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. 2025 Aug 6;5:104380. doi: 10.1016/j.bas.2025.104380

Outcome measurements in patients with a lumbar disc herniation – a scoping review

N Gabrovsky a, M Petrov a,, Y Kotceva a, Y Petrova b
PMCID: PMC12356021  PMID: 40822263

Abstract

Introduction

Outcome measurement is a cornerstone of modern medicine. A range of tools are commonly used for outcome assessment in lumbar disc herniation (LDH) treatment.

Research question

What are the outcome measurement tools (OMTs) that have been used in the randomized controlled trials (RCTs) for LDH for the last 25 years?

Material and methods

The search covered only RCT of adult patients with LDH for the period January 01, 2000–December 31, 2024. Two authors reviewed independently the RCTs’ relevance to the topic of our scoping review. The reviewed and selected RCTs were analyzed, and relevant data was extracted, standardized and classified.

Results

We identified 168 RCTs and 29 outcome measurement tools covering 6 main domains: pain measurement – 6 tools, disability – 4 tools, quality of life – 2 tools, clinical parameters – 9 tools, psychological facet – 3 tools and self-perceived recovery – 5 tools. The number of tools used per RCT was most frequently 3 (26.2 %) or 4 (21.4 %).

Discussion and conclusion

Measuring outcome in patients with LDH is a complex and multidimensional task. The RCTs involving surgical treatment usually applied tools from 4 domains: pain, disability, clinical parameters and QOL. The most frequently used tools for the different domains were respectively: VAS, ODI, a mixture of clinical parameters and SF-36/12. A new group of outcome measuring tools based on computer adapted tests, wearable devices and digital outcome measures are on the horizon trying to impose new standards but their application needs further investigation.

Keywords: Lumbar disc herniation, Outcome measurement tools, Outcome measurement

Highlights

  • Search only RCT of adult patients with LDH for the period January 01, 2000–December 31, 2024

  • Extract, analyze and group outcome measurement tools used in these RCT in domains.

  • Identify the most frequently used OMT for the different domains.

1. Introduction

Outcome measurement is a cornerstone of modern medicine, serving as the foundation for evaluating the effectiveness of treatment, improving patient care, and advancing healthcare quality. A plethora of therapeutic options and opinions exist among medical specialties for the treatment of low back pain and lumbar disk herniation (LDH). A standardized approach to measuring patient outcome plays crucial role to provide clearer insights into treatment's effectiveness.

An extensive range of tools are commonly used for outcome assessment in LDH treatment. These tools measure various domains of outcome such as pain, disability, quality of life, psychological and clinical status. They provide a comprehensive multi-dimensional picture of the treatment's impact on the patient's daily life. The objective of our scoping review is to analyze the outcome measurement tools (OMT) that have been used most frequently in the randomized controlled trials (RCT) for LDH for the last 25 years.

2. Material and methods

We conducted our scoping review following the steps described in the PRISMA extension for scoping reviews published in 2018 (PRISMA-ScR) (Tricco et al., 2018). The research question of this scoping review was which outcome measurement tools (OMTs) have been most frequently used in the randomized controlled trials (RCTs) for LDH for the last 25 years. Our goal was to assess which are the most used tools, to systematize them depending on the domain that they examine and to analyze which are the most used combinations of domain and tools to assess the outcome in adult patients with a lumbar disc herniation.

The second step was identifying RCT that should be included in the scoping review. Medline Ultimate Database was searched via EBSCOhost Research Database and Cochrane Library to identify all randomized controlled trials related to the search terms “lumbar disc herniation”, “randomized controlled trial” and “outcome or outcome measurement”. The search covered a period of 25 years (January 01, 2000–December 31, 2024) and included only RCT of adult patients with LDH. The search algorithm was: “lumbar disc herniation” AND “outcome or outcome measurement”; Limiters - Publication Date: 20000101–20241231; Human; Age Related: All Adult: 19+ years; Publication Type: Randomized Controlled Trial; Expanders - Apply equivalent subjects; Search modes - Boolean/Phrase. To sum up, the main inclusion criteria were “randomized controlled trial”, “lumbar disc herniation” and “outcome measurement” in adult patients, for the aforementioned time period.

Next step was review of relevance of the studies to the topic of the current scoping review. Two authors reviewed independently the relevance of the RCTs to the topic of our study. In case of disagreement between them, a discussion and analyses were performed until achieving scientific consensus (Fig. 1). The reviewed and selected RCTs were analyzed in depth and the relevant data was extracted, standardized and classified in MS Excel spreadsheets with the following fields: year of the study; number of patients involved; type of treatment – surgical (microdiscectomy or endoscopy) or non-surgical (minimally invasive procedures like periradicular injections, denervation etc., medications, physiotherapy); outcome measurement tools used. All RCTs with a cohort of less than 50 patients were excluded from the final analysis as well as all the OMTs that have been used less than 3 times. Finally, the remaining OMTs have been categorized into groups based on the main domain of outcome that they examine - pain, disability, quality of life (QOL), clinical, psychological and self-perceived recovery (SPR). After including all the data into a single chart, the remaining OMT have been analyzed and summarized.

Fig. 1.

Fig. 1

A simplified algorithm of the scoping review that we have conducted about OMT in RCTs of adult patients with LDH for the period January 01, 2000–December 31, 2024.

