Skip to main content
Download PDF

Patient-reported outcome (PRO) instruments used in patients undergoing adoptive cell therapy (ACT) for the treatment of cancer: a systematic review

Systematic Reviews volume 12, Article number: 183 (2023) Cite this article

A Correction to this article was published on 30 April 2024

This article has been updated

Abstract

Introduction

Adoptive cell therapy (ACT) is a rapidly evolving field. Patient-reported outcomes (PROs) allow patients to report the impact of treatment on their quality of life during and after treatment. The systematic review aims to characterise the breadth of PROs utilised in ACT cancer care and provide guidance for the use of PROs in this patient population in the future.

Methods

A systematic search was conducted (MEDLINE, PsycINFO, Embase and CINAHL) in August 2021 by two reviewers. Search terms covered the following: “adoptive cell therapy”, “patient-reported outcomes” and “cancer”. Studies were included if they used a PRO measure to report the impact of ACT. The methodological quality of PROs was assessed. Forward and backward reference searching was conducted of any relevant papers. A quality grading scale was applied based on Cochrane and Revenson criteria for classification of high-quality studies. Key data from the studies and the included PROs was extracted by two researchers and tabulated.

Results

One-hundred nine papers were identified; 11 papers were included. The majority of studies were single-arm trials or observational studies. Twenty-two different PROs were identified; none was ACT specific. The PROMIS-29 and EQ-5D were most commonly used. Few studies collected PRO data in the first 1–2 weeks. Four studies followed patients up for over a year, and a further four studies followed patients for approximately 3 months.

Discussion

None of the PROs identified have been designed specifically for ACT. Appropriateness of existing instruments should be considered. It should be considered whether it is appropriate to collect data more frequently in the acute stage and then less frequently during follow-up. It should be considered if one tool is suitable at all time points or if the tool should be adapted depending on time since treatment. More research is needed to identify the exact timings of PRO assessments, and qualitative work with patients is needed to determine the most important issues for them throughout the treatment and follow-up.

Peer Review reports

Background

Surgery, chemotherapy and radiotherapy have been the main treatments for cancer for many years. More recently, however, new treatments such as targeted therapies and immunotherapies have started to be developed and have shown promising results in terms of survival [1]. Adoptive cell therapy or adoptive cell transfer (ACT) is a form of immunotherapy which harnesses the natural ability of immune cells to specifically recognise and eliminate target cells; thus, tumour-specific T cells can be infused to patients with the aim of the host immune system recognising and attacking cancer cells [2]. ACT has quickly become one of the fastest-growing areas of immune-oncology (IO) clinical research in the world [3]. ACT could be an additional treatment option for patients where other targeted and immunotherapy approaches have failed [4].

There are many types of ACT [5], but chimeric antigen receptors cell therapy (CAR T-cell) has made the most progress in terms of both clinical development and regulatory approval [6]. CAR T-cell treatments which target CD19 have demonstrated significant clinical benefit in clinical trials of patients with CD19 positive B-cell malignancies. A systematic review and meta-analysis of CAR-T trials found that CAR-T had better survival outcomes for large B-cell lymphoma patients compared to high-dose chemotherapy or autologous stem cell transplant [7]. It has been reported that children with aggressive lymphomas had very few treatment options available to them before CAR-T developments [1].

In 2017, the first two CD19-directed CAR-T therapies, tisagenlecleucel and axicabtagene ciloleucel, were approved by the Food and Drug Administration (FDA) and subsequently the European Medicines Agency (EMA) to treat patients with diffuse large B-cell lymphoma (DLBCL) and B-cell acute lymphoblastic leukaemia (B-ALL). Both of these licenced treatments are now being widely used in the commercial setting [8]. Since 2017, the haematological indications for approved CD19-directed CAR T-cell therapies have broadened to include conditions such as mantle cell lymphoma and certain types of follicular lymphoma, and in 2021, the first B-cell maturation antigen (BCMA)-directed CAR-T, idecabtagene vicleucel, was approved by the FDA for use in multiple myeloma. Tisagenlecleucel is another form of ACT which is also licensed for use. Since ACT is an emerging and expanding field, many treatments are still only available within the context of early phase clinical trials. Therefore, detailed knowledge of specific toxicities and in particular long-term effects may still be unknown. There is no consensus on what constitutes short- and long-term effects in this context; in a review of late effects, Chakraborty et al. [9] define toxicities that occur beyond 1–3 months post infusion as long-term effects, suggesting that short-term effects would occur in the first 3 months.

Due to the unique way ACT therapies work, many of the toxicities experienced by patients differ from those linked to traditional cytotoxic drugs and immunotherapies. CAR T-cell toxicities or the so-called on-target effects are variable, and the spectrum of toxicities depends on the specificity of the precise antibody target and T-cell activation [10]. Not all ACT treatments will have the same severity or range of toxicities. As safety data continues to emerge and mature, the toxicity profiles for these novel therapies will develop allowing more tailored patient management depending on the particular type of ACT therapy received. The toxicity profile for CD19 CAR T-cell is the most mature with over 1000 patients treated on CD19 CAR T-cell clinical trials in the USA alone, and increasing numbers of patients now treated both on and off trials globally [10]. Although even this group where toxicity data is more established, information on long-term events remains limited [11].

Acute toxicities are more well documented, and in fact, both cytokine release syndrome (CRS) and neurotoxicity, both of which have proved to have serious and/or life-threatening consequences, have received significant attention [12]. CRS is a spectrum of clinical and laboratory findings of fevers, hypotension, hypoxia and neurologic changes associated with substantial elevations of serum cytokine levels. The time of onset of CRS can be variable, ranging from a few hours to over a week after CAR T-cell infusion [13]. Neurologic toxicity is the second major side effect which has been seen in a substantial number of patients treated with CD19-targeted CAR T-cells. This toxicity is now widely referred to as immune effector cell-associated neurotoxicity syndrome (ICANS) [14] as it has also been observed following other types of cellular therapies. The clinical presentation of ICANS can be varied and includes tremor, headache, encephalopathy (confusion or delirium), expressive aphasia, motor weakness, seizures, depressed level of consciousness and, rarely, diffuse cerebral oedema. The onset of ICANS is also variable and can occur as early as 1 day post treatment, although presentation tends to be later than CRS and can occur up to the third or fourth week after infusion [13].

