S, Juliusson G, Karma M, et al. Risk of infections in multiple myeloma. A populationbased study on 8,672 multiple myeloma patients diagnosed 2008–2021 from the Swedish myeloma registry. Haematologica. 2025;110(1):163–72. 39021214 10.3324/haematol.2024.285645 PMC11694133

8. Jolles S Smith BD Vinh DC Mallick R Espinoza G DeKoven M Risk factors for severe infections in secondary immunodeficiency: a retrospective US administrative claims study in patients with hematological malignancies Leuk Lymphoma 2022 63 1 64 73 10.1080/10428194.2021.1992761 34702119 Jolles S, Smith BD, Vinh DC, Mallick R, Espinoza G, DeKoven M, et al. Risk factors for severe infections in secondary immunodeficiency: a retrospective US administrative claims study in patients with hematological malignancies. Leuk Lymphoma. 2022;63(1):64–73. 34702119 10.1080/10428194.2021.1992761

9. Reiser M Borte M Huscher D Baumann U Pittrow D Sommer C Management of patients with malignancies and secondary immunodeficiencies treated with Immunoglobulins in clinical practice: Long-term data of the SIGNS study Eur J Haematol 2017 99 2 169 77 10.1111/ejh.12900 28467615 Reiser M, Borte M, Huscher D, Baumann U, Pittrow D, Sommer C, et al. Management of patients with malignancies and secondary immunodeficiencies treated with Immunoglobulins in clinical practice: Long-term data of the SIGNS study. Eur J Haematol. 2017;99(2):169–77. 28467615 10.1111/ejh.12900

10. Balmaceda N Aziz M Chandrasekar VT McClune B Kambhampati S Shune L Infection risks in multiple myeloma: a systematic review and meta-analysis of randomized trials from 2015 to 2019 BMC Cancer 2021 21 1 730 10.1186/s12885-021-08451-x 34172037 PMC8233183 Balmaceda N, Aziz M, Chandrasekar VT, McClune B, Kambhampati S, Shune L, et al. Infection risks in multiple myeloma: a systematic review and meta-analysis of randomized trials from 2015 to 2019. BMC Cancer. 2021;21(1):730. 34172037 10.1186/s12885-021-08451-x PMC8233183

11. Monleón Bonet C Waser N Cheng K Tzivelekis S Edgar JDM Sánchez-Ramón S A systematic literature review of the effects of Immunoglobulin replacement therapy on the burden of secondary immunodeficiency diseases associated with hematological malignancies and stem cell transplants Expert Rev Clin Immunol 2020 16 9 911 21 10.1080/1744666X.2020.1807328 32783541 Monleón Bonet C, Waser N, Cheng K, Tzivelekis S, Edgar JDM, Sánchez-Ramón S. A systematic literature review of the effects of Immunoglobulin replacement therapy on the burden of secondary immunodeficiency diseases associated with hematological malignancies and stem cell transplants. Expert Rev Clin Immunol. 2020;16(9):911–21. 32783541 10.1080/1744666X.2020.1807328

12. Forconi F Moss P Perturbation of the normal immune system in patients with CLL Blood 2015 126 5 573 81 10.1182/blood-2015-03-567388 26084672 Forconi F, Moss P. Perturbation of the normal immune system in patients with CLL. Blood. 2015;126(5):573–81. 26084672 10.1182/blood-2015-03-567388

13. Dhalla F Lucas M Schuh A Bhole M Jain R Patel SY Antibody deficiency secondary to chronic lymphocytic leukemia: should patients be treated with prophylactic replacement immunoglobulin? J Clin Immunol 2014 34 3 277 82 10.1007/s10875-014-9995-5 24557494 Dhalla F, Lucas M, Schuh A, Bhole M, Jain R, Patel SY, et al. Antibody deficiency secondary to chronic lymphocytic leukemia: should patients be treated with prophylactic replacement immunoglobulin? J Clin Immunol. 2014;34(3):277–82. 24557494 10.1007/s10875-014-9995-5