3. Results

Following the described search strategy, we identified 421 articles as potential candidates for our scoping review. After the review of relevance by the two independent authors 206 RCT have been selected as relevant to the main topic – outcome measurement in patients with LDH. From these 206 RCTs some enrolled more than 1000 patients and some less than 30. In our scoping review we included only RCT that enrolled more than 50 patients. Therefore, 37 RCTs were excluded. The remaining 168 RCTs were considered eligible and have been analyzed in depth and the relevant data – extracted. From the 168 RCTs, 85 RCTs evaluated surgical treatment, 111 evaluated non-surgical treatment and 28 – a combination of surgical and non-surgical treatment.

A total of 55 different outcome measurement tools have been used. Twenty-six of them have been applied in only 1 or 2 RCTs. These OMT have not established themselves and have not become generally accepted for a quarter of a century, so we deemed it reasonable to exclude them from the current scoping review which is mainly based on the frequency of use of the OMTs. – see Table 1.

Table 1.

Number of RCT and OMT after conducting different stages of our scoping review.

№ randomized studies № OM tools
All 421
relevant 206 67
Relevant AND >50 169 55
After exclusion of tools used in less than 3 RCTs 168 29

Final analysis was performed on 168 RCTs and 29 outcome measurement tools that met all our criteria. All 29 OMTs are listed in alphabetic order and shortly described in Table 2.

Table 2.

List of all 29 OMTs listed in alphabetic order. Abbreviation, full name, description, domain and number of applications in the selected 168 RCTs.

abbreviation full name description domain applications
BDQ Beck Depression Questionnaire/Inventory A 21-item, self-report rating inventory that measures characteristic attitudes and symptoms of depression. psychological 3 (0.5 %)
CLI Clinical Objective outcome measures as neurological status, instrumental measuring/goniometer, femoral stretch test, dual inclinometer, Schober's test/, EMG, Physical fitness-physical training, body endurance tests, MMT, quantitative sensory testing. clinical 30 (5.5 %)
Drugs Medications Pain-related drug use – pre- and postoperative drug use. clinical 20 (3.6 %)
EQ-5D EuroQol-5D-5L A standardized instrument with 5 dimensions used to measure health-related quality of life. QOL 12 (2.2 %)
FABQ Fear Avoidance Beliefs Questionnaire A 16-item self-reported tool that assesses a person's fear-avoidance beliefs about physical activity and work. psychological 4 (0.7 %)
GPE Global Perceived Effect Patient-reported outcome measure used to assess a person's perceived change in health status over time. self-percieved recovery 4 (0.7 %)
HFAQ Hannover Functional Ability Questionnaire Self-administered questionnaires for the assessment of functional limitations in activities of daily living. disabilty 3 (0.5 %)
InOp Intraoperative Values Objective intraoperative measures that include operation time, blood loss, intraoperative fluoroscopy, time under general/epidural anesthesia. clinical 22 (4.0 %)
JOA score Japanese Orthopedic Association score Clinical evaluation tool used to assess functional status and outcomes in patients with spinal disorders clinical 13 (2.4 %)
LBP-RS Lower Back Pain Rating scale An index scale which includes measurements of pain intensity, disability and physical impairment. pain 5 (0.9 %)
LiSc Likert Scale with 7 or 10 positions psychometric scale measuring the degree to which a respondent agrees or disagrees with a given statement, or their feelings about a particular topic. self-percieved recovery 8 (1.5 %)
McNC MacNab Criteria A set of subjective measures used to evaluate the outcome, classifying patients based on pain relief and functional improvement into four categories, from excellent to poor. self-percieved recovery 11 (2.0 %)
MPQ RS McGill Pain Questionnaire Rating Scale Questionnaire used for standart registration and evaluation of the complaints of pain in a patient. pain 8 (1.5 %)
MST Modified Schober test Objective test to determine if there is a decrease in lumbar spine range of motion (flexion). clinical 5 (0.9 %)
NASS North American Spine Society Outcome Questionnaire A patient-reported outcome measures used to evaluate the impact of spinal disorders on a patient's health and quality of life self-percieved recovery 3 (0.5 %)
NRS Numerical Rating Scale A tool to measure the intensity of symptoms, most commonly pain. pain 24 (4.4 %)
ODI Oswestry Disability Index A validated questionnaire designed to measure the degree of disability or functional impairment caused by low back pain. disabilty 102 (18.5 %)
PPI Present Pain Intensity A tool for assessing pain severity. pain 3 (0.5 %)
PPT Pressure Pain Threshold A tool measuring deep muscular tissue sensitivity. The test determines the minimum amount of pressure that induces pain. clinical 3 (0.5 %)
PSc Prolo scale A two questions Likert-type scales evaluating the functional and the economic status of the patient. disabilty 3 (0.5 %)
PSI Patient Satisfaction Index A consumer experience metric that represents the satisfaction levels of patients with the overall healthcare experience. self-percieved recovery 3 (0.5 %)
RMDQ Roland-Morris Disability Questionnaire A 24-item self-report measure used to assess pain-related disability caused by lower back pain. disabilty 21 (3.8 %)
ROM Range of motion Measurement of the distance and direction a joint can move between its fully extended and fully flexed positions. clinical 6 (1.1 %)
SBI Sciatica Bothersomeness Index A tool used to assess the severity and impact of symptoms associated with sciatica. pain 5 (0.9 %)
SF-36/12 36/12 Item Short-form Survey Short Form-36 Health Survey is a questionnaire designed to assess health-related quality of life across 8 domains. SF-12 is the abbreviated version of SF-36 HRQoL QOL 42 (7.6 %)
SLR test Straight Leg Raise test Also called the Lasegue test - a fundamental maneuver during the physical examination of a patient with lower back pain. clinical 17 (3.1 %)
SOM Secondary Outcome Measures Additional objective postoperative outcome measures as: recurrences and reoperation; complication rate; time to return to work; length of hospital stay; return to daily activities. clinical 52 (9.5 %)
TSK Tampa Scale for Kinesiophobia a self-report questionnaire that is used to assess an individual's fear of movement or re-injury. psychological 4 (0.7 %)
VAS Visual Analogue Scale Rating scale used to measure the intensity or frequency of various symptoms. pain 114 (20.7 %)
Total 29 tools 550 (100 %)

We identified 6 main domains that were analyzed and covered by the OMT: pain, disability, quality of life (QOL), clinical, psychological and self-perceived recovery (SPR).

