Chronic myeloid leukemia in resource-limited settings: Navigating treatment challenges amid limited tyrosine kinase inhibitor access

Abstract

Objectives

Chronic myeloid leukemia presents unique management challenges in resource-limited settings such as Pakistan, where access to advanced molecular monitoring and newer tyrosine kinase inhibitors remains limited. This study evaluates the outcomes in patients with chronic myeloid leukemia in Pakistan, where first-generation tyrosine kinase inhibitors remain the primary mode of treatment due to the lack of newer interventions and insufficient molecular surveillance facilities.

Methods

This retrospective cohort study analyzed 73 patients with chronic myeloid leukemia treated at the Indus Hospital and Health Network, Karachi, Pakistan, between 2018 and 2025. Patients were stratified according to the European Treatment and Outcome Study long-term survival score, and treatment responses were compared using hematologic and molecular remission.

Results

The proportion of males and females was almost equal. Conventional karyotypes were observed in 92.9% of cases. With imatinib as the first-line therapy, optimal response and treatment failure was observed in 31.3% and 45.3% cases, respectively. A lower complete hematologic response was associated with intermediate-risk scores and atypical fluorescence in situ hybridization results. The intent to change therapy was found to be a powerful predictor of better overall response (adjusted odds ratio: 23.620, p-value: 0.0001). Only two patients transitioned to blast crisis.

Conclusion

Although there are promising trends of improvement in progression-free survival, the high rates of treatment failure as well as the lack of access to advanced treatment regimens and monitoring remain major concern. Strengthening public–private collaborations and international partnerships is essential to ensure equitable access to advanced therapies and improve long-term outcomes in patients with chronic myeloid leukemia in low- and middle-income countries.

Keywords

Chronic myeloid leukemia low- and middle-income countries tyrosine kinase inhibitors first generation imatinib cytogenetics response progression-free survival

Introduction

Chronic myeloid leukemia (CML) is a clonal myeloproliferative neoplasm caused by the breakpoint cluster region (BCR)-Abelson (BCR-ABL1) fusion oncoprotein, a product of Philadelphia chromosome translocation, which results in constitutive tyrosine kinase activity. The advent of tyrosine kinase inhibitors (TKIs) marked a major transition in CML care worldwide, transforming a fatal disease into a generally manageable chronic condition, particularly in high-income countries (HICs) where access to second and third generation TKIs, molecular monitoring, and treatment discontinuation strategies is available.^1,2

In Pakistan, CML contributes substantially to hematologic malignancies. Data from a 4-year institutional hematopoietic tumor registry in Karachi indicated that CML was among the most common diseases in males, representing approximately 16% of all hematologic cancers.³ A study conducted in Northern Pakistan has reported that CML accounts for approximately 80% of all myeloproliferative disorders, with the peak incidence occurring between the ages of 21 and 50 years and a male predominance.⁴ Compared with the Western population, mean age at presentation in the Pakistani population is much lower, and several patients are in their 30s to 50s at the time of diagnosis.⁵

Current research and treatment strategies are actively progressing toward achieving a cure for CML, specifically through the induction of treatment-free remission (TFR).⁶

The infrastructure for CML care in Pakistan continues to face challenges, despite the relatively high prevalence and younger age at onset. Limitations related to cost and an underdeveloped healthcare system hinder the availability of advanced therapies, including second-generation TKIs, recommended molecular monitoring, consistent drug supply, and options such as treatment discontinuation. First-generation TKIs (such as imatinib) are the backbone of available therapy for many patients. However, delayed patient presentation, inadequate diagnostic infrastructure, and lack of data on long-term outcomes raise important concerns regarding whether the advancements observed in high-resource settings are replicated locally.^7,8

In Pakistan, although imatinib is frequently available via governmental or donor-supported assistance programs, the use of newer TKIs (e.g. nilotinib) as frontline therapy is restricted owing to budgetary limitations and is often limited to private centers.⁷ Molecular monitoring via real time polymerase chain reaction (PCR) (RT-PCR) or cytogenetics is not available consistently, and when available, it is sometimes performed at intervals longer than those recommended in the guidelines due to economic constraints.⁷ In addition, indirect costs, travel distances, and concerns over the sustainability of free drug programs affect compliance and treatment continuity.⁹ Growing evidence has demonstrated that contextual factors affect CML outcomes in Pakistan; however, these impacts have not yet been quantified fully.