14. Chemaly RF Vigil KJ Saad M Vilar-Compte D Cornejo-Juarez P Perez-Jimenez C A multicenter study of pandemic influenza A (H1N1) infection in patients with solid tumors in 3 countries: early therapy improves outcomes Cancer 2012 118 18 4627 33 10.1002/cncr.27447 22359314 Chemaly RF, Vigil KJ, Saad M, Vilar-Compte D, Cornejo-Juarez P, Perez-Jimenez C, et al. A multicenter study of pandemic influenza A (H1N1) infection in patients with solid tumors in 3 countries: early therapy improves outcomes. Cancer. 2012;118(18):4627–33. 22359314 10.1002/cncr.27447

15. Hermann B Lehners N Brodhun M Boden K Hochhaus A Kochanek M Influenza virus infections in patients with malignancies - - characteristics and outcome of the season 2014/15. A survey conducted by the infectious diseases working party (AGIHO) of the German society of haematology and medical oncology (DGHO) Eur J Clin Microbiol Infect Dis 2017 36 3 565 73 10.1007/s10096-016-2833-3 27838792 PMC5309266 Hermann B, Lehners N, Brodhun M, Boden K, Hochhaus A, Kochanek M, et al. Influenza virus infections in patients with malignancies -- characteristics and outcome of the season 2014/15. A survey conducted by the infectious diseases working party (AGIHO) of the German society of haematology and medical oncology (DGHO). Eur J Clin Microbiol Infect Dis. 2017;36(3):565–73. 27838792 10.1007/s10096-016-2833-3 PMC5309266

16. Food US, Administration D. Patient-Reported Outcome Measures: Use in Medical Product Development to Support Labeling Claims. FDA; 2009 [cited 2020 Aug 5]. Available from: https://www.fda.gov/regulatory-information/search-fda-guidance-documents/patient-reported-outcome-measures-use-medical-product-development-support-labeling-claims

17. Basch E Mody GN Dueck AC Electronic patient-reported outcomes as digital therapeutics to improve cancer outcomes JCO Oncol Pract 2020 10.1200/OP.20.00264 32484724 Basch E, Mody GN, Dueck AC. Electronic patient-reported outcomes as digital therapeutics to improve cancer outcomes. JCO Oncol Pract. 2020. 10.1200/OP.20.00264. 32484724 10.1200/OP.20.00264

18. Basch E Deal AM Dueck AC Scher HI Kris MG Hudis C Overall survival results of a trial assessing Patient-Reported outcomes for symptom monitoring during routine cancer treatment JAMA 2017 318 2 197 8 10.1001/jama.2017.7156 28586821 PMC5817466 Basch E, Deal AM, Dueck AC, Scher HI, Kris MG, Hudis C, et al. Overall survival results of a trial assessing Patient-Reported outcomes for symptom monitoring during routine cancer treatment. JAMA. 2017;318(2):197–8. 28586821 10.1001/jama.2017.7156 PMC5817466

19. Gibbons C Porter I Gonçalves-Bradley DC Stoilov S Ricci-Cabello I Tsangaris E Routine provision of feedback from patient-reported outcome measurements to healthcare providers and patients in clinical practice Cochrane Database Syst Rev 2021 10 CD011589 34637526 10.1002/14651858.CD011589.pub2 PMC8509115 Gibbons C, Porter I, Gonçalves-Bradley DC, Stoilov S, Ricci-Cabello I, Tsangaris E, et al. Routine provision of feedback from patient-reported outcome measurements to healthcare providers and patients in clinical practice. Cochrane Database Syst Rev. 2021;10:CD011589. 34637526 10.1002/14651858.CD011589.pub2 PMC8509115

20. Balitsky AK Rayner D Britto J Lionel AC Ginsberg L Cho W Patient-reported outcome measures in cancer care: an updated systematic review and meta-analysis JAMA Netw Open 2024 7 8 e2424793 10.1001/jamanetworkopen.2024.24793 39136947 PMC11322847 Balitsky AK, Rayner D, Britto J, Lionel AC, Ginsberg L, Cho W, et al. Patient-reported outcome measures in cancer care: an updated systematic review and meta-analysis. JAMA Netw Open. 2024;7(8):e2424793. 39136947 10.1001/jamanetworkopen.2024.24793 PMC11322847