Patients can report toxicities they are experiencing using patient-reported outcomes (PROs). PROs are increasingly being used to ensure that patients have the opportunity to accurately report their own experience during and after treatment and provide a greater understanding of the impact of a disease and/or its treatments including any toxicities experienced [15, 16]. In clinical practice, PRO data can be used to inform and guide patient-centred care and clinical decision-making. In clinical trials, PROs can be used to assess the efficacy, safety and tolerability of treatments from the patient perspective, providing valuable insights into patients’ symptoms and health-related quality of life (HRQOL) [17, 18] and can be used to inform regulatory decision-making, clinical guidelines and health policy [19,20,21,22]. Evaluating PRO data alongside other trial outcomes can provide important information to aid in the understanding of the risks and benefits of treatment from the patients’ perspective. A Medicare Evidence Development and Coverage Advisory Committee (MEDCAC) meeting included a discussion with key stakeholders and experts in the field on the use of PROs in CAR-T trials. The panel emphasised the additional valuable data PROs provide but voiced concerns about their use due to lack of standardisation in scoring and patient and clinician understanding of the measures. These concerns need to be addressed to fully embrace the use of PROs in CAR T-cell trials.

It is important to consider the timing of PRO assessments within advanced cell therapy trials. Lasiter et al. (2020) recommend both short- and long-term follow-up. Regular PRO assessment should occur during the active treatment stage but given the curative expectations of these therapies, long-term follow-up (potentially up to 15 years for some trials) is recommended to identify any long-term side effects. Despite these treatments being in their infancy and the changing profile of toxicity overtime, it is necessary to further understand the short- and long-term effects of ACT. It is the aim of the potential lack of studies exploring long-term effects of ACT; it is still the aim within this review to include studies focusing on both short- and long-term effects.

Recent reviews have explored the collection of HRQOL data [23] or the use of PROs in CAR T-cell trials specifically [24]. Messina et al. [25] reported that the use of PROs in CAR T-cell trials is considerably less than the industry average (6.17% compared with 27%), despite the growing importance of HRQOL and its impact on value-based care [26,27,28]. The authors concluded that despite the increase in interest in ACT trials, there continues to be a deficiency of including and reporting of PROs in the trial design of this new therapeutic area. Similarly, Raymakers et al. [23] identified 424 CAR-T trials, and only 29 (6.8%) included HRQOL as a primary or secondary outcome.

Qualitative studies exploring the experience of patients receiving ACT treatment are limited. The three recent studies in this area have all focused on CAR-T rather than ACT more broadly [29,30,31]. Cheng et al. [29] reviewed a number of PROs that had been used in CAR-T trials and explored whether their study participants endorsed the items covered in these questionnaires. They reported that physical, emotional, social, role functioning and fatigue were all highly endorsed by patients, and cognitive function, pain, sleep, and general symptoms were moderately endorsed. They concluded that the EORTC-QLQ-C30 had the best coverage of items, but a CAR-T-specific questionnaire may be required to cover some of the key symptoms. Whisenant et al. [31] created a list of the commonly reported CAR-T treatment side effects, the most common being fatigue. Similar to Cheng et al. [29], Whisenet et al. [31] found that existing questionnaires did not cover all areas of importance of this patient group, and as a result, suggested adding additional items to the MDSAI to create the MDSAI-CT, a tool specific for patients receiving cellular therapy. In Jenei et al.’s qualitative study [30], they reviewed an online social media forum, and their findings focused on patient experienced more broadly such as accessing and navigating treatment and overcoming uncertainties.

Since ACT is a rapidly evolving field in cancer care with the potential to offer some patients durable response, it is important to understand what the short- and long-term effects of these novel treatments are for patients living with and beyond cancer. PRO data could inform the effective management of both short- and long-term physical and psychosocial morbidities.

The aim of this systematic review was to characterise the breadth of PROs utilised in ACT cancer care and provide guidance for the use of PROs in this patient population in the future. Specific objectives were as follows:

  • Identify which PROs have been used in the ACT patient population in clinical trials or in clinical practice.

  • Determine which instruments have been developed and validated in the ACT patient population.

  • Summarise the available reliability and validity data and current use for PROs in the ACT patient population.

  • Explore what issues are covered in PROs used in the ACT population.

  • Identify any areas for future research in the use of PROs in ACT patients.

Methods

Search strategy

A systematic search was conducted on four databases (MEDLINE, PsycINFO, Embase and CINAHL) in August 2021. An information specialist helped to develop the search strategy. We used similar keywords across the databases, adapting the Boolean operators and MeSH vocabulary. The search terms used were related to the following: “adoptive cell therapy”, “patient-reported outcomes” and “cancer”. As the majority of ACT treatment is given in the context of clinical trials, it is anticipated that many of the studies identified will be clinical trials. We did however want to include as many relevant papers as possible; therefore, the search was not limited to clinical trials. Any studies including ACT patients in a clinical trial or clinical practice context were included. An example of the full research strategy can be found in Table 1. Results were not restricted by date or language. Articles identified were stored and managed in EndNote and duplicates removed.

Table 1 Example of full search terms used in MEDLINE
Full size table

Selection and screening

Identified articles were imported into the Rayyan systematic review reference system [32], and all were independently screened by two reviewers (S. T. and J. C. M.) against the inclusion and exclusion criteria. Studies were included if they used a PRO measure to report the impact of ACT treatment. There were no restrictions based on comparisons, outcomes assessed or study design. Initially, the titles and abstracts were screened. The full text was retrieved for any paper which potentially met the inclusion criteria. The two reviewers would discuss any discrepancies, and a third reviewer (M. D.) would be consulted if required. Forward and backward reference searching was used to identify any additional papers for inclusion.