The distribution of the 29 remaining OMT across the different domains was as follow: pain measurement – 6 tools (LBP-RS, MPQ RS, NRS, PPI, SBI, VAS), disability – 4 tools (HFAQ, ODI, PSc, RMDQ), quality of life (QOL) assessment – 2 tools (EQ-5D, SF-36/12), self-perceived recovery – 5 tools (GPE, LiSc, McNC, NASS, PSI) and clinical parameters – 9 tools (CLI, drugs, InOp, JOA score, MST, PPT, ROM, SLR test, SOM), psychological facet – 3 tools (BDQ, FABQ, TSK) - see Table 2. Usually, the OMT are divided in 2 categories – subjective and objective measurement tools (Mobbs, 2021b). There is not a gradual distribution of the OMTs on the subjectivity spectrum and most are allocated to the extremes – either highly subjective (for instance purely based on patient-reported data) or strictly objective tools (measured by a specific instrument or device). This usual distribution of OMT in only two categories lead our team to look into the matter and try to allocate those tools in more domains because this simple bimodal distribution gives the reader no information about the real purpose of the OMTs.

3.1. Pain assessment

According to our scoping review, the most used pain assessment tools are VAS – applied in 20.7 % of the RCTs and NRS – 4.4 % of the RCTs.

The VAS is by far the most frequently used instrument for measuring pain intensity. This scale is focused on measuring the subjective experience of pain. Studies have shown it is widely recognized for its sensitivity and ease of use. They have demonstrated its effectiveness in capturing changes in pain levels over time, making it a valuable tool for monitoring treatment outcomes in LDH (Alodaibi et al., 2013; Chiarotto et al., 2017).

The NRS is often favored for its simplicity and possibility for conducting a verbal interview without a personal contact with the patient. This makes it particularly suitable for clinical environments where time is of the essence or studies are conducted in scarcely populated areas where large geographical areas are covered. Studies have shown that the NRS can yield results that are comparable to those obtained from the VAS. Many patients express a preference for the NRS due to its straightforward numerical format (Firdous et al., 2020; Shafshak and Elnemr, 2020). However, some research indicates that the NRS may not capture the full spectrum of pain intensity as effectively as the VAS, particularly in cases of severe pain (Saltychev et al., 2016). Both scales have demonstrated good reliability and validity in various populations, including those with chronic pain conditions (Hjermstad et al., 2011; Modarresi et al., 2021).

Following the results of the current scoping review VAS was the most frequently used pain measuring tool.

3.2. Disability

Functional disability assessment evaluates the extent to which the disease impairs daily activities, such as walking, lifting, sitting. In our scoping review, the most frequently used tool for measuring disability was ODI – applied in 18.5 % of the RCTs, followed by RMDQ – applied in 3.8 % of the RCTs.

ODI is one of the most studied and clinically proven tools for measuring disability validated in 14 languages (Aithala, 2015; Chiarotto et al., 2017; Papuga et al., 2015). ODI is a questionnaire consisting of ten items with 6 questions each. It evaluates the degree of disability experienced by individuals and assesses various aspects of daily living, including personal care, lifting, walking, sitting, standing, sleeping, social life, and traveling. It demonstrates consistently high reliability, good construct validity and high responsiveness (Chiarotto et al., 2017; Roland and Fairbank, 2000).

The RMDQ comprises 24 items that assess disability through a simple yes/no format, rating the patient's perception and associated disability. Fifteen of the items are related to physical activity, 3 – to sleep and rest, 2 – to psychological perceptions, 2 – to household management, 1 – to eating and 1 – to pain frequency (Chiarotto et al., 2017; Roland and Fairbank, 2000; Stevens et al., 2016).

Both the ODI and the RMDQ have demonstrated good reliability and validity in various populations. The RMDQ also exhibits strong psychometric properties, with studies indicating significant correlations with the ODI, suggesting that both tools effectively measure similar constructs of disability (Chiarotto et al., 2017; Chung et al., 2013; Stevens et al., 2016). The RMDQ may be better suited to settings in which patients have mild to moderate disability and the ODI to situations in which patients may have persistent severe disability (Roland and Fairbank, 2000).

Following the results of the current scoping review ODI was the most frequently used disability measuring tool.

3.3. Quality of life

Measuring quality of life could give physicians a broader perspective on the recovery of patients with LDH. In our scoping review, the most used QOL assessment tools were SF-36/12 – applied in 7.6 % of the RCTs followed by EQ-5D – 2.2 % of the RCTs.

The SF-36 is one of the most popular tools to assess health-related quality of life. It is a generic, patient-reported questionnaire with 36 items. It is designed to evaluate eight dimensions of health (physical functioning, bodily pain, limitations due to physical health problems, limitations due to personal or emotional problems, general mental health, social functioning, energy/fatigue, and general health perceptions), capturing both physical and mental well-being. SF-36 has demonstrated high responsiveness to changes in health status of patients (Du et al., 2023; Farzanegan et al., 2011). Regarding that SF-36 is generic health-related QOL tool it has been critisized for poorer responsiveness in LDH patients compared with other scales (Yao et al., 2020). However, as a generic instrument it permits comparisons across groups with and without LDH (Hoffman and Dukes, 2008).