21. Perry MB Taylor S Khatoon B Vercell A Faivre-Finn C Velikova G Examining the effectiveness of electronic patient-reported outcomes in people with cancer: systematic review and meta-analysis J Med Internet Res 2024 26 e49089 10.2196/49089 39083791 PMC11325109 Perry MB, Taylor S, Khatoon B, Vercell A, Faivre-Finn C, Velikova G, et al. Examining the effectiveness of electronic patient-reported outcomes in people with cancer: systematic review and meta-analysis. J Med Internet Res. 2024;26:e49089. 39083791 10.2196/49089 PMC11325109

22. Chan AW Tetzlaff JM Altman DG Laupacis A Gøtzsche PC Krleža-Jerić K SPIRIT 2013 statement: defining standard protocol items for clinical trials Ann Intern Med 2013 158 3 200 7 10.7326/0003-4819-158-3-201302050-00583 23295957 PMC5114123 Chan AW, Tetzlaff JM, Altman DG, Laupacis A, Gøtzsche PC, Krleža-Jerić K, et al. SPIRIT 2013 statement: defining standard protocol items for clinical trials. Ann Intern Med. 2013;158(3):200–7. 23295957 10.7326/0003-4819-158-3-201302050-00583 PMC5114123

23. Calvert M Kyte D Mercieca-Bebber R Slade A Chan AW King MT Guidelines for inclusion of patient-reported outcomes in clinical trial protocols: the SPIRIT-PRO extension JAMA 2018 319 5 483 94 10.1001/jama.2017.21903 29411037 Calvert M, Kyte D, Mercieca-Bebber R, Slade A, Chan AW, King MT, et al. Guidelines for inclusion of patient-reported outcomes in clinical trial protocols: the SPIRIT-PRO extension. JAMA. 2018;319(5):483–94. 29411037 10.1001/jama.2017.21903

24. Piccinin C, Kuliś D, Bottomley A, Bjordal K, Coens C, Darlington AS et al. EORTC Quality of Life Group Item Library User Guidelines. 2022 [cited 2022 Nov 7]. Available from: https://www.eortc.org/app/uploads/sites/2/2022/10/EORTC-Item-Library-User-Guidelines.pdf

25. Piccinin C Basch E Bhatnagar V Calvert M Campbell A Cella D Recommendations on the use of item libraries for patient-reported outcome measurement in oncology trials: findings from an international, multidisciplinary working group Lancet Oncol 2023 24 2 e86 95 10.1016/S1470-2045(22)00654-4 36725153 Piccinin C, Basch E, Bhatnagar V, Calvert M, Campbell A, Cella D, et al. Recommendations on the use of item libraries for patient-reported outcome measurement in oncology trials: findings from an international, multidisciplinary working group. Lancet Oncol. 2023;24(2):e86–95. 36725153 10.1016/S1470-2045(22)00654-4

26. Yu J Powers JH Vallo D Falloon J Evaluation of efficacy endpoints for a phase IIb study of a respiratory syncytial virus vaccine in older adults using patient-reported outcomes with laboratory confirmation Value Health 2020 23 2 227 35 10.1016/j.jval.2019.09.2747 32113628 Yu J, Powers JH, Vallo D, Falloon J. Evaluation of efficacy endpoints for a phase IIb study of a respiratory syncytial virus vaccine in older adults using patient-reported outcomes with laboratory confirmation. Value Health. 2020;23(2):227–35. 32113628 10.1016/j.jval.2019.09.2747

27. Han A Poon JL Powers JH Leidy NK Yu R Memoli MJ Using the influenza Patient-reported outcome (FLU-PRO) diary to evaluate symptoms of influenza viral infection in a healthy human challenge model BMC Infect Dis 2018 18 1 353 10.1186/s12879-018-3220-8 30055573 PMC6064178 Han A, Poon JL, Powers JH, Leidy NK, Yu R, Memoli MJ. Using the influenza Patient-reported outcome (FLU-PRO) diary to evaluate symptoms of influenza viral infection in a healthy human challenge model. BMC Infect Dis. 2018;18(1):353. 30055573 10.1186/s12879-018-3220-8 PMC6064178