Data extraction

Two independent reviewers (S. T. and K. L.) used a structured Excel table to extract data from the selected full-text articles. Data collected included information regarding the publication (author(s), journal, year of publication), the study (type of study, setting), the intervention (ACT, treatment regimen), characteristics of the population (cancer type, stage, type of therapy) and outcomes. Data extraction also captured information related to the identified PRO measure(s) and aspects of clinical utility including name of the PRO, the concept it measured, mode and timing of administration, recruitment and completion rates and methodology used for the analysis (statistical or clinical significance, thresholds, type of measure and the method used for the analysis). Once the list of included papers had been generated, a list was created of the issues covered in the identified PROs these issues were cross-referenced against the symptoms and functional issues identified in available qualitative studies [29, 31] to explore if any of the PROs fully address the needs of this patient group.

Methodological assessment of PRO use

The consensus-based standards for the selection of health status measurement instruments (COSMIN) checklist is a tool designed to assess key psychometric qualities (validity, reliability and responsiveness to change) of PROs [33]. Given the anticipated dearth of PROs developed specifically for the ACT population, it was decided that the modified version of the COSMIN checklist as recommended by the FDA [21] would be applied to any PROs not specific to ACT, and the full COSMIN tool would be applied if any ACT-specific tools were identified. The key psychometric qualities assessed in the modified version include conceptual framework, reliability and content validity, construct validity and clinical relevance of score changes (Table 2). It was felt that this would be sufficient for any non-ACT-specific PROs. Original validation papers for the included PROs were examined to collect relevant information of psychometric properties. An additional search was carried out for each questionnaire to identify any additional studies where the questionnaires had been used in the ACT population. Given that no RCTs were identified in the review, it was not felt appropriate to use the Cochrane risk-of-bias criteria. A description of the quality grading scale applied is presented in Table 3. This classification system was devised using Cochrane [34] and Revenson [35] criteria for classification of high-quality studies and has been used.

Table 2 Modified version of COSMIN checklist
Full size table
Table 3 Study quality grading criteria (grade 1 indicates the highest quality study)
Full size table

Results

The search retrieved 103 papers, seven duplicates were removed and the titles and abstracts of the remaining 96 were reviewed. A PRISMA flow diagram is presented in Fig. 1.

Fig. 1
figure 1

Flow diagram of articles identified for use in the review

Full size image

Sixteen papers were selected for full-text review, and a further six were identified following forward and backward reference searching. Of the 22 papers where full text was reviewed, 11 were excluded. Reasons for exclusion are as follows: no PRO reported (n = 1), review paper (n = 5), commentary paper (n = 2), abstract only (n = 1), protocol only (n = 1) and qualitative study (n = 1). References in the five review papers were searched to ensure all relevant papers had been included. Some of the included papers were published as abstracts only, but they included sufficient detail for data extraction. Searches were conducted to ensure full-text papers were not available. Given the limited number of eligible papers, it was decided that these papers would be included.

Study characteristics

The majority of studies were conducted in the USA (n = 7) [36,37,38,39,40,41,42], three were international studies conducted in several countries [26, 43, 44] (see Table 4 for full list of countries included) and one was conducted in China [45] (Table 3). Six studies included participants with a single type of cancer: melanoma (n = 1) [45], myeloma (n = 2) [26, 38], leukaemia (n = 1) [43] and lymphoma (n = 2) [36, 44]. Two studies included participants with any haematological malignancy [39, 42], one study included lymphoma or leukaemia patients [37, 41] and one study included lymphoma, leukaemia or myeloma participants [40]. The number of participants included in the studies ranged from n = 16 to n = 128. The majority of studies were single-arm trials or observational studies and were graded as a 7 in terms of their methodological quality. Only two studies included a comparison arm, but these were not randomised controlled trials; one was an observational cohort study [39], and one was a retrospective study [45]. The majority of the trials used CAR-T treatment (n = 8) [36,37,38,39,40,41,42, 46], two used Tisagenlecleucel [43, 44] and one used adoptive immunotherapy using cytokine-induced killer (CIK) cells [45].

Table 4 Study characteristics
Full size table

Patient-reported outcomes

A total of 23 different PROs were used across the studies (Table 5). The most commonly used PRO were the PROMIS-29 [48] which was used in four of the identified studies [36, 40,41,42] and the EQ5D [49] which was used in three studies [38, 42, 43]. Ten of the PROs were generic measures not focusing on any particular disease group. Seven of the generic PROs were measures assessing a broad range of different functional aspects such as mobility, activities of daily living and impact on social and emotional function. One of these generic tools was developed specifically for paediatric patients. Four of the generic questionnaires focused on a specific symptom (pain, anxiety and depression, sleep, cognition). A further one that could not be located appeared to focus on fatigue. Four PROs were cancer specific and measured a wide range of symptoms or functional issues. Three PROs were disease specific and focused on neurological diseases, myeloma and lymphoma. Five studies either use PROs specific to the included patient population or state that the questionnaires had been validated in the stated patient population. None of the questionnaires used had been developed specifically to collect PRO data for patients receiving ACT.

Table 5 Review of psychometric properties of identified questionnaires using modified version of COSMIN checklist
Full size table

Given that none of the identified PROs had been developed specifically for ACT patients, we felt it was important to examine whether the PROs covered the experiences of this patient group. Two qualitative studies [29, 65] were identified which explored the QOL experiences of a total of 39 ACT patients. The issues identified in these studies were tabulated and then cross-referenced with the items covered in all the PROs included in this review. None of the included PROs covered all items identified in the two qualitative research studies (Table 6). The PRO-CTCAE had the best coverage of items, but there were still some areas that were not addressed. The majority of studies used multiple PROs in a single study. The quality of the included PROs was mixed, some were well validated whereas others had been developed specifically for the study and had not been subjected to any psychometric testing. All but one study [45] used at least one validated PRO. The timing of PRO administration varied across the studies, some were completed at a single time point only (n = 3) [40,41,42] whereas other studies included multiple time points. There was no consistency in the time points used, only one study collected PRO data at 7 days [38] and three collected it at 14 days [36, 37, 39].