SF-12 derived from the SF-36 and represents a shorter, 12-item questionnaire that captures enough data to estimate physical and mental well-being but does not provide scores for individual domains. SF-12 has the advantage to be easier and faster (Lin et al., 2020).

EQ-5D is a generic, patient-reported questionnaire designed to evaluate five dimensions: mobility, self-care, usual activities, pain/discomfort and anxiety/depression. Each dimension has 5 levels: no problems, slight problems, moderate problems, severe problems and extreme problems (https://euroqol.org).

Following the results of the current scoping review SF-36 and SF-12 were the most frequently used QOL measuring tools.

3.4. Self-perceived recovery

The more complex outcome studies include OMTs for self-perceived recovery. In our scoping review, the most used SPR tools was the MacNab Criteria– applied in 2.0 % of the RCTs followed by Likert Scale – 1.5 % of the RCTs.

Self-perceived recovery in spinal surgery refers to a patient's subjective assessment of their recovery following a spinal procedure. It is an important outcome measure because it reflects the patient's personal experience and satisfaction with the results of the surgery.

Some studies have shown that a mismatch between the surgeon's perspective (“successful surgery”) and the patient's perspective (“not-so-successful surgery”) may appear in up to 24 % of patients (Schwartz et al., 2015). The notions of “Response Shift”, “Minimal Important Difference” (Finkelstein and Schwartz, 2019) and “Minimal clinically important differences” (Cook, 2008) are rising more and more interest and attention.

Following the results of the current scoping review the most frequently used SPR measuring tool was the MacNab Criteria.

3.5. Clinical parameters (objective)

In our scoping review tools and tests from the objective, clinical domain, alone or in combination have been used in 30.6 % of the RCTs. This group is very heterogenous and include clinical parameters (neurological status, instrumental measurements, EMG, Physical fitness-physical training, body endurance tests, quantitative sensory testing); intraoperative parameters (operation time, blood loss, intraoperative fluoroscopy, time under general/epidural anesthesia); secondary outcome measures (recurrences and reoperation; complication rate; time to return to work; length of hospital stay; return to daily activities). The high variability and heterogeneity of the instruments and tests included in this group makes it impossible to give recommendation for a concrete set of tools. The most frequently used OMTs were the straight leg test (Lasegue test), the Japanese Orthopedic Association score, the quantities of medications used.

Despite this heterogeneity, the main point is that adding objective measurements could be the key to overcome the disadvantages of subjective OMT (VAS, ODI etc.) – poor reliability and bias (Gautschi et al., 2014; Mobbs, 2021a). Using these tools in combination with subjective OMT could outline a more holistic perspective of the patients experience before and after treatment of LDH.

The top 10 most used OMTs are listed in Table 3. The distribution is very similar for the whole group of 168 RCTs, for the surgical and for the non-surgical group of studies. The number of tools used per RCT was most frequently 2 (21.4 %), 3 (26.2 %) or 4 (21.4 %). The distribution was similar in the surgical and the non-surgical group of RCTs with a tendency for the surgical RCT to use slightly larger number of tools (Table 4). One outcome measurement tool was used in 13.1 %, 5 tools – in 9.5 % and 6 or more tools – in 8.4 % of the trials.

Table 3.

Top 10 OMTs for all 168 studies, for the surgical and for the nonsurgical RCTs.

Tool ALL (n = 168) SURG (n = 85) CONSERV (n = 111)
VAS 114 20.7 % 58 20.6 % 69 19.6 %
ODI 102 18.5 % 54 19.2 % 62 17.6 %
SOM 52 9.5 % 34 12.1 % 27 7.7 %
SF-36/12 42 7.6 % 25 8.9 % 27 7.7 %
CLINICS 30 5.5 % 14 5.0 % 22 6.3 %
NRS 24 4.4 % 6 2.1 % 19 5.4 %
InOp 22 4.0 % 18 6.4 %
RMDQ 21 3.8 % 8 2.8 % 18 5.1 %
Drugs 20 3.6 % 9 3.2 % 14 4.0 %
SLR 17 3.1 % 9 3.2 % 12 3.4 %

Table 4.

Number of OMTs applied per RCT for all 168 studies, for the surgical and for the nonsurgical RCTs.

№ tools per study № of studies all n = 168 № studies SURGERY n = 85 № of studies non-surgical – n = 111
1 22 13.1 % 12 14.1 % 16 14.4 %
2 36 21.4 % 14 16.5 % 28 25.2 %
3 44 26.2 % 26 30.6 % 25 22.5 %
4 36 21.4 % 14 16.5 % 26 23.4 %
5 16 9.5 % 11 12.9 % 9 8.1 %
6 7 4.2 % 5 5.9 % 2 1.8 %
7 5 3.0 % 2 2.4 % 3 2.7 %
>7 2 1.2 % 1 1.2 % 2 1.8 %

For the RCTs using 2 OMTs, the most frequent combination of tools was: VAS + ODI (pain + disability domains) or ODI + SF-36/12 (disability + QOL domains).

For the RCTs using 3 OMTs, the most frequent combination of tools was: VAS + ODI + SF-36/12 (pain + disability + QOL domains).

For the RCTs using 4 OMTs, the most frequent combination of tools was: VAS + ODI + SOM + CLI (pain + disability + clinical (2 tools) domains) or VAS + ODI + SOM + RMDQ (pain + disability (2 tools) + clinical domains) or VAS + ODI + SOM + SF-36/12 (pain + disability + clinical + QOL domains).