28. Barrett B Locken K Maberry R Schwamman J Brown R Bobula J The Wisconsin upper respiratory symptom survey (WURSS): a new research instrument for assessing the common cold J Fam Pract 2002 51 3 265 11978238 Barrett B, Locken K, Maberry R, Schwamman J, Brown R, Bobula J, et al. The Wisconsin upper respiratory symptom survey (WURSS): a new research instrument for assessing the common cold. J Fam Pract. 2002;51(3):265. 11978238

29. Mall S Akmatov MK Schultze A Ahrens W Obi N Pessler F Web-based questionnaires to capture acute infections in long-term cohorts: findings of a feasibility study Bundesgesundheitsblatt Gesundheitsforsch Gesundheitsschutz 2014 57 11 1308 14 10.1007/s00103-014-2049-6 PMC4210750 25293887 Mall S, Akmatov MK, Schultze A, Ahrens W, Obi N, Pessler F, et al. Web-based questionnaires to capture acute infections in long-term cohorts: findings of a feasibility study. Bundesgesundheitsblatt Gesundheitsforsch Gesundheitsschutz. 2014;57(11):1308–14. 10.1007/s00103-014-2049-6 PMC4210750 25293887

30. Holzner B Giesinger JM Pinggera J Zugal S Schöpf F Oberguggenberger AS The computer-based health evaluation software (CHES): a software for electronic patient-reported outcome monitoring BMC Med Inform Decis Mak 2012 12 126 10.1186/1472-6947-12-126 23140270 PMC3529695 Holzner B, Giesinger JM, Pinggera J, Zugal S, Schöpf F, Oberguggenberger AS, et al. The computer-based health evaluation software (CHES): a software for electronic patient-reported outcome monitoring. BMC Med Inform Decis Mak. 2012;12:126. 23140270 10.1186/1472-6947-12-126 PMC3529695

31. Lehmann J Buhl P Giesinger JM Wintner LM Sztankay M Neppl L Using the computer-based health evaluation system (CHES) to support self-management of symptoms and functional health: evaluation of hematological patient use of a web-based patient portal J Med Internet Res 2021 23 6 e26022 10.2196/26022 34100765 PMC8262597 Lehmann J, Buhl P, Giesinger JM, Wintner LM, Sztankay M, Neppl L, et al. Using the computer-based health evaluation system (CHES) to support self-management of symptoms and functional health: evaluation of hematological patient use of a web-based patient portal. J Med Internet Res. 2021;23(6):e26022. 34100765 10.2196/26022 PMC8262597

32. Lehmann J de Ligt KM Tipelius S Giesinger JM Sztankay M Voigt S Adherence to patient-reported symptom monitoring and subsequent clinical interventions for patients with multiple myeloma in outpatient care: longitudinal observational study J Med Internet Res 2023 25 e46017 10.2196/46017 37606979 PMC10481208 Lehmann J, de Ligt KM, Tipelius S, Giesinger JM, Sztankay M, Voigt S, et al. Adherence to patient-reported symptom monitoring and subsequent clinical interventions for patients with multiple myeloma in outpatient care: longitudinal observational study. J Med Internet Res. 2023;25:e46017. 37606979 10.2196/46017 PMC10481208

33. Aaronson NK Ahmedzai S Bergman B Bullinger M Cull A Duez NJ The European organization for research and treatment of cancer QLQ-C30: a quality-of-life instrument for use in international clinical trials in oncology J Natl Cancer Inst 1993 3 5 365 76 10.1093/jnci/85.5.365 8433390 Aaronson NK, Ahmedzai S, Bergman B, Bullinger M, Cull A, Duez NJ, et al. The European organization for research and treatment of cancer QLQ-C30: a quality-of-life instrument for use in international clinical trials in oncology. J Natl Cancer Inst. 1993;3(5):365–76. 10.1093/jnci/85.5.365 8433390