Table 6 Item coverage in identified PROs cross-referenced with issues identified by at least 2 participants in a qualitative study exploring experiences of CAR-T [31]
Full size table

Four studies followed patients up for over a year [43,44,45, 47], with the longest follow-up period being 5 years [43]; a further four studies followed patients for approximately 3 months [36,37,38,39]. The completion rates for most studies were above 70%; three studies however had very low response rates (44%; 38%; 18%). The majority of studies do not provide details as to how the PRO was administered. The three studies where details were provided were administered online; one of these studies also had a paper option if required.

Although only two studies included a comparison arm [45], the majority of studies reported on whether there was a significant difference in their outcome measures. Only one study [39] reported a statistically significant difference in PRO responses. Sidana et al. reported that the CAR T-cell group experienced significantly less worsening in quality of life as measured by FACT-G than both autoSCT and alloSCT groups from baseline to each time point (week 2, months 1, 2 and 3) [39]. Five studies reported minimal clinically important differences in some elements of the PRO data [38, 40, 43, 44, 47].

Discussion

Eleven studies were identified in this review, the majority of which were conducted in the USA. A relatively low number of ACT studies were identified that collected PRO data. In comparison to the number of studies, a large number of PRO instruments were identified which highlights the need for further research to standardise assessment in this area. Measuring patient experience and patient-reported outcomes is crucial in the development of new treatments. PRO toxicity data has been reported to be more accurate than clinician-reported data [66, 67]. As expected given the focus of ACT clinical trials [68], the majority of studies only included patients with haematological cancer. Only one study [39] reported a statistically significant difference in PRO responses; the CAR T-cell group experienced significantly less worsening in QoL as measured by FACT-G than both stem cell transplant groups.

The studies included in this review have highlighted many methodological challenges to the use of PRO data in the ACT population. The wide range of PROs used make it difficult for any comparisons to be made across the data collected. As highlighted in other research, the majority of studies do not use the PRO as their primary outcome [69]. The majority of ACT trials are early phase with safety as a priority; therefore, investigators may be reluctant to include QoL as an outcome [23]. The study designs were also not methodologically robust, no RCTs were included and only two included a comparison arm. This is a problem unique to ACT as traditionally ACT studies would generally be tested in early phase trials only. RCTs are the gold standard in clinical trials, and RCT data would be needed to fully explore the impact of ACT on toxicities and quality of life. The type of patients included is also a concern as some of the studies only report results on the more well patients or have a significant dropout rate; therefore, the results may not be generalisable. Furthermore, the needs of underserved populations may not have been considered [70].

Choosing an appropriate PRO instrument is a crucial step when developing a trial. Ideally, a PRO should be valid, reliable, sensitive to change and be generalisable to the target patient population [71]. PROs can be generic or disease specific. Many of the cancer PROs aim to assess quality of life and key symptoms or toxicities. None of the studies identified in this review uses PROs designed specifically for the ACT population. Further research is required to understand the concepts that matter to patients undergoing ACT. In their qualitative study, Whisenant et al. [65] explored the symptom burden of CAR T-cell therapy. Participants reported experiencing 34 symptoms related to the disease and treatment; they also described how their symptoms interfered with their functioning in many different areas. In this review, we cross-referenced qualitative findings with the issues covered in the identified PROs and found that none of the PROs covered all the issues pertinent to this patient group. This is perhaps why many of the included studies used multiple questionnaires. There is a danger however of overburdening patients if they are expected to complete large numbers of questionnaires. More qualitative research is needed to further explore experience in a wider population of ACT patients. Qualitative findings can be used to inform the creation of new PROs where required.

The timing of PRO assessments is an important issue that needs to be considered [69]. Lasiter et al. suggest there are three distinct phases in PRO data collection: acute, sub-acute and long term; they suggest that timing of PRO assessments should vary within these phases, and different PROs may also be used in order to address the most pertinent issues at each time point [72]. The acute phase when patients are likely to experience toxicities is considered to be weeks 1–4, and it is recommended that PRO data should be collected at least once a week during this phase [73]. Some of the key toxicities such as CRS and ICANS are likely to occur 1–2 weeks after treatment. Only one of the included studies collected PRO data at 7 days, and three collected it at 14 days. The majority of studies therefore may not have collected data on the key toxicities patients may experience. It is important to monitor toxicities in new therapeutic areas as these toxicities could be predictors of worse complications in the future. One qualitative study [29] suggested that the majority of patient side effects had improved after 6 months. After this time point, the emphasis of collecting data may shift to more general QoL rather than PROs that collect information on symptoms.

The follow-up period varied across the included studies. Four studies followed patients up for over a year, with the longest follow-up period being 5 years; a further four studies followed patients for approximately 3 months. Long-term follow-up is important with a relatively new drug as data needs to be collected on long-term toxicities. Existing research has not explored the role of collecting of PRO data overtime [69]. There are practicality issues with following patients up for a long time however as their care may be transferred to other centres, and therefore, keeping track of patients and getting clinical teams to manage and take ownership of follow-up may be difficult [73]. Electronic patient-reported outcomes (ePROs) are becoming more common place and may make longer-term follow-up more feasible [46]; however, issues of digital inclusion must be considered [70]. There is also the issue of patient compliance. In some studies included in this review, compliance rates were very low. Whatever time points are selected, it is important to ensure that baseline data is collected as the patients in this population may have received several lines of treatment before their ACT, and as a result, their baseline data may be significantly lower than some patient populations.

Attempts have been made to make recommendations for the most suitable questionnaires to be used in the ACT population. In this review, the most commonly used PROs were the PROMIS-29 which was used in four of the identified studies and the EQ5D which was used in three studies; however, frequency of use should not be the main driver for future practice. Rather this should be informed by addressing concepts that matter to patients and other key stakeholders. PROMIS, FACT-G and PRO-CTCAE were recommended in one review as possible PROs to use in this patient population [73] PROMIS was recommended due to its high correlation with SF36, ease of comparison with general population and free availability. FACT-G was recommended due to the availability of historical data in different cancer subtypes and PROCTCAE was recommended as a suitable measure of toxicity [73]. The Centers for Medicare & Medicaid Services (CMS) panel have also made their own recommendations about the most appropriate tools to use (PROCTCAE [51], MD Anderson Symptom Inventory [60], EORTC-QLQ-C30 [62] and PROMIS [48]), all of which are flexible questionnaire systems that use item banks or a modular approach. It is important to consider the purpose of the PRO tool as PROs are designed to measure different things. Some PROs focus on HRQOL, whereas others focus on toxicities; therefore, different PROs may be required at different points of the disease trajectory.