Distribution of the number of applications of the different OMTs during the 25-year period shows a rising interest with a peek in the period 2015–2019 when the top 10 tools have been applied 163 times in different RCTs (Table 5). The variations of the number of applications for the different tools is smooth, proportional and we did not observe any peaks for certain tools for certain periods.

Table 5.

Distribution of the number of applications of the different top 10 OMTs during the 25-year period.

2000–04 2005–09 2010–14 2015–19 2020–24
VAS 5 24 27 39 19
ODI 0 17 26 40 19
PostOp 4 10 12 20 6
SF-36/12 1 10 9 13 9
CLINICS 5 9 7 7 2
NRS 0 0 9 12 3
InOp 1 5 2 13 1
RMDQ 2 5 6 6 2
Drugs 3 6 6 5 0
SLR 2 4 2 8 1
Total 23 90 106 163 62

4. Discussion

Lumbar disk herniation (LDH) is recognized as one of the most prevalent spinal disorders that lies at the intersection of several medical specialties - orthopedics, neurology, neurosurgery, physical therapy, and pain management. Each specialty brings unique perspective, diagnostic methods, and treatment philosophies but also brings a high variability of treatment strategies (Abou-Elroos et al., 2017; Botelho et al., 2011; Hakan and Gürcan, 2016).

Reliable outcome measurement tools are the foundation for improved decision-making, for comparing different treatment options, for guidance of clinical practices, innovations and evidence-based approach and ultimately better patient care and enhanced quality of life (Abou-Elroos et al., 2017; Earhart et al., 2012; Werneke, 2016). Additionally, reliable outcome data can improve the economical analysis, prognostication, enhance recovery and control and/or avoid complications (Fairbank, 2015; van Munster et al., 2024; Werneke, 2016; Xiong et al., 2022).

A wide variety of tools are commonly employed to capture the multifaceted nature of patient outcome. LDH affects not only physical functioning but also psychological well-being, social participation, and overall quality of life. Some authors suggest that only VAS and SF-36 will be sufficient for measuring the outcome in patients with LDH (Zanoli, 2005). An international group of 22 specialists proposed the outcome of low back pain to be assessed with a numerical pain scale, lumbar-related function using the Oswestry disability index, health-related quality of life using the EQ-5D-3L questionnaire, and questions assessing work status and analgesic use (Clement et al., 2015). Other authors suggest a more complex measurement of outcome in LDH patients, using a more sophisticated combination of tools as: NRS, ODI, neck disability index, SF-12, EQ-5D, Zung depression scale, and Modified Somatic Perception Questionnaire anxiety scale (Godil et al., 2013).

This variability clearly delineates the lack of consensus amongst the scientific community about the number of domains and tools that should be used in the outcome measurment of patients with LDH.

The result of our scoping review demonstrates that most of the authors of RCTs studies prefer to use at least two tools in two different domains: Pain + Disability or Disability + Quality of life. For the surgical group the number of domains is most frequently 3 or 4. When the study includes 3 domains, they are most frequently Pain + Disability + Quality of life or Pain + Disability + Clinical. When the domains are 4, they usually assess Pain + Disability + Clinical + QOL. As a result, we would recommend the use of 4 domains covering Pain + Disability + Clinical + QOL.

4.1. Timing for OMT application

Another important point is at what time after the conducted treatment the outcome measurement tools should be applied. The recommended timeframe is to perform a baseline evaluation of pain, disability and quality of life before initiating any type of treatment. Recommended follow-up intervals are at 6, 12, and 24 months after initiating treatment, with optional follow-up at 3 months and 5 years (Clement et al., 2015).

4.2. Emerging trends and future perspectives

Some tools with shorter history couldn't become part of sufficient number of RCTs and consequently were not included in the current scoping review but still deserve attention. For example, the Core Outcome Measures Index - Back (COMI) (Deyo et al., 1998; Mannion et al., 2009, 2016) or the Keele STarT Back Screening Tool (Hill et al., 2011).

On the other hand, there is a shift toward digitalization of the OMTs and some authors emphasize the need for transition to computer adaptive tests that could be a promising alternative metric choice for measuring patient's function (Werneke, 2016). This attitude has been adopted by some organisations and programs as: PROMIS® (Patient-Reported Outcomes Measurement Information System), Neuro-QoL, NIH Toolbox, the International Consortium for Health Outcome Measurement (ICHOM) (Mannion et al., 2009; Young et al., 2021).

Additionally, the worldwide spread of smartphones and different wearable computing devices reveals new horizons for longitudinal monitoring of objective functional impairment in patients with LDH (Leibold et al., 2023; Sosnova et al., 2020). A lot of data could be passively collected through smartwatches or mobile phones during patient's daily life. A new notion has emerged – digital outcome measures (DOM). The main advantages of DOMs are that the collection of data could be performed during normal patients' activity, continuously, without unnecessary hospital visits. DOMs make possible enrollment in clinical trials of patients from distant geographical locations or of patients with restricted mobility (Ahmad et al., 2024; Lee et al., 2020; Maldaner et al., 2021; Sosnova et al., 2020; Ziga et al., 2023). However, the DOM are still not widely used due to some disadvantages – the process of data collection is still not standardized, the measurement is conducted in an uncontrolled environment and various factors may influence the objectivity of the data. Finally, the data acquisition is not performed under medical supervision which could lead to false data or missing data (Lee et al., 2020; Sosnova et al., 2020; Ziga et al., 2023). Further investigation of these tools is necessary. It is highly probable that the digital outcome measurement tools become the future standard of outcome measurement (Ahmad et al., 2024; Gautschi et al., 2014; Lee et al., 2020; Mobbs, 2021a; Young et al., 2021).