The proposed study considered the outcome among patients with CML in Pakistan where first-generation TKIs were used in the absence of advanced therapy and regular molecular monitoring. Through an analysis of emerging literature as well as data on clinical therapeutic responses, survival rates, and disease progression, this study aimed to define current care gaps, guide policy, and develop action plans to enhance the outcomes under resource limitations.

Materials and methods

A retrospective analysis was conducted at the departments of Clinical and Laboratory Hematology of the Indus Hospital and Health Network (IHHN), Karachi, Pakistan. IHHN is a non-profit making tertiary care hospital offering holistic services free of charge in the entire country.

Study population

The study population included all patients diagnosed with CML between January 2018 and March 2025. The diagnosis was established based on the World Health Organization (WHO) criteria and included clinical presentation, hematologic parameters, bone marrow examination, and confirmatory cytogenetic or molecular testing.¹⁰ A total of 73 patients who met the inclusion criteria were included in the analysis.

Data collection

After obtaining consent from the Institutional Review Board (IRB) (IRB#: IHHN_IRB_2022_09_013), clinical, laboratory, and therapeutic data related to the research were retrieved from the electronic medical records of the hospital. The following variables were recorded: (a) Demographic characteristics. Age, sex, and locality of residence (urban/rural); (b) Clinical manifestation. Presenting symptoms and comorbidities; (c) Laboratory findings. Complete blood count (CBC), staging of the disease using bone marrow biopsy, cytogenetic analysis, fluorescence in situ hybridization (FISH), and molecular testing; (d) Details of treatment. Type of TKI used, treatment adherence, therapeutic response, and any subsequent changes (where appropriate).

Diagnostic and cytogenetic analysis

A diagnosis of CML was established using CBC parameters, bone marrow biopsy, and cytogenetic analysis. Standard G-banded karyotyping was performed, and the presence of the BCR:ABL1 fusion gene was determined using interphase FISH. Based on cytogenetic findings, patients were classified as having typical or atypical CML.

Risk stratification

Baseline risk was measured using the European Treatment and Outcome Study (EUTOS) long-term survival scores (ELTS), followed by the categorization of the patients into low-, intermediate-, and high-risk categories after an assessment of age, spleen size, platelet count, and the percentage of blasts in the peripheral blood.¹¹

Surveillance and treatment procedure

Due to constraints related to institutional resources and the hospital’s objective to provide free medical care, all patients were initiated on first-generation TKIs, predominantly imatinib. Nilotinib was administered when a patient failed to respond to first-line imatinib therapy, as defined by the European Leukemia Network (ELN) treatment failure criteria.¹² Therapeutic response (optimal, warning, and failure) monitoring employed complete hematological response (CHR) and molecular response monitoring, which were measured using quantitative PCR (qPCR) analysis of BCR levels in a transcript of ABL1 at predetermined intervals based on ELN response assessment criteria for CML treatment.¹² However, due to resource constraints, strict adherence to fixed time points (e.g. 3, 6, or 12 months) was not always feasible, and monitoring was occasionally performed at extended or variable intervals.

Treatment adherence and follow-up

Adherence to the treatment was evaluated by reviewing the follow-up records and physicians notes made during clinic visits, indicating compliance or non-compliance. Patients were considered treatment-adherent when they maintained regular follow-up visits and there was no documented evidence of treatment interruption or non-compliance in the physician notes.

Statistical analyses

Statistical analyses were performed using Statistical Package for Social Sciences (SPSS) software (IBM SPSS Statistics version 24.0). Demographic and clinical information were summarized using descriptive statistics. Categorical variables were evaluated using the chi-square (Fisher’s exact) test, according to the nature of the association. Predictors of treatment response were determined using logistic regression. The Kaplan–Meier approach was used to determine progression-free survival (PFS), and a log-rank test was used to compare survival distributions. A p-value <0.05 was considered statistically significant.