Limitations

There are many methodological concerns with the studies identified in this review such as a lack of robust study designs and concerns about the patient population included; additionally, a wide range of PROs have been used across the studies. These issues make it difficult for any recommendations to be made about the appropriate PRO to be used in the ACT patient population. It was a concern that such a small number of papers were identified in the search. We did however work with information specialists to generate the search terms and also searched key authors and reference lists; therefore, we are confident that all relevant papers have been identified.

Conclusion

None of the PROs identified has been designed specifically for the ACT population, and none of them covered all the needs of this patient population. Appropriateness of existing instruments should be considered and if necessary a new tool developed. It should be considered whether it is appropriate to collect data more frequently in the acute stage and then less frequently for a considerable time during the follow-up in order to identify late effects and whether one tool is suitable at all time points or if the tool should be adapted depending on time since treatment. More research is needed to identify the exact timings of PRO assessments, and qualitative work with patients is needed to determine what are the most important issues for them throughout the treatment and follow-up trajectory.

Availability of data and materials

All data generated or analysed during this study are included in this published article. The protocol was not published but can be obtained from the authors if required.

Change history

References

  1. CAR T cells: engineering immune cells to treat cancer - NCI. Available from: https://www.cancer.gov/about-cancer/treatment/research/car-t-cells. [cited 2023 Jul 24].

  2. Hinrichs CS, Rosenberg SA. Exploiting the curative potential of adoptive T-cell therapy for cancer. Immunol Rev. 2014;257(1):56–71.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. The Association of the British Pharmaceutical Industry. Cell and gene therapy market data. 2016.

  4. Rohaan MW, Wilgenhof S, Haanen JBAG. Adoptive cellular therapies: the current landscape.

  5. Adoptive Cell Transfer Therapy - Melanoma Research Alliance. 

  6. CAR T-cell therapy and its side effects. 

  7. Shargian L, Raanani P, Yeshurun M, Gafter-Gvili A, Gurion R. Chimeric antigen receptor T-cell therapy is superior to standard of care as second-line therapy for large B-cell lymphoma: a systematic review and meta-analysis. Br J Haematol. 2022;198(5):838–46.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Mohty M, Gautier J, Malard F, Aljurf M, Bazarbachi A, Chabannon C, et al. CD19 chimeric antigen receptor-T cells in B-cell leukemia and lymphoma: current status and perspectives. Leukemia. 2019;33(12):2767–78.

    Article  PubMed  Google Scholar 

  9. Chakraborty R, Hill BT, Majeed A, Majhail NS. Late effects after chimeric antigen receptor T cell therapy for lymphoid malignancies. Transplant Cell Ther. 2021;27(3):222–9.

    Article  CAS  PubMed  Google Scholar 

  10. June CH, Sadelain M. Chimeric antigen receptor therapy. N Engl J Med. 2018;379(1):64–73.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Cordeiro A, Bezerra ED, Hirayama AV, Hill JA, Wu QV, Voutsinas J, et al. Late events after treatment with CD19-targeted chimeric antigen receptor modified T cells. Biol Blood Marrow Transplant. 2020;26(1):26–33.

    Article  CAS  PubMed  Google Scholar 

  12. Hossain NM, Nishimura MI. Late events after CD-19 CAR-T treatment. Biol Blood Marrow Transplant. 2020;26(1):e1-2.

    Article  PubMed  Google Scholar 

  13. Santomasso B, Bachier C, Westin J, Rezvani K, Shpall EJ. The other side of CAR T-cell therapy: cytokine release syndrome, neurologic toxicity, and financial burden. Am Soc Clin Oncol Educ book Am Soc Clin Oncol Annu Meet. 2019;39(39):433–44.

    Article  Google Scholar 

  14. Lee DW, Santomasso BD, Locke FL, Ghobadi A, Turtle CJ, Brudno JN, et al. ASTCT consensus grading for cytokine release syndrome and neurologic toxicity associated with immune effector cells. Biol Blood Marrow Transplant. 2019;25(4):625–38.

    Article  CAS  PubMed  Google Scholar 

  15. Kluetz PG, Kanapuru B, Lemery S, Johnson LL, Fiero MH, Arscott K, et al. Informing the tolerability of cancer treatments using patient-reported outcome measures: summary of an FDA and Critical Path Institute Workshop. Value Health. 2018;21(6):742–7.

    Article  PubMed  Google Scholar 

  16. Cruz Rivera S, McMullan C, Jones L, Kyte D, Slade A, Calvert M. The impact of patient-reported outcome data from clinical trials: perspectives from international stakeholders. J Patient-Reported Outcomes. 2020;4(1):1–14.

    Article  Google Scholar 

  17. Retzer A, Aiyegbusi OL, Rowe A, Newsome PN, Douglas-Pugh J, Khan S, et al. The value of patient-reported outcomes in early-phase clinical trials. Nat Me. 2022;28(1):18–20.

    Article  CAS  Google Scholar 

  18. Kluetz PG, O’Connor DJ, Soltys K. Incorporating the patient experience into regulatory decision making in the USA, Europe, and Canada. Lancet Oncol. 2018;19(5):e267-74.

    Article  PubMed  Google Scholar 

  19. FDA. Core patient-reported outcomes in cancer clinical trials | FDA.

  20. FDA patient-focused drug development guidance series for enhancing the incorporation of the patient’s voice in medical product development and regulatory decision making | FDA.

  21. FDA. Patient-reported outcome measures: use in medical product development to support labeling claims | FDA. 2009.

  22. Medicines Agency E. Committee for Medicinal Products for Human Use (CHMP) Appendix 2 to the guideline on the evaluation of anticancer medicinal products in man The use of patient-reported outcome (PRO) measures in oncology studies. 2016.