5. Conclusion

Measuring outcome in patients with LDH is a complex and multidimensional task. This scoping review of the RCTs identified 6 main domains of outcome measurement: pain, disability, QOL, clinical parameters, psychological facet and self-perceived recovery. The surgical group RCTs most frequently included tools from 4 domains: pain, disability, clinical parameters and QOL. The most frequently used tools for the different domains were respectively: VAS, ODI, a mixture of clinical parameters and SF-36/12. A new group of OMTs based on computer adapted tests, wearable devices and digital outcome measures are on the horizon trying to impose new standards but their application needs further investigation.

Limitations

One of the limitations of the current scoping review is the limited time period (25 years) that was included. Secondly, the more recent outcome measurement tools, like DOM, could not be included in the current scoping review as they have not established themselves yet. Therefore, conducting the same review in 5-years’ time with the same parameters might bring completely different results.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

We gratefully acknowledge the support of Prof. Andreas Demetriades provided during the revision process of the article.

Handling Editor: Dr W Peul

Footnotes

This article is part of a special issue entitled: EANS-Lumbar Disc Hernation published in Brain and Spine.

References

  1. Abou-Elroos D., Eltoukhy M., Nageeb G., Dawood E., Abouhashem S. Prolonged physiotherapy versus early surgical intervention in patients with lumbar disk herniation: short-term outcomes of clinical randomized trial. Asian Spine J. 2017;11(4):531–537. doi: 10.4184/asj.2017.11.4.531. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Ahmad H.S., Chauhan D., Dagli M.M., Turlip R.W., Bashti M., Hamade A., Wang P.T., Ghenbot Y., Yang A.I., Basil G.W., Welch W.C., Yoon J.W. Machine learning models leveraging smartphone-based patient mobility data can accurately predict functional outcomes after spine surgery. J. Clin. Med. 2024;13(21):6515. doi: 10.3390/jcm13216515. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Aithala P. Difficulties in using oswestry disability index in indian patients and validity and reliability of translator-assisted oswestry disability index. J. Orthop. Surg. Res. 2015;10(1) doi: 10.1186/s13018-015-0230-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Alodaibi F., Minick K.I., Fritz J.M. Do preoperative fear avoidance model factors predict outcomes after lumbar disc herniation surgery? A systematic review. Chiropractic Manual Therapies. 2013;21(1) doi: 10.1186/2045-709X-21-40. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Botelho R., Cardoso T., Bernardo W. Systematic review of the effect of fusion added to discectomy compared with discectomy alone for lumbar disk prolapse surgery. Open Access Surg. 2011;65 doi: 10.2147/oas.s25177. [DOI] [Google Scholar]
  6. Chiarotto A., Boers M., Deyo R.A., Buchbinder R., Corbin T.P., Costa L.O.P., et al. Core outcome measurement instruments for clinical trials in nonspecific low back pain. Pain. 2017;159(3):481–495. doi: 10.1097/j.pain.0000000000001117. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Chung E.J., Hur Y., Lee B. A study of the relationship among fear-avoidance beliefs, pain and disability index in patients with low back pain. J. Exercise Rehabilitation. 2013;9(6):532–535. doi: 10.12965/jer.130079. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Clement R.C., Welander A., Stowell C., Cha T.D., Chen J.L., Davies M., Fairbank J.C., Foley K.T., Gehrchen M., Hagg O., Jacobs W.C., Kahler R., Khan S.N., Lieberman I.H., Morisson B., Ohnmeiss D.D., Peul W.C., Shonnard N.H., Smuck M.W., Solberg T.K., et al. A proposed set of metrics for standardized outcome reporting in the management of low back pain. Acta Orthop. 2015;86(5):523–533. doi: 10.3109/17453674.2015.1036696. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Cook CE. Clinimetrics Corner. The minimal clinically important change score (MCID): a necessary pretense. J. Man. Manip. Ther. 2008;16(4):E82–E83. doi: 10.1179/jmt.2008.16.4.82E. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Deyo R.A., Battie M., Beurskens A.J., Bombardier C., Croft P., Koes B., Malmivaara A., Roland M., Von Korff M., Waddell G. Outcome measures for low back pain research. A proposal for standardized use. Spine (Phila Pa 1976) 1998;23(18):2003–2013. doi: 10.1097/00007632-199809150-00018. Erratum in: Spine 1999 Feb 15;24(4):418. PMID: 9779535. [DOI] [PubMed] [Google Scholar]
  11. Du C., Song K., Hai B., Wang X. Retrospective study of minimal three-year follow-up of transforaminal endoscopic discectomy for lumbar disc herniation: 5000 multicenter cases. Cureus. 2023;15(12) doi: 10.7759/cureus.50993. 2023 Dec 23. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Earhart J., Roberts D., Roc G., Gryzlo S., Hsu W. Effects of lumbar disk herniation on the careers of professional baseball players. Orthopedics. 2012;35(1):43–49. doi: 10.3928/01477447-20111122-40. [DOI] [PubMed] [Google Scholar]