Results

Patient demographics and clinical characteristics

A total of 73 patients with a confirmed diagnosis of CML were enrolled in the study. The mean age of the patients was 37.8 years (±11.9), with approximately equal gender distribution comprising 46.6% male and 53.4% female. Most patients (72.6%) lived in urban areas. The most common presenting symptoms were fever (42%), generalized weakness or fatigue (33%), and abdominal pain (26%). Most patients (79.5%) had no recorded comorbidities, whereas 20.5% had a range of conditions, each accounting for a small proportion of the total, including Hepatitis (B, C, and D), decompensated chronic liver disease secondary to Hepatitis B and C, epilepsy, hypertension, and pulmonary tuberculosis.

Cytogenetics and risk stratification findings

Significantly more patients (92.9% of 56 patients) presented with a typical karyotype, whereas 7 had an atypical karyotype. Among the four patients reported to have additional cytogenetic abnormalities, as revealed by karyotypic analysis, three had three-way translocation (t(6:9:22), t(9;22;15)(q34;q11.2;q26.3), and t(9;22;18)(q34;q11.2;q23)), and one patient exhibited deletion of chromosome 9 (der(9)del(9q)t(9;22)). Similarly, FISH analysis in 50 patients revealed typical results in 56%, atypical results in 32%, and both in 12%. Based on baseline risk stratification, 22.8%, 45.6%, and 31.6% of patients were classified as having low, intermediate, and high-risk, respectively (Table 1).

Table 1.

Demographic and clinical profiles of the study participants.

Variable	Value
Demographics
Age, yearsMean (±SD)	37.8 years (±11.9)
Sex, male/femalen (%)	34 (46.6)/39 (53.4)
Location, urban/ruraln (%)	53 (72.6)/20 (27.4)
Laboratory parameters
Hemoglobin, g/dLMean (±SD)	9.5 (±2.2)
Total leukocyte count (TLC), ×10⁹/LMean (±SD)	169.0 (±137.7)
Neutrophils, %Mean (±SD)	56.1 (±15.5)
Basophils, %Mean (±SD)	5.5 (±4.0)
Blasts, %Mean (±SD)	2.6 (±1.4)
Platelet count, ×10⁹/LMean (±SD)	377.8 (±227.5)
Spleen size, cmMean (±SD)	18.9 (±4.3)
^aKaryotype (n = 56)
Typical, n (%)	52 (92.9)
Atypical, n (%)	4 (7.1)
^bFluorescence in situ hybridization (FISH) (n = 50)
Typical, n (%)	28 (56.0)
Atypical, n (%)	16 (32.0)
Both, n (%)	6 (12.0)
^cBaseline risk stratification
Low-risk, n (%)	13 (22.8)
Intermediate-risk, n (%)	26 (45.6)
High-risk, n (%)	18 (31.6)

Data missing (n = 17); ^bData missing (n = 23); ^cData missing (n = 16) due to non-availability of spleen size, which is required for the calculation of the risk score.

Treatment adherence and location

Treatment adherence was observed in 27.5% (19/69) and 72.5% (50/69) of the urban patients; however, there was no significant difference between the two groups (p = 1.000).

Treatment response

The response to first-line TKI therapy was evaluated in 73 patients with CML; 64 received imatinib, and 9 received nilotinib. Among patients with available CBC data, CHR after 1 month was achieved in 62.9% of those receiving imatinib and 62.5% of those receiving nilotinib; however, this difference was not statistically significant (p = 1.000) (Table 2). The overall response to TKIs was variable, with optimal response observed in 31.3% of patients on imatinib and 44.4% of those on nilotinib. Treatment failure was observed in 45.3% of the patients on imatinib and 33.3% of those on nilotinib (Figure 1). A treatment switch was offered to 31 (42.5%) patients; 29 (45.3%) had initially received imatinib, whereas the remainder had received nilotinib. Following the TKI switch, 29 of the 31 patients were transitioned to nilotinib, whereas the remaining patients were initiated on dasatinib. Although 2.3% of the patients on imatinib experienced recurrent cytopenia, leading to a second-line switch, no nilotinib treatment switch due to toxicity was observed.

Table 2.