  23. Raymakers AJN, Regier DA, Peacock SJ, Freeman CL. Health-related quality of life data collected in chimeric antigen receptor T-cell (CAR-T) therapy clinical trials. J Cancer Policy. 2021;30: 100304.

    Article  PubMed  Google Scholar 

  24. Messina AJ, Andrianov V, Mazzolenis D, Vidal-Fisher L. Emerging trends and utilization of patient-reported outcomes (PROs) in clinical trials of chimeric antigen receptor (CAR) T-cell therapies. 2020 May;38(15_suppl):e19142–e19142.

  25. Messina AJ, Andrianov V, Mazzolenis D, Vidal-Fisher L. Emerging trends and utilization of patient-reported outcomes (PROs) in clinical trials of chimeric antigen receptor (CAR) T-cell therapies. 2020 May 25;38(15_suppl):e19142–e19142.

  26. Shah KK, Bennett B, Lenny A, Longworth L, Brazier JE, Oppe M, et al. Adapting preference-based utility measures to capture the impact of cancer treatment-related symptoms. Eur J Health Econ. 2021;22(8):1301–9.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Velikova G, Absolom K, Hewison J, Holch P, Warrington L, Avery K, et al. Electronic self-reporting of adverse events for patients undergoing cancer treatment: the eRAPID research programme including two RCTs. Program Grants Appl Res. 2022;10(1):1–110.

    Article  Google Scholar 

  28. Teisberg E, Wallace S, O’Hara S. Defining and implementing value-based health care: a strategic framework. Acad Med. 2020;95(5):682–5.

    Article  PubMed  Google Scholar 

  29. Cheng Kayla Scippa Frederick Locke Julia Thornton Snider Heather Jim RL. Patient perspectives on health-related quality of life in diffuse large B-cell lymphoma treated with Car T-cell therapy: A Qualitative Study.

  30. Jenei K, Burgess M, Peacock S, Raymakers AJN. Experiences and perspectives of individuals accessing CAR-T cell therapy: a qualitative analysis of online Reddit discussions. J Cancer Policy. 2021;30:100303.

    Article  PubMed  Google Scholar 

  31. Whisenant MS, Srour SA, Williams LA, Subbiah I, Griffin D, Ponce D, et al. The Unique symptom burden of patients receiving CAR T-cell therapy. Semin Oncol Nurs. 2021;37(6): 151216.

    Article  PubMed  Google Scholar 

  32. Ouzzani M, Hammady H, Fedorowicz Z, Elmagarmid A. Rayyan-a web and mobile app for systematic reviews. Syst Rev. 2016;5(1). 

  33. Prinsen CAC, Mokkink LB, Bouter LM, Alonso J, Patrick DL, de Vet HCW, et al. COSMIN guideline for systematic reviews of patient-reported outcome measures. Qual Life Res. 2018;27(5):1147–57.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Higgins JP, Altman DG, Sterne JA, Wiley J. Chapter 8: Assessing risk of bias in included studies. 2017;

  35. Revenson TA, Temple LK, McClelland SI. Improving sexual function in female cancer survivors: a systematic review of psychosocial interventions. 2010;28(15_suppl):e19522–e19522.

  36. Hoogland AI, Jayani RV, Collier A, Irizarry-Arroyo N, Rodriguez Y, Jain MD, et al. Acute patient-reported outcomes in B-cell malignancies treated with axicabtagene ciloleucel. Cancer Med. 2021;10(6):1936–43.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Knight JM, Arapi I, Szabo A, Yim S, Sauber G, Hillard C, et al. Quality of life, tryptophan metabolites, and neurotoxicity assessments of patients with relapsed or refractory B cell malignancies undergoing CAR 20/19 - T cell therapy. Blood. 2020;136(Supplement 1):42–3.

    Article  Google Scholar 

  38. Martin T, Lin Y, Agha M, Cohen AD, Htut M, Stewart AK, et al. Health-related quality of life in the Cartitude-1 Study of Ciltacabtagene Autoleucel for relapsed/refractory multiple myeloma. Blood. 2020;136(Supplement 1):41–2.

    Article  Google Scholar 

  39. Sidana S, Thanarajasingam G, Griffin J, Thompson CA, Burtis M, Warsame R, et al. Patient experience of chimeric antigen receptor (CAR)-T cell therapy vs. stem cell transplant: longitudinal patient reported adverse events, cognition and quality of life. Blood. 2019;134(1):794–794.

    Article  Google Scholar 

  40. Mullane E, Jones T, Voutsinas J, Wu QV, Loggers E, Fann J, et al. Patient-reported outcomes at time of CAR-T cell therapy. Blood. 2020;136(Supplement 1):35–6.

    Article  Google Scholar 

  41. Ruark J, Mullane E, Cleary N, Cordeiro A, Bezerra ED, Wu V, et al. HHS Public Access. 2021;26(1):34–43.

  42. Wang XS, Srour SA, Whisenant M, Subbiah IM, Chen TH, Ponce D, et al. Patient-reported symptom and functioning status during the first 12 months after chimeric antigen receptor T cell therapy for hematologic malignancies. Transplant Cell Ther. 2021;27(11):930.e1-930.e10.

    Article  CAS  PubMed  Google Scholar 

  43. Laetsch TW, Myers GD, Baruchel A, Dietz AC, Pulsipher MA, Bittencourt H, et al. Patient-reported quality of life after tisagenlecleucel infusion in children and young adults with relapsed or refractory B-cell acute lymphoblastic leukaemia: a global, single-arm, phase 2 trial. Lancet Oncol. 2019;20(12):1710–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Maziarz RT, Waller EK, Jaeger U, Fleury I, McGuirk J, Holte H, et al. Patient-reported long-term quality of life after tisagenlecleucel in relapsed/refractory diffuse large B-cell lymphoma. Blood Adv. 2020;4(4):629–37.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Li H, Huang L, Liu L, Wang X, Zhang Z, Yue D, et al. Selective effect of cytokine-induced killer cells on survival of patients with early-stage melanoma. Cancer Immunol Immunother. 2017;66(3):299–308.