  13. Fairbank J. Spinal disorders, quality-based healthcare and spinal registers. Acta Orthop. 2015;86(5):521–522. doi: 10.3109/17453674.2015.1072431. Epub 2015 Jul 13. PMID: 26169065; PMCID: PMC4564772. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Farzanegan G., Alghasi M., Safari S. Quality-of-life evaluation of patients undergoing lumbar discectomy using short form 36. Anesthesiol. Pain Med. 2011;1(2) doi: 10.5812/kowsar.22287523.1998. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Finkelstein J.A., Schwartz C.E. Patient-reported outcomes in spine surgery: past, current, and future directions. J. Neurosurg. Spine. 2019;31(2):155–164. doi: 10.3171/2019.1.SPINE18770. Epub 2019 Aug 1. PMID: 31370009. [DOI] [PubMed] [Google Scholar]
  16. Firdous S., Berger A., Jehangir W., Fernandez C., Behm B., Mehta Z., et al. How should we assess pain: do patients prefer a quantitative or qualitative scale? A study of patient preferences. Am. J. Hospice Palliat. Med. 2020;38(4):383–390. doi: 10.1177/1049909120945599. [DOI] [PubMed] [Google Scholar]
  17. Gautschi O.P., Corniola M.V., Schaller K., Smoll N.R., Stienen M.N. The need for an objective outcome measurement in spine surgery--the timed-up-and-go test. Spine J. 2014;14(10):2521–2522. doi: 10.1016/j.spinee.2014.05.004. [DOI] [PubMed] [Google Scholar]
  18. Godil S.S., Parker S.L., Zuckerman S.L., Mendenhall S.K., Devin C.J., Asher A.L., McGirt M.J. Determining the quality and effectiveness of surgical spine care: patient satisfaction is not a valid proxy. Spine J. 2013;13(9):1006–1012. doi: 10.1016/j.spinee.2013.04.008. [DOI] [PubMed] [Google Scholar]
  19. Hakan T., Gürcan S. Spontaneous regression of herniated lumbar disc with new disc protrusion in the adjacent level. Case Rep. Orthopedics. 2016;2016:1–4. doi: 10.1155/2016/1538072. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Hill J.C., Whitehurst D.G., Lewis M., Bryan S., Dunn K.M., Foster N.E., Konstantinou K., Main C.J., Mason E., Somerville S., Sowden G., Vohora K., Hay E.M. Comparison of stratified primary care management for low back pain with current best practice (STarT back): a randomised controlled trial. Lancet. 2011;378(9802):1560–1571. doi: 10.1016/S0140-6736(11)60937-9. Epub 2011 Sep 28. PMID: 21963002; PMCID: PMC3208163. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Hjermstad M., Fayers P., Haugen D., Caraceni A., Hanks G., Loge J., et al. Studies comparing numerical rating scales, verbal rating scales, and visual analogue scales for assessment of pain intensity in adults: a systematic literature review. J. Pain Symptom Manag. 2011;41(6):1073–1093. doi: 10.1016/j.jpainsymman.2010.08.016. [DOI] [PubMed] [Google Scholar]
  22. Hoffman D.L., Dukes E.M. The health status burden of people with fibromyalgia: a review of studies that assessed health status with the SF-36 or the SF-12. Int. J. Clin. Pract. 2008;62(1):115–126. doi: 10.1111/j.1742-1241.2007.01638.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Lee T.J., Galetta M.S., Nicholson K.J., Cifuentes E., Goyal D.K.C., Mangan J.J., Fang T., Schroeder G.D., Kepler C.K., Vaccaro A.R. Wearable technology in spine surgery. Clin. Spine Surg. 2020;33(6):218–221. doi: 10.1097/BSD.0000000000000905. [DOI] [PubMed] [Google Scholar]
  24. Leibold A., Mansoor Ali D., Harrop J., Sharan A., Vaccaro A.R., Sivaganesan A. Smartphone-based activity tracking for spine patients: current technology and future opportunities. World Neurosurg. X. 2023;21 doi: 10.1016/j.wnsx.2023.100238. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Lin Y., Yu Y., Zeng J., Zhao X., Wan C. Comparing the reliability and validity of the SF-36 and SF-12 in measuring quality of life among adolescents in China: a large sample cross-sectional study. Health Qual. Life Outcome. 2020;18(1):360. doi: 10.1186/s12955-020-01605-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Maldaner N., Sosnova M., Zeitlberger A.M., Ziga M., Gautschi O.P., Regli L., Bozinov O., Weyerbrock A., Stienen M.N. Responsiveness of the self-measured 6-minute walking test and the timed Up and Go test in patients with degenerative lumbar disorders. J. Neurosurg. Spine. 2021;35(1):52–59. doi: 10.3171/2020.11.SPINE201621. Epub 2021 May 7. PMID: 33974372. [DOI] [PubMed] [Google Scholar]
  27. Mannion A.F., Porchet F., Kleinstück F.S., Lattig F., Jeszenszky D., Bartanusz V., Dvorak J., Grob D. The quality of spine surgery from the patient's perspective. Part 1: the core outcome measures index in clinical practice. Eur. Spine J. 2009;18:367–373. doi: 10.1007/s00586-009-0942-8. Suppl 3(Suppl 3) [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Mannion A.F., Vila-Casademunt A., Domingo-Sàbat M., Wunderlin S., Pellisé F., Bago J., Acaroglu E., Alanay A., Pérez-Grueso F.S., Obeid I., Kleinstück F.S., European Spine Study Group (ESSG) The core outcome measures index (COMI) is a responsive instrument for assessing the outcome of treatment for adult spinal deformity. Eur. Spine J. 2016;25(8):2638–2648. doi: 10.1007/s00586-015-4292-4. [DOI] [PubMed] [Google Scholar]