Treatment profile of the study participants.

^aHematological response		Imatinib(n = 62)	Nilotinib(n = 8)	p-value
Achieved	44 (62.9)	39 (62.9)	5 (62.5)	1.000
Not achieved	26 (37.1)	23 (37.1)	3 (37.5)	1.000

CBC not available (n = 3).

CBC: complete blood count.

Figure 1.

Overall response to the TKI therapy in the study participants. It presents the overall treatment response of patients with CML who were treated with TKI (n = 73). The responses are classified based on the European Leukemia Network (ELN) criteria into optimal response, warning, and treatment failure. The figure shows the percentage of patients who attained each category of responses by type of TKI therapy (imatinib vs nilotinib), thus showing the relative distribution of the treatment outcomes in the study population. TKI: tyrosine kinase inhibitor; CML: chronic myeloid leukemia.

Majority of the patients reported musculoskeletal symptoms, including myalgia and joint pain. Cutaneous adverse effects were also observed, with a proportion of patients exhibiting hypopigmentation, whereas a smaller subset developed melasma or hypopigmentation. Additionally, a small proportion of patients experienced hematological toxicity, necessitating temporary treatment interruption or transition to second-line therapy.

Association of cytogenetics and risk scores with outcomes

An evaluation of the findings of baseline cytogenetics and risk scores (Table 3) revealed no significant differences in the treatment outcomes between typical and atypical karyotypes. However, atypical FISH results tended to be associated with poorer response rates.

Table 3.

Association of baseline cytogenetic findings and risk score with complete hematological and overall responses.

		Complete hematological response
			Achieved	Not achieved	p-value
Karyotype (n = 55)	Typical, n (%)	52	32 (94.1)	20 (95.2)	1.000
Karyotype (n = 55)	Atypical, n (%)	3	2 (5.9)	1 (4.8)
Fluorescence in situ hybridization (FISH, n = 46)	Typical, n (%)	26	20 (69.0)	6 (35.3)
	Atypical, n (%)	16	7 (24.1)	9 (52.9)	0.058
	Both, n (%)	4	2 (6.9)	2 (11.8)	0.058
Baseline risk stratification(n = 54)	Low-risk, n (%)	11	5 (14.3)	6 (31.6)	0.194
	Intermediate-risk, n (%)	25	19 (54.3)	6 (31.6)
	High-risk, n (%)	18	11 (31.4)	7 (36.8)
Overall response
			Optimal	Warning	Failure	p-value
Karyotype(n = 56)	Typical, n (%)	52	19 (95.0)	14 (93.3)	19 (90.5)	1.000
Karyotype(n = 56)	Atypical, n (%)	4	1 (5.0)	1 (6.7)	2 (9.5)	1.000
FISH (n = 50)	Typical, n (%)	26	10 (66.7)	5 (55.6)	11 (45.8)	0.712
	Atypical, n (%)	16	3 (20.0)	3 (33.3)	10 (41.7)
	Both, n (%)	6	2 (13.3)	1 (11.1)	3 (12.5)
Baseline risk stratification(n = 57)	Low-risk, n (%)	13	3 (15.8)	4 (30.8)	6 (24.0)	0.870
	Intermediate-risk, n (%)	26	9 (47.4)	5 (38.5)	12 (48.0)
	High-risk, n (%)	18	7 (36.8)	4 (40.8)	7 (28.0)

Overall, the treatment switch occurred in 25 patients, including 44.4% (8/18) of those in the high-risk group, 46.2% (12/26) of those in the intermediate-risk group, and 38.5% (5/13) of those in the low-risk group, with no statistically significant difference between the groups (p-value = 0.942).

Logistic regression analysis (Table 4) demonstrated that atypical FISH (cOR: 4.286, p = 0.034) and intermediate-risk scores (cOR: 0.230, p = 0.042) were significantly associated with lower CHR, although these associations were not significant in the adjusted model. For overall response (Table 5), treatment switch emerged as the most significant predictor with an adjusted odds ratio of 23.620 (p ≤ 0.0001), indicating a significant association between switching TKIs and better outcomes.

Table 4.

Regression analysis of impact of under study variables on the complete hematological response.