34. Giesinger JM Kieffer JM Fayers PM Groenvold M Petersen MA Scott NW Replication and validation of higher order models demonstrated that a summary score for the EORTC QLQ-C30 is robust J Clin Epidemiol 2016 69 79 88 10.1016/j.jclinepi.2015.08.007 26327487 Giesinger JM, Kieffer JM, Fayers PM, Groenvold M, Petersen MA, Scott NW, et al. Replication and validation of higher order models demonstrated that a summary score for the EORTC QLQ-C30 is robust. J Clin Epidemiol. 2016;69:79–88. 26327487 10.1016/j.jclinepi.2015.08.007

35. Efficace F Cottone F Sommer K Kieffer J Aaronson N Fayers P Validation of the European organization for research and treatment of cancer quality of life questionnaire core 30 summary score in patients with hematologic malignancies Value Health 2019 22 11 1303 10 10.1016/j.jval.2019.06.004 31708068 Efficace F, Cottone F, Sommer K, Kieffer J, Aaronson N, Fayers P, et al. Validation of the European organization for research and treatment of cancer quality of life questionnaire core 30 summary score in patients with hematologic malignancies. Value Health. 2019;22(11):1303–10. 31708068 10.1016/j.jval.2019.06.004

36. Cocks K Cohen D Wisløff F Sezer O Lee S Hippe E An international field study of the reliability and validity of a disease-specific questionnaire module (the QLQ-MY20) in assessing the quality of life of patients with multiple myeloma Eur J Cancer 2007 43 11 1670 8 10.1016/j.ejca.2007.04.022 17574838 Cocks K, Cohen D, Wisløff F, Sezer O, Lee S, Hippe E, et al. An international field study of the reliability and validity of a disease-specific questionnaire module (the QLQ-MY20) in assessing the quality of life of patients with multiple myeloma. Eur J Cancer. 2007;43(11):1670–8. 17574838 10.1016/j.ejca.2007.04.022

37. Oerlemans S Efficace F Kieffer JM Kyriakou C Xochelli A Levedahl K International validation of the EORTC QLQ-CLL17 questionnaire for assessment of health-related quality of life for patients with chronic lymphocytic leukaemia Br J Haematol 2022 10.1111/bjh.18072 35255152 Oerlemans S, Efficace F, Kieffer JM, Kyriakou C, Xochelli A, Levedahl K, et al. International validation of the EORTC QLQ-CLL17 questionnaire for assessment of health-related quality of life for patients with chronic lymphocytic leukaemia. Br J Haematol. 2022. 10.1111/bjh.18072. 35255152 10.1111/bjh.18072

38. Forde K Cocks K Wells JR McMillan I Kyriakou C EORTC Quality of Life Group Use of the European organisation for research and treatment of cancer multiple myeloma module (EORTC QLQ-MY20): a review of the literature 25 years after development Blood Cancer J 2023 13 1 79 10.1038/s41408-023-00815-9 37193682 PMC10188493 Forde K, Cocks K, Wells JR, McMillan I, Kyriakou C, EORTC Quality of Life Group. Use of the European organisation for research and treatment of cancer multiple myeloma module (EORTC QLQ-MY20): a review of the literature 25 years after development. Blood Cancer J. 2023;13(1):79. 37193682 10.1038/s41408-023-00815-9 PMC10188493

39. Youron P Singh C Jindal N Malhotra P Khadwal A Jain A Quality of life in patients of chronic lymphocytic leukemia using the EORTC QLQ-C30 and QLQ-CLL17 questionnaire Eur J Haematol 2020 105 6 755 62 10.1111/ejh.13503 32748412 Youron P, Singh C, Jindal N, Malhotra P, Khadwal A, Jain A, et al. Quality of life in patients of chronic lymphocytic leukemia using the EORTC QLQ-C30 and QLQ-CLL17 questionnaire. Eur J Haematol. 2020;105(6):755–62. 32748412 10.1111/ejh.13503

40. Mandrekar JN Receiver operating characteristic curve in diagnostic test assessment J Thorac Oncol 2010 5 9 1315 6 10.1097/JTO.0b013e3181ec173d 20736804 Mandrekar JN. Receiver operating characteristic curve in diagnostic test assessment. J Thorac Oncol. 2010;5(9):1315–6. 20736804 10.1097/JTO.0b013e3181ec173d