  29. Mobbs R.J. From the subjective to the objective era of outcomes analysis: how the tools we use to measure outcomes must change to be reflective of the pathologies we treat in spinal surgery. J. Spine surg.(Hong Kong) 2021;7(3):456–457. doi: 10.21037/jss-2021-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Mobbs R.J. From the subjective to the objective era of outcomes analysis: how the tools we use to measure outcomes must change to be reflective of the pathologies we treat in spinal surgery. J. Spine Surg. 2021;7(3):456–457. doi: 10.21037/jss-2021-2. PMID: 34734150; PMCID: PMC8511557. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Modarresi S., Lukacs M., Ghodrati M., Salim S., MacDermid J., Walton D. A systematic review and synthesis of psychometric properties of the numeric pain rating scale and the visual analog scale for use in people with neck pain. Clin. J. Pain. 2021;38(2):132–148. doi: 10.1097/AJP.0000000000000999. [DOI] [PubMed] [Google Scholar]
  32. Papuga M.O., Mesfin A., Molinari R.W., Rubery P.T. Correlation of promis physical function and pain cat instruments with oswestry disability index and neck disability index in spine patients. Spine J. 2015;15(10):S109–S110. doi: 10.1097/BRS.0000000000001518. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Roland M., Fairbank J. The roland-morris disability questionnaire and the oswestry disability questionnaire. Spine (Phila Pa 1976) 2000;25(24):3115–3124. doi: 10.1097/00007632-200012150-00006. [DOI] [PubMed] [Google Scholar]
  34. Saltychev M., Vastamäki H., Mattie R., McCormick Z., Vastamäki M., Laimi K. Psychometric properties of the pain numeric rating scale when applied to multiple body regions among professional musicians. PLoS One. 2016;11(9) doi: 10.1371/journal.pone.0161874. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Schwartz C.E., Ayandeh A., Finkelstein J.A. When patients and surgeons disagree about surgical outcome: investigating patient factors and chart note communication. Health Qual. Life Outcome. 2015;13:161. doi: 10.1186/s12955-015-0343-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Shafshak T., Elnemr R. The visual analogue scale versus numerical rating scale in measuring pain severity and predicting disability in low back pain. JCR J. Clin. Rheumatol. 2020;27(7):282–285. doi: 10.1097/RHU.0000000000001320. [DOI] [PubMed] [Google Scholar]
  37. Sosnova M., Zeitlberger A.M., Ziga M., Gautschi O.P., Weyerbrock A., Stienen M.N., Maldaner N. Longitudinal smartphone-based self-assessment of objective functional impairment in patients undergoing surgery for lumbar degenerative disc disease: initial experience. Acta Neurochir (Wien) 2020;162(9):2061–2068. doi: 10.1007/s00701-020-04377-8. Epub 2020 May 13. PMID: 32405670. [DOI] [PubMed] [Google Scholar]
  38. Stevens M.L., Lin C.C., Maher C.G. The roland morris disability questionnaire. J. Physiother. 2016;62(2):116. doi: 10.1016/j.jphys.2015.10.003. [DOI] [PubMed] [Google Scholar]
  39. Tricco A.C., Lillie E., Zarin W., O'Brien K.K., Colquhoun H., Levac D., Moher D., Peters M.D., Horsley T., Weeks L., Hempel S., et al. PRISMA extension for scoping reviews (PRISMA-ScR): checklist and explanation. Ann. Intern. Med. 2018;169(7):467–473. doi: 10.7326/M18-0850. [DOI] [PubMed] [Google Scholar]
  40. van Munster J., Noordenbos M.W., Halperin I.J.Y., van den Hout W.B., van Benthem P.P., Seinen I., Moojen W.A., Peul W. Impact of evidence-based guidelines on healthcare utilisation and costs for disc related sciatica in the Netherlands: a population-based, cross-sectional study. BMJ Open. 2024;14(3) doi: 10.1136/bmjopen-2023-078459. PMID: 38471686; PMCID: PMC10936503. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Werneke M. A proposed set of metrics for standardized outcome reporting in the management of low back pain. Acta Orthop. 2016;87(1):88. doi: 10.3109/17453674.2015.1120127. Epub 2015 Nov 26. PMID: 26610164; PMCID: PMC4940601. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Xiong G.X., Goh B.C., Agaronnik N., Crawford A.M., Smith J.T., Hershman S.H., Schoenfeld A.J., Simpson A.K. Impact of insurance type on patient-reported outcome measures in patients with lumbar disc herniation. Spine J. 2022;22(8):1309–1317. doi: 10.1016/j.spinee.2022.03.011. Epub 2022 Mar 26. PMID: 35351668. [DOI] [PubMed] [Google Scholar]
  43. Yao M., Xu Bp, Li Zj, et al. A comparison between the low back pain scales for patients with lumbar disc herniation: validity, reliability, and responsiveness. Health Qual. Life Outcome. 2020;18:175. doi: 10.1186/s12955-020-01403-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Young K., Steinhaus M., Gang C., Vaishnav A., Jivanelli B., Lovecchio F., Qureshi S., McAnany S., Kim H.J., Iyer S. The use of patient-reported outcomes measurement information system in spine: a systematic review. Int. J. Spine Surg. 2021;15(1):186–194. doi: 10.14444/8024. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Zanoli G. Outcome assessment in lumbar spine surgery. Acta Orthop. Suppl. 2005;76(318):5–47. PMID: 16175972. [PubMed] [Google Scholar]
  46. Ziga M., Sosnova M., Zeitlberger A.M., Regli L., Bozinov O., Weyerbrock A., Ratliff J.K., Stienen M.N., Maldaner N. Objective outcome measures May demonstrate continued change in functional recovery in patients with ceiling effects of subjective patient-reported outcome measures after surgery for lumbar degenerative disorders. Spine J. 2023;23(9):1314–1322. doi: 10.1016/j.spinee.2023.05.002. Epub 2023 May 13. PMID: 37182704. [DOI] [PubMed] [Google Scholar]

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