Variables		cOR (95% CI)	p-value	aOR (95% CI)	p-value
Age, years	≤30	Reference
	31–50	0.395 (0.133–1.172)	0.094 ^a	0.639 (0.291–1.403)	0.264
	>50	0.545 (0.117–2.549)	0.441
Sex	Female	Reference
Sex	Male	1.409 (0.549–3.614)	0.475
Hb, g/dL	≤10	Reference
Hb, g/dL	>10	1.190 (0.438–3.236)	0.733
TLC, ×10⁹/L	≤100	Reference
	101–300	1.074 (0.370–3.112)	0.896
	>300	1.275 (0.243–4.751)	0.717
Basophils, %	≤1.0%	Reference
Basophils, %	>1.0%	0.611 (0.175–2.132)	0.440
Platelet count, ×10⁹/L	≤145	Reference
	146–400	0.436 (0.066–2.888)	0.389
	>400	0.333 (0.046–2.415)	0.277
Fluorescence in situ hybridization (FISH)	Typical	Reference
	Atypical	4.286 (1.117–16.443)	0.034 ^a	0.999 (0.999–1.000)	0.872
	Both	6.667 (0.971–45.793)	0.054
European Treatment and Outcome Study (EUTOS) risk score	Low	Reference
	Intermediate	0.230 (0.056–0.947)	0.042 ^a	1.000 (0.999–1.000)	0.841
	High	0.398 (0.109–2.159)	0.217 ^a	1.000 (0.999–1.000)	0.841
Spleen size, cm		1.000 (0.999–1.001)	0.797

statistically significant.

cOR: crude odds ratio; aOR: adjusted odds ratio; CI: confidence interval; TLC: totoal leukocyte count; Hb: hemoglobin.

Table 5.

Regression analysis of the impact of parameters on the overall response to the TKIs.

Variables		cOR (95% CI)	p-value	aOR (95% CI)	p-value
Age, years	≤30	Reference
	31–50	1.380 (0.460–4.143)	0.565
	>50	1.000 (0.212–4.709)	1.000
Sex	Female	Reference
Sex	Male	0.807 (0.309–2.109)	0.663
Hb, g/dL	≤10	Reference
Hb, g/dL	>10	1.097 (0.389–3.086)	0.861
TLC, ×10⁹/L	≤100	Reference
	101–300	1.977 (0.650–6.009)	0.230 ^a	2.048 (0.535–7.845)	0.295
	>300	0.784 (0.210–2.923)	0.717
Basophils, %	≤1.0%	Reference
Basophils, %	>1.0%	0.587 (0.143–2.411)	0.460
Platelet count, ×10⁹/L	≤145	Reference
	146–400	0.382 (0.039–3.719)	0.408
	>400	0.607 (0.057–6.439)	0.679
FISH	Typical	Reference
	Atypical	1.875 (0.471–7.454)	0.372
	Both	1.250 (0.192–8.129)	0.815
European Treatment and Outcome Study (EUTOS) Risk score	Low	Reference
	Intermediate	0.567 (0.124–2.597)	0.456
	High	0.471 (0.095–2.337)	0.357
Complete hematological response (CHR)	No	Reference
Complete hematological response (CHR)	Yes	0.532 (0.185–1.528)	0.241 ^a	0.477 (0.128–1.779)	0.270
Treatment switch	No	Reference
Treatment switch	Yes	21.176 (4.448–100.814)	<0.0001 ^a	23.620 (4.412–126.468)	<0.0001 ^a
Spleen size, cm		0.999 (0.999–1.001)	0.9.1

statistically significant.

cOR: crude odds ratio; aOR: adjusted odds ratio; CI: confidence interval; TKIs: tyrosine kinase inhibitors; Hb: hemoglobin; TLC: total leukocyte count.

Follow-up details

The mean follow-up period was 42.3 months (±33.8 months). At the time of analysis, all patients in the study group were alive. Progression to blast crisis was observed in two patients, both in the imatinib group. The PFS rate was 100% in the nilotinib group compared with 96.9% in the imatinib group. The overall PFS was reported to be 1065.0 (615.0–1750.0) days. Patients receiving imatinib had a median (interquartile range (IQR) PFS of 929.5 days (543.0–1600.0 days) compared with 2032.0 days (1265.5–2719.5 days) in those receiving nilotinib (Figure 2). There was a significant increase in the PFS of patients receiving nilotinib compared with that of those receiving imatinib (log-rank p = 0.034).