    Article  CAS  PubMed  Google Scholar 

  46. Banerjee R, Shah N, Dicker AP. Next-generation implementation of chimeric antigen receptor T-cell therapy using Digital Health. JCO Clin Cancer Inform. 2021;5:668–78.

    Article  PubMed  Google Scholar 

  47. Shah N, et al. Secondary quality-of-life domains in patients with relapsed and refractory multiple Myeloma treated with the Bcma-Directed CAR T cell therapy Idecabtagene Vicleucel (ide-cel; bb2121): results from the Karmma clinical trial. Blood. 2020;136(1):28–9. https://doi.org/10.1182/BLOOD-2020-136665.

  48. Hays RD, Spritzer KL, Schalet BD, Cella D. PROMIS ®-29 v2.0 Profile Physical and Mental Health Summary Scores HHS Public Access. Qual Life Res. 2018;27(7):1885–91.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Balestroni G, Bertolotti G. EuroQol-5D (EQ-5D): an instrument for measuring quality of life. Monaldi Arch Chest Dis. 2012;78(3):155–9.

    PubMed  Google Scholar 

  50. Brazier JE, Harper R, Jones NMB, O’Cathain A, Thomas KJ, Usherwood T, et al. Validating the SF-36 health survey questionnaire: new outcome measure for primary care. BMJ Br Med J. 1992;305(6846):160.

    Article  CAS  Google Scholar 

  51. Dueck AC, Mendoza TR, Mitchell SA, Reeve BB, Castro KM, Rogak LJ, et al. Validity and reliability of the US National Cancer Institute’s Patient-Reported Outcomes Version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE). JAMA Oncol. 2015;1(8):1051–9.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Watson D, O’Hara MW, Simms LJ, Kotov R, Chmielewski M, McDade-Montez EA, et al. Development and validation of the Inventory of Depression and Anxiety Symptoms (IDAS). Psychol Assess. 2007;19(3):253–68.

    Article  PubMed  Google Scholar 

  53. Cleeland C, Ryan K. Pain assessment: global use of the Brief Pain Inventory - PubMed. Ann Acad Med Singapore. 1994;23(2):129–38.

    CAS  PubMed  Google Scholar 

  54. Buysse DJ, Reynolds CF, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh sleep quality index: a new instrument for psychiatric practice and research. Psychiatry Res. 1989;28(2):193–213.

    Article  CAS  PubMed  Google Scholar 

  55. 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 Ins. 1993;85(5):365–76.

    Article  CAS  Google Scholar 

  56. Herdman M, Gudex C, Lloyd A, Janssen M, Kind P, Parkin D, et al. Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Qual Life Res. 2011;20(10):1727–36.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Rabin R, De Charro F. EQ-5D: a measure of health status from the EuroQol Group. Ann Med. 2001;33(5):337–43.

    Article  CAS  PubMed  Google Scholar 

  58. Wille N, Badia X, Bonsel G, Burström K, Cavrini G, Devlin N, et al. Development of the EQ-5D-Y: a child-friendly version of the EQ-5D. Qual Life Res. 2010;19(6):875–86.

    Article  PubMed  PubMed Central  Google Scholar 

  59. Hays RD, Bjorner JB, Revicki DA, Spritzer KL, Cella D. Development of physical and mental health summary scores from the Patient-Reported Outcomes Measurement Information System (PROMIS) global items. Qual Life Res. 2009;18(7):873–80.

    Article  PubMed  PubMed Central  Google Scholar 

  60. Cleeland CS, Mendoza TR, Shelley Wang X, Chou C, Margaret Harle RT, Marilyn Morrissey R, et al. Assessing symptom distress in cancer patients. Cancer. 2000;89(7):1634–46.

    Article  CAS  PubMed  Google Scholar 

  61. Alderfer MA, Marsac ML. Pediatric Quality of Life Inventory (PedsQL). Encycl Behav Med. 2013;1448–9. 

  62. Cella D, Tulsky D, Gray G, Sarafian B, … ELJC, 1993 undefined. The Functional Assessment of Cancer Therapy scale: development and validation of the general measure. researchgate.net. 1993.

  63. Gershon RC, Lai JS, Bode R, Choi S, Moy C, Bleck T, et al. Neuro-QOL: quality of life item banks for adults with neurological disorders: item development and calibrations based upon clinical and general population testing. Qual Life Res. 2012;21(3):475–86.

    Article  PubMed  Google Scholar 

  64. Hlubocky FJ, Webster K, Cashy J, Beaumont J, Cella D. The development and validation of a measure of health-related quality of life for non-Hodgkin’s lymphoma: the Functional Assessment of Cancer Therapy—Lymphoma (FACT-Lym). Lymphoma. 2013;20(2013):1–9.

    Article  Google Scholar 

  65. Whisenant MS, Srour SA, Williams LA, Subbiah I, Griffin D, Ponce D, et al. The unique symptom burden of patients receiving CAR T-cell therapy. Semin Oncol Nurs. 2021;37(6):151216.

    Article  PubMed  Google Scholar 

  66. Atkinson TM, Li Y, Coffey CW, Sit L, Shaw M, Lavene D, et al. Reliability of adverse symptom event reporting by clinicians. Qual Life Res. 2012;21(7):1159–64.

    Article  PubMed  Google Scholar 

  67. Di Maio M, Basch E, Bryce J, Perrone F. Patient-reported outcomes in the evaluation of toxicity of anticancer treatments. Nat Rev Clin Oncol. 2016;13(5):319–25.

    Article  PubMed  Google Scholar 

  68. Mohanty R, Chowdhury CR, Arega S, Sen P, Ganguly P, Ganguly N. CAR T cell therapy: a new era for cancer treatment (review). Oncol Rep. 2019;42(6):2183–95.

    CAS  PubMed  Google Scholar 

  69. Kamal M, Joseph J, Greenbaum U, Hicklen R, Kebriaei P, Srour SA, et al. Patient-reported outcomes for cancer patients with hematological malignancies undergoing chimeric antigen receptor T cell therapy: a systematic review. Transplant Cell Ther. 2021;27(5):390.e1-390.e7.