Figure 2.

Progression-free survival (PFS) based on the TKI. It shows Kaplan–Meier survival analysis of PFS in patients with CML based on the type of TKI (imatinib vs nilotinib) received. PFS refers to the interval between the beginning of treatment and disease progression (accelerated or blast crisis) or the final follow-up. The figure illustrates a difference in survival distribution between treatment groups during the follow-up time and comparisons performed using the log-rank test. TKI: tyrosine kinase inhibitor; CML: chronic myeloid leukemia.

Discussion

This study provides a valuable snapshot of CML in low-to-middle-income countries (LMICs), highlighting demographic patterns, cytogenetic profiles, treatment responses, and survival outcomes that differ significantly from those observed in HICs.

The mean age at diagnosis of 37.8 years in LMICs was substantially lower than in HICs, where the median age is typically >50 years. This younger age at presentation is consistent with other LMIC cohorts, including Pakistan and sub-Saharan Africa, and may reflect population demographics, environmental exposures, or genetic factors.^13–15 The high urban representation suggests urban-centric healthcare access and lack of healthcare access in rural areas.¹⁶ An association between patient location and treatment adherence revealed an insignificant relationship (p = 1.000), demonstrating that close follow-ups and compliance monitoring promote better treatment responses regardless of the distance.

The exceptionally low non-compliance rate observed in this study (1.4%) compares favorably with regional adherence reports from other LMICs, where rates remain substantially lower (34.2% in China, 55.1% in Ethiopia, and 69% in Malaysia), likely reflecting the benefit of structured follow-up and monthly prescription refills.^17–19 When second-line TKIs are available, treatment outcomes in LMICs increasingly approximate those reported in HICs, as demonstrated by Kenya’s Glivec International Patient Assistance Program (GIPAP) and by the reported complete cytogenetic response (CCyR) and major molecular response (MMR) rates of approximately 50% and 40%, respectively, following imatinib failure.^15,20,21 Nevertheless, TFR remains difficult to achieve across LMICs, with low sustained TFR rates reported despite high deep molecular response rates, underscoring the importance of reliable molecular monitoring.^22,23 Collectively, these data place our findings within the broader LMIC experience, where younger age at diagnosis, limited TKI availability, cost-prohibitive mutation testing, and variable adherence remain common challenges, which can be partly mitigated through coordinated care models and public–private partnerships.^16,24,25

Long-term survival and molecular response rates in patients with CML in public–private partnership programs (e.g. GIPAP) in Pakistan and similar countries are significantly higher than those for patients managed outside these initiatives. Patients with guaranteed continuous imatinib access through these initiatives demonstrate better 20-year overall survival (76% vs. 61%).^16,26 However, achieving deep molecular remission and TFR remains a challenge in Pakistan due to limited access to TKI options beyond imatinib and nilotinib.^7,27 Both have lower TFR rates (38% at 8 years for imatinib and 43% at 5 years for nilotinib) than those reported with newer-generation TKIs.^6,28,29 In contrast, in the developed world settings, access to the fourth- and later-generation TKIs in chronic-phase CML (CML-CP) helps patients achieve higher deep molecular responses (MR; MR ≥4.0), resulting in a TFR of 59% in the first year and 55% in the second year after TKI discontinuation.⁶

In our study, imatinib remains the primary treatment option due to cost and accessibility factors; however, a significant proportion of patients require switching to a second-generation TKI, predominantly nilotinib, often because of treatment failure or intolerance. Treatment failure rates are higher than in developed countries, likely due to late presentation, high-risk disease, and potential issues related to drug quality or adherence.³⁰ Monthly prescription refills and follow-up in our services ensured better adherence. However, 1.4% of the patients in this study remained non-compliant despite access to regular treatment refills and disease education, whereas 12.3% of cases were unable to access second-line treatment after imatinib failure due to the high treatment cost. In this study, among 73 patients, 2 (2.7%, both cases of first-line imatinib failures) progressed to the aggressive phase and subsequently into blast crisis due to the lack of available second-line options.

The observed benefit of switching to nilotinib in treatment-adherent imatinib-failure cases is consistent with the existing literature, which has demonstrated improved treatment responses with the use of second-generation TKIs, particularly after imatinib failure.^30,31

We faced challenges in accessing second-line treatment options other than nilotinib in our region. Additionally, the high cost of tyrosine kinase domain (TKD) mutation analysis prevented adherence to international recommendations for switching therapies based on TKD mutation analysis.³² This was reflected by the fact that only one patient in the current study underwent mutational analysis on treatment failure.

A positive finding of our study was the high PFS rate despite the higher proportion of atypical FISH findings, 77.2% of patients having high/intermediate ELTS risk scores, and many patients falling into the warning ELN category (23.4% patients on imatinib and 11.1% patients on nilotinib). In our study, imatinib was well-tolerated as a first-line treatment in 85.4% of patients; this aligns with our center’s efforts to provide cost-effective treatment options that improve patient care, and this approach seemed adequate. However, the shorter median follow-up and higher imatinib-failure rates, potentially due to inconsistent drug access or substandard drug quality compared with that in developed world cohorts, suggest ongoing challenges in achieving optimal, long-term treatment outcomes, including TFRs, given the limited TKI supply in our region.^8,30

Our study’s strengths include detailed clinical and cytogenetic characterization, regular disease monitoring using PCR, and use of real-world treatment data. Limitations of the study include a relatively small sample size; an urban, tertiary care focus; possible selection bias (patients with easier access to medical services); and lost-to-follow-up cases, a common problem in LMICs.^13–15,30 A key limitation of the present study was the relatively small number of patients who received nilotinib (n = 9). This imbalance limited the statistical power and precision of comparative analyses between the treatment groups and may have resulted in unstable effect estimates. Therefore, the observed differences in response and survival outcomes between the two groups should be interpreted with caution and considered exploratory rather than definitive. The study might not fully represent rural and socioeconomically disadvantaged populations, which are more likely to have impaired clinical outcomes.^14,16

Conclusion

The study reveals the real-world clinical situation of CML treatment in Pakistan, where TKIs (first generation) are the therapeutic backbone. It outlines the complexities of CML treatment in resource-constrained settings, such as the role played by a younger population of patients, urban-based health care, and lack of access to second-line treatment. Even though the data showed a promising PFS and tolerance for imatinib in a structured follow-up, lack of TKD mutation screening and other TKIs hampered the achievement of deeper molecular remission and TFR. Public–private partnerships, policy changes, and international cooperation will play a stronger role in addressing the imbalance, bridging the treatment gap, and improving treatment outcomes for patients with CML in LMICs.

Supplemental Material

sj-pdf-1-imr-10.1177_03000605261454643 - Supplemental material for Chronic myeloid leukemia in resource-limited settings: Navigating treatment challenges amid limited tyrosine kinase inhibitor access

Supplemental material, sj-pdf-1-imr-10.1177_03000605261454643 for Chronic myeloid leukemia in resource-limited settings: Navigating treatment challenges amid limited tyrosine kinase inhibitor access by Zunaira Aamir, Bushra Kaleem, Syed Jawad Hassan, Aqsa Hafeez, Ambar Jabeen, Syeda Ambreen Zehra and Neelum Mansoor in Journal of International Medical Research

Footnotes

Acknowledgments

Not applicable.

Author contributions

ZA: Contributed to the conception of the study and drafting of the manuscript; BK: Data analysis and reviewing the manuscript for critical intellectual content; SJH: Drafting of the manuscript; AH: Data extraction; AJ: Data extraction; SAZ: Data extraction and interpretation; NM: Study design, critical review, and final approval of the manuscript.

Data availability statement

The data that support the findings of this study are available from the corresponding author, ZA, upon reasonable request

Declaration of conflicting interests

The authors report that there are no competing interests to declare.

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

ORCID iDs

Zunaira Aamir

Neelum Mansoor

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