    Article  CAS  PubMed  Google Scholar 

  70. Calvert M, Cruz Rivera S, Retzer A, Hughes S, Campbell L, Molony-Oates B, et al. Patient reported outcome assessment must be inclusive and equitable. Nature. 2022;28(6):1120–4.

    CAS  Google Scholar 

  71. Weldring T, Smith SMS. Patient-reported outcomes (pROs) and patient-reported outcome measures (pROMs). Health Serv Insights. 2013;6:61–8.

    PubMed  PubMed Central  Google Scholar 

  72. Lasiter L, Campbell A, Basch E, Hudgens S, Stewart M, Wu JJ, et al. Use of patient-reported outcomes to understand & measure the patient experience of novel cell and gene therapies. Ther Innov Regul Sci. 2020;54(6):1566–75.

    Article  PubMed  Google Scholar 

  73. Chakraborty R, Sidana S, Shah GL, Scordo M, Hamilton BK, Majhail NS. Patient-reported outcomes with chimeric antigen receptor T cell therapy: challenges and opportunities. Biol Blood Marrow Transplant. 2019;25(5):e155–62.

    Article  PubMed  Google Scholar 

Download references

Funding

This work was supported by iMATCH (innovate Manchester Advanced Therapy Centre Hub) and funded by UKRI (InnovateUK) grant number: 107500 MC, OLA and FT disclosed receipt of the following financial support for the research, authorship and/or publication of this article. This work was supported by the Midlands-Wales Advanced Therapies Treatment Centre (MW-ATTC) programme grant from Innovate UK to a consortium of partners including Health Technology Wales, the Welsh Blood Service and the University of Birmingham (Grant number: IUK: 104232) and Innovate UK (part of UK Research and Innovation) grant patient-reported outcomes assessment to support accelerated access to advanced cell and gene therapies: PROmics (Grant No: IUK: 104777). The funder was not involved in any aspect of the research work.

Author information

Authors and Affiliations

  1. Christie Patient Centred Research, The Christie NHS Foundation Trust, Wilmslow Road, Manchester, M204BX, UK

    Sally Taylor, Kate Law, Jake Coomber-Moore & Janelle Yorke

  2. School of Nursing and Midwifery, The University of Manchester, Oxford Road, Manchester, M13 9PL, UK

    Sally Taylor, Kate Law & Janelle Yorke

  3. The Christie NHS Foundation Trust, Wilmslow Road, Manchester, M204BX, UK

    Michelle Davies & Fiona Thistlethwaite

  4. The University of Manchester, Oxford Road, Manchester, M13 9PL, UK

    Michelle Davies & Fiona Thistlethwaite

  5. Centre for Patient Reported Outcome Research (CPROR), Institute of Applied Health Research, University of Birmingham, Birmingham, UK

    Mel Calvert & Olalekan Aiyegbusi

  6. National Institute for Health Research (NIHR) Applied Research Centre (ARC) West Midlands, Birmingham, UK

    Mel Calvert & Olalekan Aiyegbusi

  7. Birmingham Health Partners Centre for Regulatory Science and Innovation, University of Birmingham, Birmingham, UK

    Mel Calvert & Olalekan Aiyegbusi

  8. National Institute for Health Research (NIHR) Birmingham Biomedical Research Centre, Birmingham, UK

    Mel Calvert & Olalekan Aiyegbusi

  9. Surgical Reconstruction and Microbiology Research Centre, National Institute for Health Research (NIHR), University of Birmingham, Birmingham, UK

    Mel Calvert

  10. Midlands Health Data Research UK, Birmingham, UK

    Mel Calvert

  11. DEMAND Hub, University of Birmingham, Birmingham, UK

    Mel Calvert

Authors
  1. Sally Taylor
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kate Law
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jake Coomber-Moore
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Michelle Davies
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Fiona Thistlethwaite
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Mel Calvert
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Olalekan Aiyegbusi
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Janelle Yorke
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

ST, MD, FT, JY, MC and OL wrote the protocol for the review. ST led the searches and data extraction with support from KM and JCM. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Sally Taylor.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

M. C. is a National Institute for Health Research (NIHR) Senior Investigator and receives funding from the National Institute for Health Research (NIHR) Birmingham Biomedical Research Centre, the NIHR Surgical Reconstruction and Microbiology Research Centre and NIHR ARC West Midlands at the University of Birmingham and University Hospitals Birmingham NHS Foundation Trust, Health Data Research UK, UKRI, Macmillan Cancer Support, UCB Pharma, Gilead, Janssen and GSK. M. C. has received personal fees from Astellas, Aparito Ltd., CIS Oncology, Takeda, Merck, Daiichi Sankyo, Glaukos, GSK and the Patient-Centered Outcomes Research Institute (PCORI) outside the submitted work. OLA receives funding from the NIHR Birmingham Biomedical Research Centre (BRC), NIHR Applied Research Collaboration (ARC), West Midlands at the University of Birmingham and University Hospitals Birmingham NHS Foundation, Innovate UK (part of UK Research and Innovation), Gilead Sciences Ltd., Janssen Pharmaceuticals, Inc., GSK and Sarcoma UK. OLA declares personal fees from Gilead Sciences Ltd., GlaxoSmithKline (GSK) and Merck outside the submitted work. The views expressed are those of the authors and not necessarily those of the NIHR, the Department of Health and Social Care or UKRI. The remaining authors declare that they have no competing interests.

Additional information

Publisher’s Note

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

The original online version of this article was revised: there was an error in the author name ‘Fiona Thistlewaite’ which should have been ‘Fiona Thistlethwaite’.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Taylor, S., Law, K., Coomber-Moore, J. et al. Patient-reported outcome (PRO) instruments used in patients undergoing adoptive cell therapy (ACT) for the treatment of cancer: a systematic review. Syst Rev 12, 183 (2023). https://doi.org/10.1186/s13643-023-02337-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s13643-023-02337-8

Keywords

Systematic Reviews

ISSN: 2046-4053